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<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
<html><head><meta http-equiv="Content-Type" content="text/html; charset=utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge,IE=9,chrome=1"><meta name="generator" content="MATLAB R2018b"><title>Generalized Geometry Projection</title><style type="text/css">.rtcContent { padding: 30px; } .S0 { margin: 3px 10px 5px 4px; padding: 0px; line-height: 28.7999992370605px; min-height: 0px; white-space: pre-wrap; color: rgb(213, 80, 0); font-family: Helvetica, Arial, sans-serif; font-style: normal; font-size: 24px; font-weight: normal; text-align: left; }
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.S11 { border-left: 1px solid rgb(233, 233, 233); border-right: 1px solid rgb(233, 233, 233); border-top: 1px solid rgb(233, 233, 233); border-bottom: 0px none rgb(0, 0, 0); border-radius: 0px; padding: 6px 45px 0px 13px; line-height: 17.2339992523193px; min-height: 18px; white-space: nowrap; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, 'Courier New', monospace; font-size: 14px; }</style></head><body><div class = rtcContent><h1 class = 'S0'><span>Generalized Geometry Projection</span></h1><div class = 'S1'><span>Author Simone Coniglio, 12/09/2019</span></div><div class = 'S1'><span>This is an introduction to a Matlab implementation of Generalized Geometry Projection approach for topology optimization.</span></div><div class = 'S1'><span>In this approach geometric primitives are projected on a Finite Element Mesh and assembled together to build the solution. </span></div><h2 class = 'S2'><span>Problem set-up</span></h2><div class = 'S1'><span>In this section of the Matlab code we define several </span><span style=' font-weight: bold;'>parameters</span><span> needed for the </span><span style=' font-weight: bold;'>Generalized Geometry Projection</span><span>.</span></div><div class="CodeBlock"><div class="inlineWrapper"><div class = 'S3'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">%-------------------------------------------------------------</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">% This is the file GGP.html you can redistribute it and/or</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">% modify it under the terms of the GNU General Public License as </span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">% published by the Free Software Foundation; either version 3 of </span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">% the License, or (at your option) any later version.</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">% </span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">% This code is distributed in the hope that it will be useful,</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">% but WITHOUT ANY WARRANTY; without even the implied warranty of</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">% GNU General Public License for more details.</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">% </span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">% You should have received a copy of the GNU General Public License</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">% (file COPYING) along with this file. If not, see </span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">% <http://www.gnu.org/licenses/>.</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">%</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">% Version Nov 2019.</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">% Simone Coniglio <simone.coniglio@airbus.com></span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">% Propulsion Airframe Stress Transverse,</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">% 31300 Toulouse, France.</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">%</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">% GGP parameters</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>stopping_criteria=</span><span style="color: rgb(160, 32, 240);">'change'</span><span>; </span><span style="color: rgb(34, 139, 34);">%stopping criteria of the optimization algorithm either change or KKT norm</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>nelx=60;nely=30; </span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>BC=</span><span style="color: rgb(160, 32, 240);">'Short_Cantilever'</span><span>;</span><span style="color: rgb(34, 139, 34);">%L-shape %Short_Cantilever%MBB</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>p.method=</span><span style="color: rgb(160, 32, 240);">'GP'</span><span>;</span><span style="color: rgb(34, 139, 34);">%MMC%MNA %GP this change the function employed for the evaluation of local volume fraction</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>q=1;</span><span style="color: rgb(34, 139, 34);">%q=1</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>p.zp=1 ;</span><span style="color: rgb(34, 139, 34);">% parameter for p-norm/mean regularization</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>p.alp=1; </span><span style="color: rgb(34, 139, 34);">%parameter for MMC</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>p.epsi=0.866;</span><span style="color: rgb(34, 139, 34);">% parameter for MMC</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>p.bet=1e-3; </span><span style="color: rgb(34, 139, 34);">%parameter for MMC</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>p.deltamin=1e-6; </span><span style="color: rgb(34, 139, 34);">%parameter for GP</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>p.r=.5;</span><span style="color: rgb(34, 139, 34);">%parameter for GP</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>minh=1;</span><span style="color: rgb(34, 139, 34);">% minimal bar thickness</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>p.sigma=1;</span><span style="color: rgb(34, 139, 34);">%parameter for MNA</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>p.gammav=1;</span><span style="color: rgb(34, 139, 34);">%parameter for GP</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>p.gammac=3;</span><span style="color: rgb(34, 139, 34);">%parameter for GP</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>p.penalty=3;</span><span style="color: rgb(34, 139, 34);">%parameter for MNA</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>p.aggregation=</span><span style="color: rgb(160, 32, 240);">'KSl'</span><span>; </span><span style="color: rgb(34, 139, 34);">%parameter for the aggregation function to be used</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">% IE= Induced Exponential % KS= KS function %KSl= lowerbound KS function</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">% p-norm %p-mean</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>p.ka=10; </span><span style="color: rgb(34, 139, 34);">% parameter for the aggregation constant</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>p.saturation=true; </span><span style="color: rgb(34, 139, 34);">% switch for saturation</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>ncx=1; </span><span style="color: rgb(34, 139, 34);">% number of components in the x direction</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>ncy=1; </span><span style="color: rgb(34, 139, 34);">% number of components in the y direction</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>Ngp=2; </span><span style="color: rgb(34, 139, 34);">% number of Gauss point per sampling window</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>R=0.5; </span><span style="color: rgb(34, 139, 34);">% radius of the sampling window (infty norm)</span></span></div></div><div class="inlineWrapper"><div class = 'S5'><span style="white-space: pre;"><span>initial_d=0.5; </span><span style="color: rgb(34, 139, 34);">% initial mass variable adopted for MNA and GP</span></span></div></div></div><div class = 'S6'><span>Generate a </span><span style=' font-weight: bold;'>folder</span><span> and a prefix to save images </span><span style=' font-weight: bold;'>optimization history</span><span>:</span></div><div class="CodeBlock"><div class="inlineWrapper"><div class = 'S3'><span style="white-space: pre;"><span>rs=replace(num2str(R,</span><span style="color: rgb(160, 32, 240);">'%3.2f'</span><span>),</span><span style="color: rgb(160, 32, 240);">'.'</span><span>,</span><span style="color: rgb(160, 32, 240);">'_'</span><span>);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>folder_name=[</span><span style="color: rgb(160, 32, 240);">'Optimization_history_'</span><span>,BC,p.method,</span><span style="color: rgb(160, 32, 240);">'nelx_'</span><span>,num2str(nelx),</span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(160, 32, 240);">'nely_'</span><span>,num2str(nely),</span><span style="color: rgb(160, 32, 240);">'_R_'</span><span>,rs,</span><span style="color: rgb(160, 32, 240);">'_Ngp_'</span><span>,num2str(Ngp),</span><span style="color: rgb(160, 32, 240);">'_SC_'</span><span>,stopping_criteria];</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>image_prefix=[BC,p.method,</span><span style="color: rgb(160, 32, 240);">'nelx_'</span><span>,num2str(nelx),</span><span style="color: rgb(160, 32, 240);">'nely_'</span><span>,num2str(nely),</span><span style="color: rgb(160, 32, 240);">'_R_'</span><span>,rs,</span><span style="color: rgb(160, 32, 240);">'_Ngp_'</span><span>,num2str(Ngp)];</span></span></div></div><div class="inlineWrapper outputs"><div class = 'S7'><span style="white-space: pre;"><span>mkdir(folder_name)</span></span></div><div class = 'S8'><div class="inlineElement eoOutputWrapper embeddedOutputsWarningElement" uid="9B0727E4" data-testid="output_0" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="diagnosticMessage-wrapper diagnosticMessage-warningType"><div class="diagnosticMessage-messagePart">Warning: Directory already exists.</div><div class="diagnosticMessage-stackPart"></div></div></div></div></div><div class="inlineWrapper"><div class = 'S9'><span style="white-space: pre;"><span>Path=[folder_name,</span><span style="color: rgb(160, 32, 240);">'/'</span><span>];</span></span></div></div></div><div class = 'S6'><span>Define </span><span style=' font-weight: bold;'>Material properties</span><span>:</span></div><div class="CodeBlock"><div class="inlineWrapper"><div class = 'S3'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">% MATERIAL PROPERTIES</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>p.E0 = 1;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>p.Emin = 1e-6;</span></span></div></div><div class="inlineWrapper"><div class = 'S5'><span style="white-space: pre;"><span>nu = 0.3;</span></span></div></div></div><div class = 'S6'><span>Prepare </span><span style=' font-weight: bold;'>finite element analysis</span></div><div class="CodeBlock"><div class="inlineWrapper"><div class = 'S3'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">% PREPARE FINITE ELEMENT ANALYSIS</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>A11 = [12 3 -6 -3; 3 12 3 0; -6 3 12 -3; -3 0 -3 12];</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>A12 = [-6 -3 0 3; -3 -6 -3 -6; 0 -3 -6 3; 3 -6 3 -6];</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>B11 = [-4 3 -2 9; 3 -4 -9 4; -2 -9 -4 -3; 9 4 -3 -4];</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>B12 = [ 2 -3 4 -9; -3 2 9 -2; 4 9 2 3; -9 -2 3 2];</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>KE = 1/(1-nu^2)/24*([A11 A12;A12' A11]+nu*[B11 B12;B12' B11]);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>nodenrs = reshape(1:(1+nelx)*(1+nely),1+nely,1+nelx);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>edofVec = reshape(2*nodenrs(1:end-1,1:end-1)+1,nelx*nely,1);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>edofMat = repmat(edofVec,1,8)+repmat([0 1 2*nely+[2 3 0 1] -2 -1],nelx*nely,1);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>iK = reshape(kron(edofMat,ones(8,1))',64*nelx*nely,1);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>jK = reshape(kron(edofMat,ones(1,8))',64*nelx*nely,1);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>U = zeros(2*(nely+1)*(nelx+1),1);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">%define the nodal coordinates</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>[Yy,Xx]=find(nodenrs);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>Yy=nely+1-Yy;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>Xx=Xx-1;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">% Element connectivity</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>enodeMat=edofMat(:,[2,4,6,8])/2;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">% DEFINE LOADS AND SUPPORTS </span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(0, 0, 255);">switch </span><span>BC</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(0, 0, 255);">case </span><span style="color: rgb(160, 32, 240);">'MBB'</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> excitation_node=1;excitation_direction=2;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> amplitude=-1;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> F = sparse(2*(excitation_node-1)+excitation_direction,1,amplitude,2*(nely+1)*(nelx+1),1);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> fixednodes=[find(Xx==min(Xx));(nelx+1)*(nely+1)];fixed_dir=[ones(nely+1,1);2];</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> fixeddofs=2*(fixednodes-1)+fixed_dir;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> emptyelts=[]; fullelts = [];</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(0, 0, 255);">case </span><span style="color: rgb(160, 32, 240);">'Short_Cantilever'</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> excitation_node=find((Xx==max(Xx))&(Yy==fix(0.5*min(Yy)+0.5*max(Yy))));excitation_direction=2;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> amplitude=-1;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> F = sparse(2*(excitation_node-1)+excitation_direction,1,amplitude,2*(nely+1)*(nelx+1),1);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> fixednodes=repmat(find(Xx==min(Xx)),2,1);fixed_dir=[ones(nely+1,1);2*ones(nely+1,1)];</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> fixeddofs=2*(fixednodes-1)+fixed_dir(:);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> emptyelts=[]; fullelts = [];</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(0, 0, 255);">case </span><span style="color: rgb(160, 32, 240);">'L-shape'</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> excitation_node=find((Xx==max(Xx))&(Yy==fix(0.5*min(Yy)+0.5*max(Yy))));excitation_direction=2;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> amplitude=-1;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> F = sparse(2*(excitation_node-1)+excitation_direction,1,amplitude,2*(nely+1)*(nelx+1),1);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> fixednodes=repmat(find(Yy==max(Yy)),2,1);fixed_dir=[ones(nelx+1,1),2*ones(nelx+1,1)];</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> fixeddofs=2*(fixednodes-1)+fixed_dir(:);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> emptyelts=find(xc>=(((max(Xx)+min(Xx))/2))&(yc>=((max(Yy)+min(Yy))/2)));</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> fullelts = [];</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(0, 0, 255);">otherwise</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> error(</span><span style="color: rgb(160, 32, 240);">'BC string should be a valid entry: ''MBB'',''L-Shape'',''Short_Cantilever'''</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(0, 0, 255);">end</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>alldofs = </span><span class="warning_squiggle_rte">[</span><span>1:2*(nely+1)*(nelx+1)];</span></span></div></div><div class="inlineWrapper"><div class = 'S5'><span style="white-space: pre;"><span>freedofs = setdiff(alldofs,fixeddofs);</span></span></div></div></div><h2 class = 'S2'><span>Prepare the </span><span style=' font-weight: bold;'>Generalized Geometry Projection:</span></h2><div class = 'S1'><span>Compute the element centroid coordinates:</span></div><div class="CodeBlock"><div class="inlineWrapper"><div class = 'S3'><span style="white-space: pre;"><span>xc=mean(Xx(enodeMat'));</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>yc=mean(Yy(enodeMat'));</span></span></div></div><div class="inlineWrapper"><div class = 'S5'><span style="white-space: pre;"><span>centroid_coordinate=[xc(:),yc(:)];</span></span></div></div></div><div class = 'S6'><span>Compute </span><span style=' font-weight: bold;'>Gauss point coordinates and weights </span><span>in a squared sampling window </span><span style="vertical-align:-5px"><img src="data:image/png;base64,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" width="64.5" height="19" /></span><span> centred in the origin</span></div><div class="CodeBlock"><div class="inlineWrapper"><div class = 'S3'><span style="white-space: pre;"><span>a=-R;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>b=R;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>[gpc,wc]=lgwt(Ngp,a,b);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>[gpcx,gpcy]=meshgrid(gpc,gpc);</span></span></div></div><div class="inlineWrapper"><div class = 'S5'><span style="white-space: pre;"><span>gauss_weight=wc*wc';</span></span></div></div></div><div class = 'S6'><span>Repeat the value ones for each element in the mesh</span></div><div class="CodeBlock"><div class="inlineWrapper"><div class = 'S3'><span style="white-space: pre;"><span>gpcx=reshape((repmat(gpcx(:),1,size(centroid_coordinate,1)))',[],1);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>gpcy=reshape((repmat(gpcy(:),1,size(centroid_coordinate,1)))',[],1);</span></span></div></div><div class="inlineWrapper"><div class = 'S5'><span style="white-space: pre;"><span>gauss_weight=reshape((repmat(gauss_weight(:),1,size(centroid_coordinate,1)))',[],1);</span></span></div></div></div><div class = 'S6'><span>translate the sampling window Gauss points of the element centroid coordinates</span></div><div class="CodeBlock"><div class="inlineWrapper"><div class = 'S3'><span style="white-space: pre;"><span>cc=repmat(centroid_coordinate,Ngp^2,1);</span></span></div></div><div class="inlineWrapper"><div class = 'S5'><span style="white-space: pre;"><span>gauss_point=cc+[gpcx,gpcy];</span></span></div></div></div><div class = 'S6'><span>Avoid to evaluate repeated value of sampling window gauss point coordinates:</span></div><div class="CodeBlock"><div class="inlineWrapper"><div class = 'S10'><span style="white-space: pre;"><span>[ugp,~,idgp]=unique(gauss_point,</span><span style="color: rgb(160, 32, 240);">'rows'</span><span>);</span></span></div></div></div><h2 class = 'S2'><span>Initialize design variable vector:</span></h2><div class = 'S1'><span>The initial design is composed of couples of crossed components regularly disposed in the mesh. </span></div><div class="CodeBlock"><div class="inlineWrapper"><div class = 'S3'><span style="white-space: pre;"><span>xp=linspace(min(Xx),max(Xx),ncx+2);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>yp=linspace(min(Yy),max(Yy),ncy+2); </span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>[xx,yy]=meshgrid(xp,yp);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>Xc=repmat(xx(:),2,1); </span><span style="color: rgb(34, 139, 34);">%component center X</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>Yc=repmat(yy(:),2,1); </span><span style="color: rgb(34, 139, 34);">%component center Y</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>Lc=2*sqrt((nelx/(ncx+2))^2+(nely/(ncy+2))^2)*ones(size(Xc)); </span><span style="color: rgb(34, 139, 34);">%component length L</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>Tc=atan2(nely/ncy,nelx/ncx)*[ones(length(Xc)/2,1);-ones(length(Xc)/2,1)];</span><span style="color: rgb(34, 139, 34);">% component orientation angle tetha</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>hc=2*ones(length(Xc),1); </span><span style="color: rgb(34, 139, 34);">% component h</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>Mc=initial_d*ones(size(Xc)); </span><span style="color: rgb(34, 139, 34);">% component mass (For MNA and GP)</span></span></div></div><div class="inlineWrapper"><div class = 'S5'><span style="white-space: pre;"><span>Xg=reshape([Xc,Yc,Lc,hc,Tc,Mc]',[],1);</span></span></div></div></div><h2 class = 'S2'><span>Build upper and lower bounds of the design problem</span></h2><div class="CodeBlock"><div class="inlineWrapper"><div class = 'S3'><span style="white-space: pre;"><span>Xl=min(Xx-1)*ones(size(Xc));Xu=max(Xx+1)*ones(size(Xc));</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>Yl=min(Yy-1)*ones(size(Xc));Yu=max(Yy+1)*ones(size(Xc));</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>Ll=0*ones(size(Xc));Lu=sqrt(nelx^2+nely^2)*ones(size(Xc));</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>hl=minh*ones(size(Xc));hu=sqrt(nelx^2+nely^2)*ones(size(Xc));</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>Tl=-2*pi*ones(size(Xc));Tu=2*pi*ones(size(Xc));</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>Ml=0*ones(size(Xc));Mu=ones(size(Xc));</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>lower_bound=reshape([Xl,Yl,Ll,hl,Tl,Ml]',[],1);</span></span></div></div><div class="inlineWrapper"><div class = 'S5'><span style="white-space: pre;"><span>upper_bound=reshape([Xu,Yu,Lu,hu,Tu,Mu]',[],1);</span></span></div></div></div><div class = 'S6'><span style=' font-weight: bold;'>Scale</span><span> the </span><span style=' font-weight: bold;'>design variable vector</span><span> accordingly </span><span style="vertical-align:-5px"><img src="data:image/png;base64,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" width="75.5" height="19" /></span><span>:</span></div><div class="CodeBlock"><div class="inlineWrapper"><div class = 'S10'><span style="white-space: pre;"><span>X=(Xg-lower_bound)./(upper_bound-lower_bound);</span></span></div></div></div><h2 class = 'S2'><span>MMA initialization:</span></h2><div class="CodeBlock"><div class="inlineWrapper"><div class = 'S3'><span style="white-space: pre;"><span>loop = 0;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>m = 1;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>n = length(X(:));</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>epsimin = 0.0000001;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>eeen = ones(n,1);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>eeem = ones(m,1);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>zeron = zeros(n,1);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>zerom = zeros(m,1);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>xval = X(:);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>xold1 = xval;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>xold2 = xval;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>xmin = zeron;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>xmax = eeen;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>low = xmin;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>upp = xmax;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>C = 1000*eeem;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>d = 0*eeem;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>a0 = 1;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>a = zerom;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>outeriter = 0;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>maxoutit = 2000;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>kkttol =0.001;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>changetol=0.001;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>kktnorm = kkttol+10;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>outit = 0;</span></span></div></div><div class="inlineWrapper"><div class = 'S5'><span style="white-space: pre;"><span>change=1;</span></span></div></div></div><div class = 'S6'><span>choose the allowable </span><span style=' font-weight: bold;'>volfrac:</span></div><div class="CodeBlock"><div class="inlineWrapper"><div class = 'S10'><span style="white-space: pre;"><span>volfrac=.4;</span></span></div></div></div><div class = 'S6'><span>Prepare plots and quantity storage:</span></div><div class="CodeBlock"><div class="inlineWrapper"><div class = 'S3'><span style="white-space: pre;"><span>cvec=zeros(maxoutit,1);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>vvec=cvec;ovvec=cvec;gvec=cvec;pvec=cvec;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>plot_rate=10;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">%initialize variables for plot</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>tt=0:0.005:(2*pi);tt=repmat(tt,length(Xc),1);</span></span></div></div><div class="inlineWrapper"><div class = 'S5'><span style="white-space: pre;"><span>cc=cos(tt);ss=sin(tt);</span></span></div></div></div><div class = 'S6'><span>Initialize the stopping criterion</span></div><div class="CodeBlock"><div class="inlineWrapper"><div class = 'S3'><span style="white-space: pre;"><span style="color: rgb(0, 0, 255);">switch </span><span>stopping_criteria</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(0, 0, 255);">case </span><span style="color: rgb(160, 32, 240);">'kktnorm'</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> stop_cond=outit < maxoutit && kktnorm>kkttol;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(0, 0, 255);">case </span><span style="color: rgb(160, 32, 240);">'change'</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> stop_cond=outit < maxoutit &&change>changetol;</span></span></div></div><div class="inlineWrapper"><div class = 'S5'><span style="white-space: pre;"><span style="color: rgb(0, 0, 255);">end</span></span></div></div></div><h2 class = 'S2'><span>Start the design loop:</span></h2><div class="CodeBlock"><div class="inlineWrapper"><div class = 'S3'><span style="white-space: pre;"><span style="color: rgb(0, 0, 255);">while</span><span> stop_cond</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> outit = outit+1;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> outeriter = outeriter+1;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(34, 139, 34);">%Compute the smooth characteristic functions and gradients for each component </span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(34, 139, 34);">% on each sampling window Gauss point (Can support GPU)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> [W,dW_dX,dW_dY,dW_dT,dW_dL,dW_dh]=Wgp(ugp(:,1),ugp(:,2),Xg,p);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(34, 139, 34);">%Compute local volume fractions and gradients using generalized projection</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(34, 139, 34);">% delta is for densities, deltac for Young modulus</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> delta=sum(reshape(W(:,idgp).*repmat(gauss_weight(:)',size(W,1),1),size(W,1),[],Ngp^2),3)</span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> ./sum(reshape(repmat(gauss_weight(:)',size(W,1),1),size(W,1),[],Ngp^2),3);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> ddelta_dX=sum(reshape(dW_dX(:,idgp).*repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3)</span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> ./sum(reshape(repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> ddelta_dY=sum(reshape(dW_dY(:,idgp).*repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3)</span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> ./sum(reshape(repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> ddelta_dT=sum(reshape(dW_dT(:,idgp).*repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3)</span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> ./sum(reshape(repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> ddelta_dL=sum(reshape(dW_dL(:,idgp).*repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3)</span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> ./sum(reshape(repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> ddelta_dh=sum(reshape(dW_dh(:,idgp).*repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3)</span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> ./sum(reshape(repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> delta_c=sum(reshape(W(:,idgp).^q.*repmat(gauss_weight(:)',size(W,1),1),size(W,1),[],Ngp^2),3)</span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> ./sum(reshape(repmat(gauss_weight(:)',size(W,1),1),size(W,1),[],Ngp^2),3);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> ddelta_c_dX=sum(reshape(q*dW_dX(:,idgp).*W(:,idgp).^(q-1).*repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3)</span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> ./sum(reshape(repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> ddelta_c_dY=sum(reshape(q*dW_dY(:,idgp).*W(:,idgp).^(q-1).*repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3)</span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> ./sum(reshape(repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> ddelta_c_dT=sum(reshape(q*dW_dT(:,idgp).*W(:,idgp).^(q-1).*repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3)</span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> ./sum(reshape(repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> ddelta_c_dL=sum(reshape(q*dW_dL(:,idgp).*W(:,idgp).^(q-1).*repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3)</span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> ./sum(reshape(repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> ddelta_c_dh=sum(reshape(q*dW_dh(:,idgp).*W(:,idgp).^(q-1).*repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3)</span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> ./sum(reshape(repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(34, 139, 34);">% model update </span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(34, 139, 34);">% compute young modulus and gradients</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> [E,dE,dE_dm]=model_updateM(delta_c,p,X);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dE_dX=dE.*ddelta_c_dX;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dE_dY=dE.*ddelta_c_dY;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dE_dT=dE.*ddelta_c_dT;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dE_dL=dE.*ddelta_c_dL;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dE_dh=dE.*ddelta_c_dh;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> E=full(reshape(E(:),nely,nelx));</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(34, 139, 34);">%compute densities</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> [rho,drho_ddelta,drho_dm]=model_updateV(delta,p,X);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> drho_dX=drho_ddelta.*ddelta_dX;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> drho_dY=drho_ddelta.*ddelta_dY;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> drho_dT=drho_ddelta.*ddelta_dT;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> drho_dL=drho_ddelta.*ddelta_dL;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> drho_dh=drho_ddelta.*ddelta_dh;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> xPhys=full(reshape(rho(:),nely,nelx));</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(34, 139, 34);">%Take in account passive elements</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> xPhys(emptyelts) = 0;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> xPhys(fullelts) = 1;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> E(emptyelts) = p.Emin;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> E(fullelts) = p.E0;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(34, 139, 34);">% FE-ANALYSIS</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> sK = reshape(KE(:)*(E(:)'),64*nelx*nely,1);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> K = sparse(iK,jK,sK); K = (K+K')/2;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> U(freedofs) = K(freedofs,freedofs)\F(freedofs);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(34, 139, 34);">% OBJECTIVE FUNCTION AND SENSITIVITY ANALYSIS</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> ce = reshape(sum((U(edofMat)*KE).*U(edofMat),2),nely,nelx);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> c = sum(sum((E).*ce));</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> v=mean(xPhys(:));</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dc_dE = -ce;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dc_dE(emptyelts) = 0;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dc_dE(fullelts) = 0;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dc_dX=dE_dX*dc_dE(:);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dc_dY=dE_dY*dc_dE(:);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dc_dL=dE_dL*dc_dE(:);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dc_dh=dE_dh*dc_dE(:);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dc_dT=dE_dT*dc_dE(:);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dc_dm=dE_dm*dc_dE(:);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dc=zeros(size(X));</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dc(1:6:end)=dc_dX;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dc(2:6:end)=dc_dY;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dc(3:6:end)=dc_dL;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dc(4:6:end)=dc_dh;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dc(5:6:end)=dc_dT;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dc(6:6:end)=dc_dm;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dv_dxPhys = ones(nely,nelx)/nelx/nely;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dv_dxPhys(emptyelts) = 0;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dv_dxPhys(fullelts) = 0;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dv_dX=drho_dX*dv_dxPhys(:);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dv_dY=drho_dY*dv_dxPhys(:);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dv_dL=drho_dL*dv_dxPhys(:);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dv_dh=drho_dh*dv_dxPhys(:);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dv_dT=drho_dT*dv_dxPhys(:);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dv_dm=drho_dm*dv_dxPhys(:);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dv=zeros(size(X));</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dv(1:6:end)=dv_dX;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dv(2:6:end)=dv_dY;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dv(3:6:end)=dv_dL;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dv(4:6:end)=dv_dh;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dv(5:6:end)=dv_dT;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dv(6:6:end)=dv_dm;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(34, 139, 34);">% store the output for plot</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> cvec(outit)=c;vvec(outit)=v;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);"> %% PRINT RESULTS</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> fprintf(</span><span style="color: rgb(160, 32, 240);">' It.:%5i Obj.:%4.3e Vol.:%7.3f kktnorm.:%7.3f ch.:%7.3f\n'</span><span>,outit,c, </span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> mean(xPhys(:)),kktnorm,change);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(34, 139, 34);">% pass scaled objective and constraint function and sensitivities to MMA</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> f0val=log(c+1);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> fval=</span><span class="warning_squiggle_rte">[</span><span>(v-volfrac)/volfrac]*100;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> df0dx=(dc(:)/(c+1).*(upper_bound(:)-lower_bound(:)));</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> dfdx=</span><span class="warning_squiggle_rte">[</span><span>dv(:)'/volfrac]*100.*(upper_bound(:)-lower_bound(:))';</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(34, 139, 34);">%plot every plot_rate iterations</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(0, 0, 255);">if </span><span>rem(outit,plot_rate)==0</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(34, 139, 34);">%convergence plot</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> figure(3)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> subplot(2,1,1)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> plot(1:outit,cvec(1:outit),</span><span style="color: rgb(160, 32, 240);">'bo'</span><span>,</span><span style="color: rgb(160, 32, 240);">'MarkerFaceColor'</span><span>,</span><span style="color: rgb(160, 32, 240);">'b'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> grid </span><span style="color: rgb(160, 32, 240);">on</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> hold </span><span style="color: rgb(160, 32, 240);">on</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> scatter(outit,c,</span><span style="color: rgb(160, 32, 240);">'k'</span><span>,</span><span style="color: rgb(160, 32, 240);">'fill'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> hold </span><span style="color: rgb(160, 32, 240);">off</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> text(outit,c,[</span><span style="color: rgb(160, 32, 240);">'C ='</span><span>,num2str(c,</span><span style="color: rgb(160, 32, 240);">'%4.2f'</span><span>),</span><span style="color: rgb(160, 32, 240);">' at iteration '</span><span>, num2str(outit)],</span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(160, 32, 240);">'VerticalAlignment'</span><span>,</span><span style="color: rgb(160, 32, 240);">'bottom'</span><span>,</span><span style="color: rgb(160, 32, 240);">'HorizontalAlignment'</span><span>,</span><span style="color: rgb(160, 32, 240);">'right'</span><span>,</span><span style="color: rgb(160, 32, 240);">'FontSize'</span><span>,24,</span><span style="color: rgb(160, 32, 240);">'FontWeight'</span><span>,</span><span style="color: rgb(160, 32, 240);">'bold'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> xlabel(</span><span style="color: rgb(160, 32, 240);">'iter'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> ylabel(</span><span style="color: rgb(160, 32, 240);">'C'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> subplot(2,1,2)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> plot(1:outit,vvec(1:outit)*100,</span><span style="color: rgb(160, 32, 240);">'ro'</span><span>,</span><span style="color: rgb(160, 32, 240);">'MarkerFaceColor'</span><span>,</span><span style="color: rgb(160, 32, 240);">'r'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> grid </span><span style="color: rgb(160, 32, 240);">on</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> hold </span><span style="color: rgb(160, 32, 240);">on</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> scatter(outit,mean(xPhys(:))*100,</span><span style="color: rgb(160, 32, 240);">'k'</span><span>,</span><span style="color: rgb(160, 32, 240);">'fill'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> hold </span><span style="color: rgb(160, 32, 240);">off</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> text(outit,mean(xPhys(:))*100,[</span><span style="color: rgb(160, 32, 240);">'V = '</span><span>,num2str(mean(xPhys(:))*100,</span><span style="color: rgb(160, 32, 240);">'%4.2f'</span><span>),</span><span style="color: rgb(160, 32, 240);">'% at iteration '</span><span>, num2str(outit)],</span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(160, 32, 240);">'VerticalAlignment'</span><span>,</span><span style="color: rgb(160, 32, 240);">'bottom'</span><span>,</span><span style="color: rgb(160, 32, 240);">'HorizontalAlignment'</span><span>,</span><span style="color: rgb(160, 32, 240);">'right'</span><span>,</span><span style="color: rgb(160, 32, 240);">'FontSize'</span><span>,24,</span><span style="color: rgb(160, 32, 240);">'FontWeight'</span><span>,</span><span style="color: rgb(160, 32, 240);">'bold'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> xlabel(</span><span style="color: rgb(160, 32, 240);">'iter'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> ylabel(</span><span style="color: rgb(160, 32, 240);">'V [%]'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> print([Path,image_prefix,</span><span style="color: rgb(160, 32, 240);">'convergence'</span><span>],</span><span style="color: rgb(160, 32, 240);">'-dpng'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);"> %% PLOT DENSITIES</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> figure(1)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> map=colormap(gray);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> map=map(end:-1:1,:);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> caxis([0 1])</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span class="warning_squiggle_rte">patchplot2</span><span> = patch(</span><span style="color: rgb(160, 32, 240);">'Vertices'</span><span>,[Xx,Yy],</span><span style="color: rgb(160, 32, 240);">'Faces'</span><span>,edofMat(:,[2,4,6,8])/2,</span><span style="color: rgb(160, 32, 240);">'FaceVertexCData'</span><span>,(1-xPhys(:))*[1 1 1],</span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(160, 32, 240);">'FaceColor'</span><span>,</span><span style="color: rgb(160, 32, 240);">'flat'</span><span>,</span><span style="color: rgb(160, 32, 240);">'EdgeColor'</span><span>,</span><span style="color: rgb(160, 32, 240);">'none'</span><span>); axis </span><span style="color: rgb(160, 32, 240);">equal</span><span>; axis </span><span style="color: rgb(160, 32, 240);">off</span><span>; hold </span><span style="color: rgb(160, 32, 240);">on</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> hold </span><span style="color: rgb(160, 32, 240);">on</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> fill([min(Xx),max(Xx),max(Xx),min(Xx)],[min(Yy),min(Yy),max(Yy),max(Yy)],</span><span style="color: rgb(160, 32, 240);">'w'</span><span>,</span><span style="color: rgb(160, 32, 240);">'FaceAlpha'</span><span>,0.)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> scatter(Xx(fixednodes(fixed_dir==1)),Yy(fixednodes(fixed_dir==1)),</span><span style="color: rgb(160, 32, 240);">'>b'</span><span>,</span><span style="color: rgb(160, 32, 240);">'filled'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> scatter(Xx(fixednodes(fixed_dir==2)),Yy(fixednodes(fixed_dir==2)),</span><span style="color: rgb(160, 32, 240);">'^b'</span><span>,</span><span style="color: rgb(160, 32, 240);">'filled'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> scal=10;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> quiver(Xx(excitation_node),Yy(excitation_node)+scal*(excitation_direction==2),excitation_direction==1,</span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> -(excitation_direction==2), scal,</span><span style="color: rgb(160, 32, 240);">'r'</span><span>,</span><span style="color: rgb(160, 32, 240);">'Linewidth'</span><span>,2)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> colormap(map)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> colorbar</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> drawnow</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> hold </span><span style="color: rgb(160, 32, 240);">off</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> axis([min(Xx),max(Xx),min(Yy),max(Yy)])</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> print([Path,</span><span style="color: rgb(160, 32, 240);">'density_'</span><span>,num2str(outit-1,</span><span style="color: rgb(160, 32, 240);">'%03d'</span><span>)],</span><span style="color: rgb(160, 32, 240);">'-dpng'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);"> %% Component Plot</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> figure(2)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> Xc=Xg(1:6:end);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> Yc=Xg(2:6:end);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> Lc=Xg(3:6:end);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> hc=Xg(4:6:end);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> Tc=Xg(5:6:end) ;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> Mc=Xg(6:6:end) ;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> C0=repmat(cos(Tc),1,size(cc,2));S0=repmat(sin(Tc),1,size(cc,2));</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> xxx=repmat(Xc(:),1,size(cc,2))+cc;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> yyy=repmat(Yc(:),1,size(cc,2))+ss;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> xi=C0.*(xxx-Xc)+S0.*(yyy-Yc);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> Eta=-S0.*(xxx-Xc)+C0.*(yyy-Yc);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> [dd]=norato_bar(xi,Eta,repmat(Lc(:),1,size(cc,2)),repmat(hc(:),1,size(cc,2)));</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> xn=repmat(Xc,1,size(cc,2))+dd.*cc;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> yn=repmat(Yc,1,size(cc,2))+dd.*ss;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> tolshow=0.1;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> Shown_compo=find(Mc>tolshow);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> fill([min(Xx),max(Xx),max(Xx),min(Xx)],[min(Yy),min(Yy),max(Yy),max(Yy)],</span><span style="color: rgb(160, 32, 240);">'w'</span><span>,</span><span style="color: rgb(160, 32, 240);">'FaceAlpha'</span><span>,0.)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> hold </span><span style="color: rgb(160, 32, 240);">on</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> fill(xn(Shown_compo,:)',yn(Shown_compo,:)',Mc(Shown_compo),</span><span style="color: rgb(160, 32, 240);">'FaceAlpha'</span><span>,0.5)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(0, 0, 255);">if </span><span>strcmp(BC,</span><span style="color: rgb(160, 32, 240);">'L-shape'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> fill([fix((min(Xx)+max(Xx))/2),max(Xx),max(Xx),fix((min(Xx)+max(Xx))/2)],[fix((min(Yy)+max(Yy))/2),</span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> fix((min(Yy)+max(Yy))/2),max(Yy),max(Yy)],</span><span style="color: rgb(160, 32, 240);">'w'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(0, 0, 255);">end</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> caxis([0,1])</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> colormap </span><span style="color: rgb(160, 32, 240);">'jet'</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> axis </span><span style="color: rgb(160, 32, 240);">equal</span><span>; axis </span><span style="color: rgb(160, 32, 240);">off</span><span>;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> hold </span><span style="color: rgb(160, 32, 240);">on</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> scatter(Xx(fixednodes(fixed_dir==1)),Yy(fixednodes(fixed_dir==1)),</span><span style="color: rgb(160, 32, 240);">'>b'</span><span>,</span><span style="color: rgb(160, 32, 240);">'filled'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> scatter(Xx(fixednodes(fixed_dir==2)),Yy(fixednodes(fixed_dir==2)),</span><span style="color: rgb(160, 32, 240);">'^b'</span><span>,</span><span style="color: rgb(160, 32, 240);">'filled'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> scal=10;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> quiver(Xx(excitation_node),Yy(excitation_node)+scal*(excitation_direction==2),excitation_direction==1,</span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> -(excitation_direction==2),scal,</span><span style="color: rgb(160, 32, 240);">'r'</span><span>,</span><span style="color: rgb(160, 32, 240);">'Linewidth'</span><span>,2)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> colorbar</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> axis([min(Xx),max(Xx),min(Yy),max(Yy)])</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> print([Path,</span><span style="color: rgb(160, 32, 240);">'component_'</span><span>,num2str(outit-1,</span><span style="color: rgb(160, 32, 240);">'%03d'</span><span>)],</span><span style="color: rgb(160, 32, 240);">'-dpng'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> hold </span><span style="color: rgb(160, 32, 240);">off</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(0, 0, 255);">end</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);"> %% MMA code optimization</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> [X,ymma,zmma,lam,xsi,eta,mu,zet,S,low,upp] = </span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> mmasub(m,n,outeriter,xval,xmin,xmax,xold1,xold2, </span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> f0val,df0dx,fval,dfdx,low,upp,a0,a,C,d);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> xold2 = xold1;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> xold1 = xval;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> xval = X;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> Xg=lower_bound+(upper_bound-lower_bound).*X;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> change=norm(xval-xold1);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);"> %% The residual vector of the KKT conditions is calculated:</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> [residu,kktnorm,residumax] = </span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> kktcheck(m,n,X,ymma,zmma,lam,xsi,eta,mu,zet,S, </span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> xmin,xmax,df0dx,fval,dfdx,a0,a,C,d);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(34, 139, 34);">% update the stopping criterion</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(0, 0, 255);">switch </span><span>stopping_criteria</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(0, 0, 255);">case </span><span style="color: rgb(160, 32, 240);">'kktnorm'</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> stop_cond=outit < maxoutit && kktnorm>kkttol;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(0, 0, 255);">case </span><span style="color: rgb(160, 32, 240);">'change'</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> stop_cond=outit < maxoutit &&change>changetol;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(0, 0, 255);">end</span></span></div></div><div class="inlineWrapper outputs"><div class = 'S7'><span style="white-space: pre;"><span style="color: rgb(0, 0, 255);">end</span></span></div><div class = 'S8'><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="298A4520" data-testid="output_1" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 1 Obj.:4.236e+04 Vol.: 0.074 kktnorm.: 10.001 ch.: 1.000</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="30859D63" data-testid="output_2" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 2 Obj.:1.028e+04 Vol.: 0.113 kktnorm.: 84.904 ch.: 0.088</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="699241E3" data-testid="output_3" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 3 Obj.:5.624e+03 Vol.: 0.149 kktnorm.: 74.311 ch.: 0.085</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="8B4C5593" data-testid="output_4" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 4 Obj.:2.991e+03 Vol.: 0.183 kktnorm.: 64.682 ch.: 0.079</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="A2EAD1C3" data-testid="output_5" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 5 Obj.:1.979e+03 Vol.: 0.220 kktnorm.: 55.702 ch.: 0.069</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="7CC3176E" data-testid="output_6" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 6 Obj.:1.513e+03 Vol.: 0.254 kktnorm.: 45.613 ch.: 0.066</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="C18E1643" data-testid="output_7" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 7 Obj.:1.187e+03 Vol.: 0.282 kktnorm.: 36.972 ch.: 0.063</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="627250AF" data-testid="output_8" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 8 Obj.:9.474e+02 Vol.: 0.315 kktnorm.: 30.084 ch.: 0.062</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="022AC95B" data-testid="output_9" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 9 Obj.:7.933e+02 Vol.: 0.346 kktnorm.: 21.728 ch.: 0.056</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="B180AF86" data-testid="output_10" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 10 Obj.:6.889e+02 Vol.: 0.370 kktnorm.: 14.059 ch.: 0.049</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="3622145A" data-testid="output_11" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 11 Obj.:6.176e+02 Vol.: 0.387 kktnorm.: 8.511 ch.: 0.038</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="676E1FC2" data-testid="output_12" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 12 Obj.:5.764e+02 Vol.: 0.395 kktnorm.: 4.412 ch.: 0.030</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="9833ED5F" data-testid="output_13" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 13 Obj.:5.517e+02 Vol.: 0.398 kktnorm.: 2.943 ch.: 0.026</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="BFEBABA9" data-testid="output_14" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 14 Obj.:5.367e+02 Vol.: 0.399 kktnorm.: 2.346 ch.: 0.024</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="EB550356" data-testid="output_15" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 15 Obj.:5.244e+02 Vol.: 0.398 kktnorm.: 2.399 ch.: 0.023</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="101737BA" data-testid="output_16" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 16 Obj.:5.121e+02 Vol.: 0.400 kktnorm.: 2.078 ch.: 0.024</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="DF66961C" data-testid="output_17" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 17 Obj.:5.033e+02 Vol.: 0.399 kktnorm.: 2.672 ch.: 0.023</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="84CC4530" data-testid="output_18" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 18 Obj.:4.927e+02 Vol.: 0.398 kktnorm.: 2.305 ch.: 0.022</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="5A2AFF13" data-testid="output_19" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 19 Obj.:4.820e+02 Vol.: 0.399 kktnorm.: 2.097 ch.: 0.022</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="C28F65A0" data-testid="output_20" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 20 Obj.:4.719e+02 Vol.: 0.399 kktnorm.: 2.049 ch.: 0.021</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="E985A281" data-testid="output_21" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 21 Obj.:4.621e+02 Vol.: 0.399 kktnorm.: 1.957 ch.: 0.021</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="7AF32DB2" data-testid="output_22" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 22 Obj.:4.529e+02 Vol.: 0.399 kktnorm.: 1.972 ch.: 0.021</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="0495D775" data-testid="output_23" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 23 Obj.:4.440e+02 Vol.: 0.399 kktnorm.: 1.862 ch.: 0.020</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="D06B9FE9" data-testid="output_24" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 24 Obj.:4.354e+02 Vol.: 0.399 kktnorm.: 1.834 ch.: 0.020</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="149EBB2C" data-testid="output_25" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 25 Obj.:4.271e+02 Vol.: 0.399 kktnorm.: 1.883 ch.: 0.020</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="2A03F33C" data-testid="output_26" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 26 Obj.:4.189e+02 Vol.: 0.399 kktnorm.: 1.863 ch.: 0.021</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="1A68EC02" data-testid="output_27" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 27 Obj.:4.106e+02 Vol.: 0.399 kktnorm.: 1.805 ch.: 0.019</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="C4F576EC" data-testid="output_28" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 28 Obj.:4.029e+02 Vol.: 0.399 kktnorm.: 1.998 ch.: 0.019</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="D2E6DA97" data-testid="output_29" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 29 Obj.:3.951e+02 Vol.: 0.399 kktnorm.: 1.814 ch.: 0.020</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="B105CBBA" data-testid="output_30" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 30 Obj.:3.874e+02 Vol.: 0.399 kktnorm.: 1.765 ch.: 0.020</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="3CD45C11" data-testid="output_31" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 31 Obj.:3.803e+02 Vol.: 0.399 kktnorm.: 1.766 ch.: 0.020</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="27F4E38C" data-testid="output_32" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 32 Obj.:3.733e+02 Vol.: 0.399 kktnorm.: 1.818 ch.: 0.019</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="84B8355F" data-testid="output_33" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 33 Obj.:3.666e+02 Vol.: 0.399 kktnorm.: 1.828 ch.: 0.020</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="DF268BD2" data-testid="output_34" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 34 Obj.:3.603e+02 Vol.: 0.399 kktnorm.: 1.885 ch.: 0.019</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="899321C0" data-testid="output_35" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 35 Obj.:3.541e+02 Vol.: 0.399 kktnorm.: 1.847 ch.: 0.019</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="95882FF1" data-testid="output_36" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 36 Obj.:3.479e+02 Vol.: 0.399 kktnorm.: 1.873 ch.: 0.019</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="20E81D00" data-testid="output_37" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 37 Obj.:3.416e+02 Vol.: 0.399 kktnorm.: 1.904 ch.: 0.019</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="07106D18" data-testid="output_38" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 38 Obj.:3.355e+02 Vol.: 0.399 kktnorm.: 1.831 ch.: 0.019</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="5451B66A" data-testid="output_39" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 39 Obj.:3.293e+02 Vol.: 0.399 kktnorm.: 1.815 ch.: 0.019</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="D70A93D5" data-testid="output_40" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 40 Obj.:3.238e+02 Vol.: 0.399 kktnorm.: 1.761 ch.: 0.019</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="670DAB61" data-testid="output_41" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 41 Obj.:3.179e+02 Vol.: 0.399 kktnorm.: 1.786 ch.: 0.019</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="80EA523D" data-testid="output_42" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 42 Obj.:3.118e+02 Vol.: 0.399 kktnorm.: 1.797 ch.: 0.019</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="2DD1E09F" data-testid="output_43" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 43 Obj.:3.064e+02 Vol.: 0.399 kktnorm.: 1.763 ch.: 0.019</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="B571066C" data-testid="output_44" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 44 Obj.:3.010e+02 Vol.: 0.399 kktnorm.: 1.770 ch.: 0.019</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="EC85C40E" data-testid="output_45" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 45 Obj.:2.957e+02 Vol.: 0.399 kktnorm.: 1.769 ch.: 0.019</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="E09EFF77" data-testid="output_46" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 46 Obj.:2.902e+02 Vol.: 0.399 kktnorm.: 1.792 ch.: 0.020</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="D7CD0D56" data-testid="output_47" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 47 Obj.:2.848e+02 Vol.: 0.399 kktnorm.: 1.795 ch.: 0.019</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="7A194D9A" data-testid="output_48" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 48 Obj.:2.796e+02 Vol.: 0.399 kktnorm.: 1.796 ch.: 0.019</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="CC0BEBA4" data-testid="output_49" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 49 Obj.:2.745e+02 Vol.: 0.399 kktnorm.: 1.791 ch.: 0.019</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="D5F69531" data-testid="output_50" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 50 Obj.:2.694e+02 Vol.: 0.399 kktnorm.: 1.783 ch.: 0.017</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="C46F9A84" data-testid="output_51" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 51 Obj.:2.642e+02 Vol.: 0.399 kktnorm.: 1.793 ch.: 0.019</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="7886E851" data-testid="output_52" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 52 Obj.:2.597e+02 Vol.: 0.399 kktnorm.: 1.704 ch.: 0.015</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="7D4BBA57" data-testid="output_53" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 53 Obj.:2.557e+02 Vol.: 0.399 kktnorm.: 1.724 ch.: 0.012</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="A5700319" data-testid="output_54" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 54 Obj.:2.516e+02 Vol.: 0.399 kktnorm.: 1.715 ch.: 0.012</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="CD9B827D" data-testid="output_55" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 55 Obj.:2.476e+02 Vol.: 0.399 kktnorm.: 1.725 ch.: 0.012</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="A6CF09C8" data-testid="output_56" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 56 Obj.:2.437e+02 Vol.: 0.399 kktnorm.: 1.757 ch.: 0.013</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="E8ACD9D2" data-testid="output_57" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 57 Obj.:2.399e+02 Vol.: 0.399 kktnorm.: 1.747 ch.: 0.012</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="366AAE14" data-testid="output_58" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 58 Obj.:2.363e+02 Vol.: 0.399 kktnorm.: 1.746 ch.: 0.011</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="52FA30B0" data-testid="output_59" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 59 Obj.:2.327e+02 Vol.: 0.399 kktnorm.: 1.772 ch.: 0.011</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="319C715E" data-testid="output_60" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 60 Obj.:2.291e+02 Vol.: 0.399 kktnorm.: 1.780 ch.: 0.011</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="80D54EDD" data-testid="output_61" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 61 Obj.:2.256e+02 Vol.: 0.399 kktnorm.: 1.754 ch.: 0.012</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="B2BCD993" data-testid="output_62" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 62 Obj.:2.221e+02 Vol.: 0.399 kktnorm.: 1.755 ch.: 0.012</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="3103AB4D" data-testid="output_63" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 63 Obj.:2.190e+02 Vol.: 0.400 kktnorm.: 1.743 ch.: 0.012</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="05F547E5" data-testid="output_64" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 64 Obj.:2.155e+02 Vol.: 0.400 kktnorm.: 2.534 ch.: 0.012</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="CEBCA8E9" data-testid="output_65" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 65 Obj.:2.125e+02 Vol.: 0.399 kktnorm.: 2.425 ch.: 0.011</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="8EACCCCB" data-testid="output_66" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 66 Obj.:2.094e+02 Vol.: 0.399 kktnorm.: 1.780 ch.: 0.011</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="508BA1AA" data-testid="output_67" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 67 Obj.:2.063e+02 Vol.: 0.399 kktnorm.: 1.776 ch.: 0.011</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="3C6809CB" data-testid="output_68" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 68 Obj.:2.032e+02 Vol.: 0.399 kktnorm.: 1.787 ch.: 0.012</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="1CD25223" data-testid="output_69" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 69 Obj.:2.002e+02 Vol.: 0.399 kktnorm.: 1.784 ch.: 0.011</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="6F112DED" data-testid="output_70" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 70 Obj.:1.974e+02 Vol.: 0.399 kktnorm.: 1.769 ch.: 0.011</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="D17AA1A0" data-testid="output_71" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 71 Obj.:1.945e+02 Vol.: 0.399 kktnorm.: 1.751 ch.: 0.011</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="1B827853" data-testid="output_72" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 72 Obj.:1.917e+02 Vol.: 0.399 kktnorm.: 1.766 ch.: 0.011</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="3E9E23D7" data-testid="output_73" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 73 Obj.:1.889e+02 Vol.: 0.399 kktnorm.: 1.774 ch.: 0.011</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="E21E54A3" data-testid="output_74" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 74 Obj.:1.862e+02 Vol.: 0.399 kktnorm.: 1.767 ch.: 0.011</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="7FF5A0A9" data-testid="output_75" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 75 Obj.:1.835e+02 Vol.: 0.399 kktnorm.: 1.757 ch.: 0.012</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="85BED05D" data-testid="output_76" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 76 Obj.:1.809e+02 Vol.: 0.399 kktnorm.: 1.758 ch.: 0.011</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="675050B9" data-testid="output_77" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 77 Obj.:1.783e+02 Vol.: 0.399 kktnorm.: 1.756 ch.: 0.011</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="DFB64823" data-testid="output_78" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 78 Obj.:1.757e+02 Vol.: 0.399 kktnorm.: 1.760 ch.: 0.011</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="61D5A23E" data-testid="output_79" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 79 Obj.:1.733e+02 Vol.: 0.399 kktnorm.: 1.748 ch.: 0.011</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="0AEBF508" data-testid="output_80" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 80 Obj.:1.708e+02 Vol.: 0.399 kktnorm.: 1.851 ch.: 0.012</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="75D99D22" data-testid="output_81" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 81 Obj.:1.683e+02 Vol.: 0.400 kktnorm.: 1.840 ch.: 0.017</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="B5C7142A" data-testid="output_82" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 82 Obj.:1.662e+02 Vol.: 0.399 kktnorm.: 2.123 ch.: 0.012</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="E70E1C25" data-testid="output_83" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 83 Obj.:1.639e+02 Vol.: 0.399 kktnorm.: 1.838 ch.: 0.011</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="B0B1D11E" data-testid="output_84" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 84 Obj.:1.617e+02 Vol.: 0.399 kktnorm.: 1.722 ch.: 0.010</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="C9EAE281" data-testid="output_85" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 85 Obj.:1.595e+02 Vol.: 0.399 kktnorm.: 1.726 ch.: 0.010</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="90864AFC" data-testid="output_86" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 86 Obj.:1.574e+02 Vol.: 0.399 kktnorm.: 1.729 ch.: 0.010</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="40DBA2CF" data-testid="output_87" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 87 Obj.:1.553e+02 Vol.: 0.399 kktnorm.: 1.736 ch.: 0.011</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="08FB575B" data-testid="output_88" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 88 Obj.:1.532e+02 Vol.: 0.399 kktnorm.: 1.769 ch.: 0.011</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="30B5F5AC" data-testid="output_89" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 89 Obj.:1.511e+02 Vol.: 0.399 kktnorm.: 1.817 ch.: 0.011</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="4B74AC16" data-testid="output_90" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 90 Obj.:1.491e+02 Vol.: 0.399 kktnorm.: 1.861 ch.: 0.010</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="8DF368B9" data-testid="output_91" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 91 Obj.:1.472e+02 Vol.: 0.399 kktnorm.: 1.869 ch.: 0.010</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="9C3CEADE" data-testid="output_92" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 92 Obj.:1.452e+02 Vol.: 0.399 kktnorm.: 1.822 ch.: 0.010</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="F18995DC" data-testid="output_93" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 93 Obj.:1.434e+02 Vol.: 0.399 kktnorm.: 1.820 ch.: 0.011</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="4F5FF72F" data-testid="output_94" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 94 Obj.:1.415e+02 Vol.: 0.399 kktnorm.: 1.803 ch.: 0.012</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="D90AD294" data-testid="output_95" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 95 Obj.:1.396e+02 Vol.: 0.399 kktnorm.: 1.807 ch.: 0.012</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="97AE370B" data-testid="output_96" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 96 Obj.:1.379e+02 Vol.: 0.399 kktnorm.: 1.794 ch.: 0.012</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="55BF2A6A" data-testid="output_97" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 97 Obj.:1.361e+02 Vol.: 0.399 kktnorm.: 1.765 ch.: 0.013</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="EA23FCB8" data-testid="output_98" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 98 Obj.:1.343e+02 Vol.: 0.399 kktnorm.: 1.751 ch.: 0.013</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="9D52054E" data-testid="output_99" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 99 Obj.:1.326e+02 Vol.: 0.399 kktnorm.: 1.748 ch.: 0.013</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="2FC33E4A" data-testid="output_100" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 100 Obj.:1.309e+02 Vol.: 0.399 kktnorm.: 1.735 ch.: 0.014</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="84A7466B" data-testid="output_101" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 101 Obj.:1.292e+02 Vol.: 0.399 kktnorm.: 1.731 ch.: 0.015</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="482C9D70" data-testid="output_102" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 102 Obj.:1.275e+02 Vol.: 0.399 kktnorm.: 1.730 ch.: 0.014</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="3F98F48E" data-testid="output_103" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 103 Obj.:1.259e+02 Vol.: 0.399 kktnorm.: 1.759 ch.: 0.020</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="8879273F" data-testid="output_104" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 104 Obj.:1.244e+02 Vol.: 0.400 kktnorm.: 2.041 ch.: 0.021</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="7DA9B5D0" data-testid="output_105" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 105 Obj.:1.228e+02 Vol.: 0.402 kktnorm.: 3.422 ch.: 0.020</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="697EC540" data-testid="output_106" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 106 Obj.:1.220e+02 Vol.: 0.398 kktnorm.: 3.934 ch.: 0.018</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="EC65ED63" data-testid="output_107" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 107 Obj.:1.200e+02 Vol.: 0.399 kktnorm.: 3.828 ch.: 0.016</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="838A1E4D" data-testid="output_108" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 108 Obj.:1.185e+02 Vol.: 0.399 kktnorm.: 2.499 ch.: 0.015</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="78BE3DB7" data-testid="output_109" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 109 Obj.:1.171e+02 Vol.: 0.399 kktnorm.: 2.233 ch.: 0.015</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="9E7E71C2" data-testid="output_110" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 110 Obj.:1.158e+02 Vol.: 0.399 kktnorm.: 2.033 ch.: 0.015</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="40D0DBA1" data-testid="output_111" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 111 Obj.:1.145e+02 Vol.: 0.399 kktnorm.: 1.893 ch.: 0.016</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="E1DEC358" data-testid="output_112" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 112 Obj.:1.132e+02 Vol.: 0.399 kktnorm.: 1.761 ch.: 0.016</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="819CB218" data-testid="output_113" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 113 Obj.:1.119e+02 Vol.: 0.399 kktnorm.: 1.644 ch.: 0.017</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="90D98AE4" data-testid="output_114" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 114 Obj.:1.106e+02 Vol.: 0.399 kktnorm.: 1.616 ch.: 0.015</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="A36CFD99" data-testid="output_115" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 115 Obj.:1.094e+02 Vol.: 0.399 kktnorm.: 1.613 ch.: 0.016</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="0470F3A8" data-testid="output_116" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 116 Obj.:1.082e+02 Vol.: 0.399 kktnorm.: 1.613 ch.: 0.016</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="CEAD3544" data-testid="output_117" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 117 Obj.:1.070e+02 Vol.: 0.399 kktnorm.: 1.611 ch.: 0.016</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="180EC9BB" data-testid="output_118" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 118 Obj.:1.057e+02 Vol.: 0.399 kktnorm.: 1.604 ch.: 0.016</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="7E8CE430" data-testid="output_119" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 119 Obj.:1.045e+02 Vol.: 0.399 kktnorm.: 1.597 ch.: 0.016</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="5BABE235" data-testid="output_120" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 120 Obj.:1.033e+02 Vol.: 0.399 kktnorm.: 1.607 ch.: 0.014</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="8C6ACC98" data-testid="output_121" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 121 Obj.:1.021e+02 Vol.: 0.399 kktnorm.: 1.621 ch.: 0.014</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="FB51E47B" data-testid="output_122" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 122 Obj.:1.009e+02 Vol.: 0.399 kktnorm.: 1.642 ch.: 0.014</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="1162F24E" data-testid="output_123" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 123 Obj.:9.973e+01 Vol.: 0.399 kktnorm.: 1.603 ch.: 0.015</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="C0E2F2CD" data-testid="output_124" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 124 Obj.:9.861e+01 Vol.: 0.399 kktnorm.: 1.700 ch.: 0.015</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="9EA2A414" data-testid="output_125" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 125 Obj.:9.752e+01 Vol.: 0.399 kktnorm.: 1.984 ch.: 0.014</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="45C37260" data-testid="output_126" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 126 Obj.:9.648e+01 Vol.: 0.399 kktnorm.: 1.686 ch.: 0.012</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="0E0B6307" data-testid="output_127" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 127 Obj.:9.545e+01 Vol.: 0.399 kktnorm.: 1.674 ch.: 0.012</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="8DDEFD1A" data-testid="output_128" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 128 Obj.:9.442e+01 Vol.: 0.399 kktnorm.: 1.632 ch.: 0.012</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="D235F1AE" data-testid="output_129" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 129 Obj.:9.340e+01 Vol.: 0.399 kktnorm.: 1.606 ch.: 0.013</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="A86C163C" data-testid="output_130" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 130 Obj.:9.244e+01 Vol.: 0.399 kktnorm.: 1.541 ch.: 0.014</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="A7DFC345" data-testid="output_131" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 131 Obj.:9.167e+01 Vol.: 0.400 kktnorm.: 1.247 ch.: 0.013</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="4B5370E4" data-testid="output_132" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 132 Obj.:9.118e+01 Vol.: 0.400 kktnorm.: 0.944 ch.: 0.012</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="9B0F066F" data-testid="output_133" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 133 Obj.:9.074e+01 Vol.: 0.400 kktnorm.: 0.907 ch.: 0.012</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="E7E67659" data-testid="output_134" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 134 Obj.:9.031e+01 Vol.: 0.400 kktnorm.: 0.913 ch.: 0.013</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="98C63A30" data-testid="output_135" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 135 Obj.:8.989e+01 Vol.: 0.400 kktnorm.: 0.898 ch.: 0.013</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="6B024538" data-testid="output_136" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 136 Obj.:8.947e+01 Vol.: 0.400 kktnorm.: 0.890 ch.: 0.013</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="31BAD18F" data-testid="output_137" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 137 Obj.:8.906e+01 Vol.: 0.400 kktnorm.: 0.890 ch.: 0.013</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="9569B684" data-testid="output_138" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 138 Obj.:8.866e+01 Vol.: 0.400 kktnorm.: 0.863 ch.: 0.013</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="4A5FAACB" data-testid="output_139" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 139 Obj.:8.828e+01 Vol.: 0.400 kktnorm.: 0.868 ch.: 0.013</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="7597DFD5" data-testid="output_140" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 140 Obj.:8.789e+01 Vol.: 0.400 kktnorm.: 1.137 ch.: 0.013</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="16CE49CF" data-testid="output_141" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 141 Obj.:8.750e+01 Vol.: 0.400 kktnorm.: 1.117 ch.: 0.013</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="57B4B367" data-testid="output_142" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 142 Obj.:8.713e+01 Vol.: 0.400 kktnorm.: 0.863 ch.: 0.014</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="F91ADF03" data-testid="output_143" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 143 Obj.:8.676e+01 Vol.: 0.400 kktnorm.: 0.881 ch.: 0.014</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="2C04174A" data-testid="output_144" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 144 Obj.:8.640e+01 Vol.: 0.400 kktnorm.: 0.862 ch.: 0.014</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="8293AEB9" data-testid="output_145" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 145 Obj.:8.605e+01 Vol.: 0.400 kktnorm.: 0.860 ch.: 0.014</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="C05E67E6" data-testid="output_146" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 146 Obj.:8.570e+01 Vol.: 0.400 kktnorm.: 0.865 ch.: 0.014</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="0EED4AB7" data-testid="output_147" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 147 Obj.:8.535e+01 Vol.: 0.400 kktnorm.: 0.865 ch.: 0.014</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="7F70799A" data-testid="output_148" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 148 Obj.:8.501e+01 Vol.: 0.400 kktnorm.: 0.863 ch.: 0.014</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="AB3C5DC7" data-testid="output_149" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 149 Obj.:8.467e+01 Vol.: 0.400 kktnorm.: 0.861 ch.: 0.014</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="D6F9C787" data-testid="output_150" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 150 Obj.:8.434e+01 Vol.: 0.400 kktnorm.: 0.855 ch.: 0.014</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="9B457534" data-testid="output_151" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 151 Obj.:8.400e+01 Vol.: 0.400 kktnorm.: 0.845 ch.: 0.014</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="EEFA6CDC" data-testid="output_152" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 152 Obj.:8.367e+01 Vol.: 0.400 kktnorm.: 0.842 ch.: 0.015</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="CFF98EFC" data-testid="output_153" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 153 Obj.:8.335e+01 Vol.: 0.400 kktnorm.: 0.831 ch.: 0.015</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="328FBE9B" data-testid="output_154" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 154 Obj.:8.302e+01 Vol.: 0.400 kktnorm.: 0.811 ch.: 0.016</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="5E18A55D" data-testid="output_155" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 155 Obj.:8.271e+01 Vol.: 0.400 kktnorm.: 0.802 ch.: 0.016</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="6E404B0D" data-testid="output_156" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 156 Obj.:8.240e+01 Vol.: 0.400 kktnorm.: 0.894 ch.: 0.015</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="0D1D5C81" data-testid="output_157" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 157 Obj.:8.208e+01 Vol.: 0.400 kktnorm.: 0.834 ch.: 0.015</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="3C4AB988" data-testid="output_158" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 158 Obj.:8.178e+01 Vol.: 0.400 kktnorm.: 0.792 ch.: 0.015</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="6078C046" data-testid="output_159" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 159 Obj.:8.148e+01 Vol.: 0.400 kktnorm.: 0.801 ch.: 0.015</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="AFB40321" data-testid="output_160" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 160 Obj.:8.118e+01 Vol.: 0.400 kktnorm.: 0.773 ch.: 0.015</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="A4D8059E" data-testid="output_161" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 161 Obj.:8.090e+01 Vol.: 0.400 kktnorm.: 0.785 ch.: 0.015</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="CB745E94" data-testid="output_162" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 162 Obj.:8.061e+01 Vol.: 0.400 kktnorm.: 0.742 ch.: 0.015</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="B4175CF2" data-testid="output_163" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 163 Obj.:8.033e+01 Vol.: 0.400 kktnorm.: 0.808 ch.: 0.015</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="A43432FD" data-testid="output_164" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 164 Obj.:8.005e+01 Vol.: 0.400 kktnorm.: 0.723 ch.: 0.015</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="FE45F525" data-testid="output_165" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 165 Obj.:7.978e+01 Vol.: 0.400 kktnorm.: 0.835 ch.: 0.014</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="093DAE96" data-testid="output_166" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 166 Obj.:7.948e+01 Vol.: 0.400 kktnorm.: 0.725 ch.: 0.015</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="81D75B08" data-testid="output_167" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 167 Obj.:7.920e+01 Vol.: 0.400 kktnorm.: 1.198 ch.: 0.014</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="3671EE45" data-testid="output_168" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 168 Obj.:7.895e+01 Vol.: 0.400 kktnorm.: 0.742 ch.: 0.014</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="13557248" data-testid="output_169" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 169 Obj.:7.871e+01 Vol.: 0.400 kktnorm.: 0.741 ch.: 0.014</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="7980D73E" data-testid="output_170" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 170 Obj.:7.853e+01 Vol.: 0.400 kktnorm.: 0.751 ch.: 0.014</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="31BFEB86" data-testid="output_171" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 171 Obj.:7.838e+01 Vol.: 0.400 kktnorm.: 0.696 ch.: 0.014</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="0F6074BB" data-testid="output_172" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 172 Obj.:7.823e+01 Vol.: 0.400 kktnorm.: 0.714 ch.: 0.013</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="E7D526C8" data-testid="output_173" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 173 Obj.:7.808e+01 Vol.: 0.400 kktnorm.: 0.694 ch.: 0.013</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="EA185AB3" data-testid="output_174" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 174 Obj.:7.792e+01 Vol.: 0.400 kktnorm.: 0.651 ch.: 0.013</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="6C03D631" data-testid="output_175" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 175 Obj.:7.777e+01 Vol.: 0.400 kktnorm.: 0.599 ch.: 0.010</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="C9875947" data-testid="output_176" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 176 Obj.:7.761e+01 Vol.: 0.400 kktnorm.: 0.573 ch.: 0.007</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="F6DFFDFC" data-testid="output_177" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 177 Obj.:7.746e+01 Vol.: 0.400 kktnorm.: 0.545 ch.: 0.007</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="77E17E62" data-testid="output_178" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 178 Obj.:7.730e+01 Vol.: 0.400 kktnorm.: 0.565 ch.: 0.007</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="23E2E061" data-testid="output_179" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 179 Obj.:7.714e+01 Vol.: 0.400 kktnorm.: 0.544 ch.: 0.008</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="76D35111" data-testid="output_180" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 180 Obj.:7.699e+01 Vol.: 0.400 kktnorm.: 0.545 ch.: 0.008</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="11B269EF" data-testid="output_181" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 181 Obj.:7.686e+01 Vol.: 0.400 kktnorm.: 0.536 ch.: 0.007</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="8CFC2135" data-testid="output_182" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 182 Obj.:7.680e+01 Vol.: 0.400 kktnorm.: 0.457 ch.: 0.005</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="F8800641" data-testid="output_183" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 183 Obj.:7.675e+01 Vol.: 0.400 kktnorm.: 0.448 ch.: 0.005</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="37B76A03" data-testid="output_184" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 184 Obj.:7.670e+01 Vol.: 0.400 kktnorm.: 0.294 ch.: 0.006</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="C8F4F2C0" data-testid="output_185" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 185 Obj.:7.665e+01 Vol.: 0.400 kktnorm.: 0.753 ch.: 0.006</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="3E62C5E0" data-testid="output_186" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 186 Obj.:7.661e+01 Vol.: 0.400 kktnorm.: 0.350 ch.: 0.006</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="F530AAB7" data-testid="output_187" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 187 Obj.:7.657e+01 Vol.: 0.400 kktnorm.: 0.457 ch.: 0.005</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="5473C69F" data-testid="output_188" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 188 Obj.:7.653e+01 Vol.: 0.400 kktnorm.: 0.304 ch.: 0.005</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="C937AE96" data-testid="output_189" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 189 Obj.:7.649e+01 Vol.: 0.400 kktnorm.: 0.301 ch.: 0.005</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="3C03D767" data-testid="output_190" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 190 Obj.:7.645e+01 Vol.: 0.400 kktnorm.: 0.298 ch.: 0.005</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="08838AE2" data-testid="output_191" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 191 Obj.:7.641e+01 Vol.: 0.400 kktnorm.: 0.301 ch.: 0.005</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="42C471C9" data-testid="output_192" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 192 Obj.:7.637e+01 Vol.: 0.400 kktnorm.: 0.303 ch.: 0.005</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="4C900102" data-testid="output_193" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 193 Obj.:7.633e+01 Vol.: 0.400 kktnorm.: 0.294 ch.: 0.005</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="89AE7DE6" data-testid="output_194" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 194 Obj.:7.630e+01 Vol.: 0.400 kktnorm.: 0.290 ch.: 0.005</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="9D7059C0" data-testid="output_195" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 195 Obj.:7.626e+01 Vol.: 0.400 kktnorm.: 0.292 ch.: 0.005</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="504636DB" data-testid="output_196" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 196 Obj.:7.622e+01 Vol.: 0.400 kktnorm.: 0.279 ch.: 0.005</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="C147B9FE" data-testid="output_197" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 197 Obj.:7.618e+01 Vol.: 0.400 kktnorm.: 0.284 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="F1409106" data-testid="output_198" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 198 Obj.:7.614e+01 Vol.: 0.400 kktnorm.: 0.249 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="D1713EEA" data-testid="output_199" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 199 Obj.:7.610e+01 Vol.: 0.400 kktnorm.: 0.307 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="32E8CEAA" data-testid="output_200" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 200 Obj.:7.607e+01 Vol.: 0.400 kktnorm.: 0.426 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="A170BFF7" data-testid="output_201" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 201 Obj.:7.603e+01 Vol.: 0.400 kktnorm.: 0.408 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="AC08C679" data-testid="output_202" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 202 Obj.:7.600e+01 Vol.: 0.400 kktnorm.: 0.314 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="6BBD1F7F" data-testid="output_203" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 203 Obj.:7.597e+01 Vol.: 0.400 kktnorm.: 0.349 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="C4235E00" data-testid="output_204" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 204 Obj.:7.594e+01 Vol.: 0.400 kktnorm.: 0.289 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="A34AED1E" data-testid="output_205" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 205 Obj.:7.590e+01 Vol.: 0.400 kktnorm.: 0.292 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="E0EABCAE" data-testid="output_206" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 206 Obj.:7.587e+01 Vol.: 0.400 kktnorm.: 0.279 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="24C58311" data-testid="output_207" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 207 Obj.:7.584e+01 Vol.: 0.400 kktnorm.: 0.266 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="C504E7FB" data-testid="output_208" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 208 Obj.:7.581e+01 Vol.: 0.400 kktnorm.: 0.248 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="CA777EDC" data-testid="output_209" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 209 Obj.:7.578e+01 Vol.: 0.400 kktnorm.: 0.238 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="5F55F1D8" data-testid="output_210" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 210 Obj.:7.575e+01 Vol.: 0.400 kktnorm.: 0.228 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="DD17D674" data-testid="output_211" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 211 Obj.:7.572e+01 Vol.: 0.400 kktnorm.: 0.221 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="D2C00573" data-testid="output_212" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 212 Obj.:7.569e+01 Vol.: 0.400 kktnorm.: 0.212 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="4AD38A06" data-testid="output_213" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 213 Obj.:7.566e+01 Vol.: 0.400 kktnorm.: 0.206 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="5807CCEF" data-testid="output_214" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 214 Obj.:7.563e+01 Vol.: 0.400 kktnorm.: 0.201 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="2F159D9B" data-testid="output_215" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 215 Obj.:7.560e+01 Vol.: 0.400 kktnorm.: 0.216 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="3A7180C0" data-testid="output_216" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 216 Obj.:7.556e+01 Vol.: 0.400 kktnorm.: 0.378 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="C1BC4E4B" data-testid="output_217" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 217 Obj.:7.554e+01 Vol.: 0.400 kktnorm.: 0.695 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="7B1650B3" data-testid="output_218" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 218 Obj.:7.551e+01 Vol.: 0.400 kktnorm.: 0.478 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="A9DE60E9" data-testid="output_219" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 219 Obj.:7.548e+01 Vol.: 0.400 kktnorm.: 0.328 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="FF76671E" data-testid="output_220" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 220 Obj.:7.546e+01 Vol.: 0.400 kktnorm.: 0.318 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="C71F30C4" data-testid="output_221" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 221 Obj.:7.543e+01 Vol.: 0.400 kktnorm.: 0.312 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="28C4DC3D" data-testid="output_222" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 222 Obj.:7.540e+01 Vol.: 0.400 kktnorm.: 0.301 ch.: 0.005</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="373990CC" data-testid="output_223" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 223 Obj.:7.537e+01 Vol.: 0.400 kktnorm.: 0.287 ch.: 0.005</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="291E0151" data-testid="output_224" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 224 Obj.:7.535e+01 Vol.: 0.400 kktnorm.: 0.269 ch.: 0.005</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="4D5FC5F0" data-testid="output_225" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 225 Obj.:7.532e+01 Vol.: 0.400 kktnorm.: 0.252 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="24F92FA4" data-testid="output_226" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 226 Obj.:7.529e+01 Vol.: 0.400 kktnorm.: 0.238 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="408D7DB3" data-testid="output_227" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 227 Obj.:7.526e+01 Vol.: 0.400 kktnorm.: 0.227 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="336A3E70" data-testid="output_228" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 228 Obj.:7.524e+01 Vol.: 0.400 kktnorm.: 0.218 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="EC90582E" data-testid="output_229" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 229 Obj.:7.521e+01 Vol.: 0.400 kktnorm.: 0.212 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="0C27276E" data-testid="output_230" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 230 Obj.:7.518e+01 Vol.: 0.400 kktnorm.: 0.210 ch.: 0.004</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="332B587D" data-testid="output_231" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 231 Obj.:7.516e+01 Vol.: 0.400 kktnorm.: 0.201 ch.: 0.003</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="A22154E3" data-testid="output_232" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 232 Obj.:7.515e+01 Vol.: 0.400 kktnorm.: 0.198 ch.: 0.002</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="47DAAD97" data-testid="output_233" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 233 Obj.:7.515e+01 Vol.: 0.400 kktnorm.: 0.176 ch.: 0.002</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="22711444" data-testid="output_234" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 234 Obj.:7.514e+01 Vol.: 0.400 kktnorm.: 0.170 ch.: 0.002</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="3834B610" data-testid="output_235" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 235 Obj.:7.509e+01 Vol.: 0.400 kktnorm.: 0.151 ch.: 0.005</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="5574DEC0" data-testid="output_236" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 236 Obj.:7.508e+01 Vol.: 0.400 kktnorm.: 0.236 ch.: 0.006</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="DED6BF4A" data-testid="output_237" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 237 Obj.:7.512e+01 Vol.: 0.400 kktnorm.: 0.252 ch.: 0.002</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="250BB022" data-testid="output_238" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 238 Obj.:7.512e+01 Vol.: 0.400 kktnorm.: 0.273 ch.: 0.002</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="53D7F09B" data-testid="output_239" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 239 Obj.:7.511e+01 Vol.: 0.400 kktnorm.: 0.259 ch.: 0.002</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="30AEDE35" data-testid="output_240" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 240 Obj.:7.511e+01 Vol.: 0.400 kktnorm.: 0.244 ch.: 0.002</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="8005D513" data-testid="output_241" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 241 Obj.:7.511e+01 Vol.: 0.400 kktnorm.: 0.232 ch.: 0.001</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="067CA56F" data-testid="output_242" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 242 Obj.:7.510e+01 Vol.: 0.400 kktnorm.: 0.212 ch.: 0.001</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="192DA5A5" data-testid="output_243" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 243 Obj.:7.510e+01 Vol.: 0.400 kktnorm.: 0.200 ch.: 0.001</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="A6984B76" data-testid="output_244" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 244 Obj.:7.510e+01 Vol.: 0.400 kktnorm.: 0.183 ch.: 0.002</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="086912E8" data-testid="output_245" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 245 Obj.:7.509e+01 Vol.: 0.400 kktnorm.: 0.188 ch.: 0.002</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="2C3FAC4E" data-testid="output_246" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 246 Obj.:7.509e+01 Vol.: 0.400 kktnorm.: 0.191 ch.: 0.002</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="CAF49D64" data-testid="output_247" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 247 Obj.:7.508e+01 Vol.: 0.400 kktnorm.: 0.199 ch.: 0.002</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="E55969B5" data-testid="output_248" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 248 Obj.:7.507e+01 Vol.: 0.400 kktnorm.: 0.212 ch.: 0.002</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="55B6D878" data-testid="output_249" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 249 Obj.:7.507e+01 Vol.: 0.400 kktnorm.: 0.214 ch.: 0.002</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="36C6E70E" data-testid="output_250" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 250 Obj.:7.506e+01 Vol.: 0.400 kktnorm.: 0.244 ch.: 0.001</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="22A3EAF5" data-testid="output_251" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 251 Obj.:7.506e+01 Vol.: 0.400 kktnorm.: 0.211 ch.: 0.001</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="220F63C8" data-testid="output_252" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 252 Obj.:7.506e+01 Vol.: 0.400 kktnorm.: 0.183 ch.: 0.001</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="5244E1F3" data-testid="output_253" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 253 Obj.:7.505e+01 Vol.: 0.400 kktnorm.: 0.214 ch.: 0.001</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="2CF027E0" data-testid="output_254" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 254 Obj.:7.505e+01 Vol.: 0.400 kktnorm.: 0.163 ch.: 0.001</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="F85F19B3" data-testid="output_255" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 255 Obj.:7.505e+01 Vol.: 0.400 kktnorm.: 0.152 ch.: 0.001</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="21041FFB" data-testid="output_256" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 256 Obj.:7.505e+01 Vol.: 0.400 kktnorm.: 0.169 ch.: 0.001</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="17091433" data-testid="output_257" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 257 Obj.:7.505e+01 Vol.: 0.400 kktnorm.: 0.161 ch.: 0.001</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="3BA994BD" data-testid="output_258" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 258 Obj.:7.504e+01 Vol.: 0.400 kktnorm.: 0.155 ch.: 0.002</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="4BEA6755" data-testid="output_259" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 259 Obj.:7.504e+01 Vol.: 0.400 kktnorm.: 0.151 ch.: 0.002</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="405142CA" data-testid="output_260" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 260 Obj.:7.504e+01 Vol.: 0.400 kktnorm.: 0.148 ch.: 0.002</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="DC321317" data-testid="output_261" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 261 Obj.:7.504e+01 Vol.: 0.400 kktnorm.: 0.147 ch.: 0.002</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="FE2DFBF9" data-testid="output_262" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 262 Obj.:7.504e+01 Vol.: 0.400 kktnorm.: 0.142 ch.: 0.002</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="49BD5C55" data-testid="output_263" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 263 Obj.:7.504e+01 Vol.: 0.400 kktnorm.: 0.137 ch.: 0.002</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="F18DE911" data-testid="output_264" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 264 Obj.:7.504e+01 Vol.: 0.400 kktnorm.: 0.127 ch.: 0.002</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="7326C4ED" data-testid="output_265" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 265 Obj.:7.503e+01 Vol.: 0.400 kktnorm.: 0.118 ch.: 0.002</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="5A86CCBF" data-testid="output_266" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 266 Obj.:7.503e+01 Vol.: 0.400 kktnorm.: 0.108 ch.: 0.002</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="29784AB7" data-testid="output_267" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 267 Obj.:7.503e+01 Vol.: 0.400 kktnorm.: 0.103 ch.: 0.002</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="752D1A99" data-testid="output_268" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 268 Obj.:7.503e+01 Vol.: 0.400 kktnorm.: 0.095 ch.: 0.002</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="7EC7B8B7" data-testid="output_269" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 269 Obj.:7.503e+01 Vol.: 0.400 kktnorm.: 0.098 ch.: 0.002</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="C982CD1E" data-testid="output_270" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 270 Obj.:7.503e+01 Vol.: 0.400 kktnorm.: 0.103 ch.: 0.001</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="B1081D96" data-testid="output_271" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 271 Obj.:7.503e+01 Vol.: 0.400 kktnorm.: 0.172 ch.: 0.001</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="2817D61B" data-testid="output_272" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 272 Obj.:7.503e+01 Vol.: 0.400 kktnorm.: 0.212 ch.: 0.001</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="CD02B685" data-testid="output_273" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 273 Obj.:7.503e+01 Vol.: 0.400 kktnorm.: 0.129 ch.: 0.001</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="CABB3F46" data-testid="output_274" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 274 Obj.:7.502e+01 Vol.: 0.400 kktnorm.: 0.184 ch.: 0.001</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsTextElement" uid="C9E43C06" data-testid="output_275" data-width="1726" data-height="18" data-hashorizontaloverflow="false" style="width: 1756px; max-height: 261px;"><div class="textElement"> It.: 275 Obj.:7.502e+01 Vol.: 0.400 kktnorm.: 0.099 ch.: 0.001</div></div><div class="inlineElement eoOutputWrapper embeddedOutputsFigure" uid="DD1EB947" data-testid="output_276" style="width: 1756px;"><div class="figureElement"><img class="figureImage figureContainingNode" 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"></div></div></div></div><div class="inlineWrapper"><div class = 'S11'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">% Make the plot of the solution</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">% convergence plot</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>figure(3)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>subplot(2,1,1)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>plot(1:outit,cvec(1:outit),</span><span style="color: rgb(160, 32, 240);">'bo'</span><span>,</span><span style="color: rgb(160, 32, 240);">'MarkerFaceColor'</span><span>,</span><span style="color: rgb(160, 32, 240);">'b'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>grid </span><span style="color: rgb(160, 32, 240);">on</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>hold </span><span style="color: rgb(160, 32, 240);">on</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>scatter(outit,c,</span><span style="color: rgb(160, 32, 240);">'k'</span><span>,</span><span style="color: rgb(160, 32, 240);">'fill'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>hold </span><span style="color: rgb(160, 32, 240);">off</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>text(outit,c,[</span><span style="color: rgb(160, 32, 240);">'C ='</span><span>,num2str(c,</span><span style="color: rgb(160, 32, 240);">'%4.2f'</span><span>),</span><span style="color: rgb(160, 32, 240);">' at iteration '</span><span>, num2str(outit)],</span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(160, 32, 240);">'VerticalAlignment'</span><span>,</span><span style="color: rgb(160, 32, 240);">'bottom'</span><span>,</span><span style="color: rgb(160, 32, 240);">'HorizontalAlignment'</span><span>,</span><span style="color: rgb(160, 32, 240);">'right'</span><span>,</span><span style="color: rgb(160, 32, 240);">'FontSize'</span><span>,24,</span><span style="color: rgb(160, 32, 240);">'FontWeight'</span><span>,</span><span style="color: rgb(160, 32, 240);">'bold'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>xlabel(</span><span style="color: rgb(160, 32, 240);">'iter'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>ylabel(</span><span style="color: rgb(160, 32, 240);">'C'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>subplot(2,1,2)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>plot(1:outit,vvec(1:outit)*100,</span><span style="color: rgb(160, 32, 240);">'ro'</span><span>,</span><span style="color: rgb(160, 32, 240);">'MarkerFaceColor'</span><span>,</span><span style="color: rgb(160, 32, 240);">'r'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>grid </span><span style="color: rgb(160, 32, 240);">on</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>hold </span><span style="color: rgb(160, 32, 240);">on</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>scatter(outit,mean(xPhys(:))*100,</span><span style="color: rgb(160, 32, 240);">'k'</span><span>,</span><span style="color: rgb(160, 32, 240);">'fill'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>hold </span><span style="color: rgb(160, 32, 240);">off</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>text(outit,mean(xPhys(:))*100,[</span><span style="color: rgb(160, 32, 240);">'V = '</span><span>,num2str(mean(xPhys(:))*100,</span><span style="color: rgb(160, 32, 240);">'%4.2f'</span><span>),</span><span style="color: rgb(160, 32, 240);">'% at iteration '</span><span>, num2str(outit)],</span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(160, 32, 240);">'VerticalAlignment'</span><span>,</span><span style="color: rgb(160, 32, 240);">'bottom'</span><span>,</span><span style="color: rgb(160, 32, 240);">'HorizontalAlignment'</span><span>,</span><span style="color: rgb(160, 32, 240);">'right'</span><span>,</span><span style="color: rgb(160, 32, 240);">'FontSize'</span><span>,24,</span><span style="color: rgb(160, 32, 240);">'FontWeight'</span><span>,</span><span style="color: rgb(160, 32, 240);">'bold'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>xlabel(</span><span style="color: rgb(160, 32, 240);">'iter'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>ylabel(</span><span style="color: rgb(160, 32, 240);">'V [%]'</span><span>)</span></span></div></div><div class="inlineWrapper outputs"><div class = 'S7'><span style="white-space: pre;"><span>print([Path,image_prefix,</span><span style="color: rgb(160, 32, 240);">'convergence'</span><span>],</span><span style="color: rgb(160, 32, 240);">'-dpng'</span><span>)</span></span></div><div class = 'S8'><div class="inlineElement eoOutputWrapper embeddedOutputsFigure" uid="2AE3A6CB" data-testid="output_277" style="width: 1756px;"><div class="figureElement"><img class="figureImage figureContainingNode" 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"></div></div></div></div><div class="inlineWrapper"><div class = 'S11'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">%% PLOT DENSITIES</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>figure(1)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>map=colormap(gray);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>map=map(end:-1:1,:);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>caxis([0 1])</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>patchplot2 = patch(</span><span style="color: rgb(160, 32, 240);">'Vertices'</span><span>,[Xx,Yy],</span><span style="color: rgb(160, 32, 240);">'Faces'</span><span>,edofMat(:,[2,4,6,8])/2,</span><span style="color: rgb(160, 32, 240);">'FaceVertexCData'</span><span>,(1-xPhys(:))*[1 1 1],</span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> </span><span style="color: rgb(160, 32, 240);">'FaceColor'</span><span>,</span><span style="color: rgb(160, 32, 240);">'flat'</span><span>,</span><span style="color: rgb(160, 32, 240);">'EdgeColor'</span><span>,</span><span style="color: rgb(160, 32, 240);">'none'</span><span>); axis </span><span style="color: rgb(160, 32, 240);">equal</span><span>; axis </span><span style="color: rgb(160, 32, 240);">off</span><span>; hold </span><span style="color: rgb(160, 32, 240);">on</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>hold </span><span style="color: rgb(160, 32, 240);">on</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>fill([min(Xx),max(Xx),max(Xx),min(Xx)],[min(Yy),min(Yy),max(Yy),max(Yy)],</span><span style="color: rgb(160, 32, 240);">'w'</span><span>,</span><span style="color: rgb(160, 32, 240);">'FaceAlpha'</span><span>,0.)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>scatter(Xx(fixednodes(fixed_dir==1)),Yy(fixednodes(fixed_dir==1)),</span><span style="color: rgb(160, 32, 240);">'>b'</span><span>,</span><span style="color: rgb(160, 32, 240);">'filled'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>scatter(Xx(fixednodes(fixed_dir==2)),Yy(fixednodes(fixed_dir==2)),</span><span style="color: rgb(160, 32, 240);">'^b'</span><span>,</span><span style="color: rgb(160, 32, 240);">'filled'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>scal=10;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>quiver(Xx(excitation_node),Yy(excitation_node)+scal*(excitation_direction==2),excitation_direction==1,</span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> -(excitation_direction==2), scal,</span><span style="color: rgb(160, 32, 240);">'r'</span><span>,</span><span style="color: rgb(160, 32, 240);">'Linewidth'</span><span>,2)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>colormap(map)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>colorbar</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>drawnow</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>hold </span><span style="color: rgb(160, 32, 240);">off</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>axis([min(Xx),max(Xx),min(Yy),max(Yy)])</span></span></div></div><div class="inlineWrapper outputs"><div class = 'S7'><span style="white-space: pre;"><span>print([Path,</span><span style="color: rgb(160, 32, 240);">'density_'</span><span>,num2str(outit-1,</span><span style="color: rgb(160, 32, 240);">'%03d'</span><span>)],</span><span style="color: rgb(160, 32, 240);">'-dpng'</span><span>)</span></span></div><div class = 'S8'><div class="inlineElement eoOutputWrapper embeddedOutputsFigure" uid="1A453C9F" data-testid="output_278" style="width: 1756px;"><div class="figureElement"><img class="figureImage figureContainingNode" 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"></div></div></div></div><div class="inlineWrapper"><div class = 'S11'><span style="white-space: pre;"><span style="color: rgb(34, 139, 34);">%% Component Plot</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>figure(2)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>Xc=Xg(1:6:end);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>Yc=Xg(2:6:end);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>Lc=Xg(3:6:end);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>hc=Xg(4:6:end);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>Tc=Xg(5:6:end) ;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>Mc=Xg(6:6:end) ;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>C0=repmat(cos(Tc),1,size(cc,2));S0=repmat(sin(Tc),1,size(cc,2));</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>xxx=repmat(Xc(:),1,size(cc,2))+cc;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>yyy=repmat(Yc(:),1,size(cc,2))+ss;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>xi=C0.*(xxx-Xc)+S0.*(yyy-Yc);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>Eta=-S0.*(xxx-Xc)+C0.*(yyy-Yc);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>[dd]=norato_bar(xi,Eta,repmat(Lc(:),1,size(cc,2)),repmat(hc(:),1,size(cc,2)));</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>xn=repmat(Xc,1,size(cc,2))+dd.*cc;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>yn=repmat(Yc,1,size(cc,2))+dd.*ss;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>tolshow=0.1;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>Shown_compo=find(Mc>tolshow);</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>fill([min(Xx),max(Xx),max(Xx),min(Xx)],[min(Yy),min(Yy),max(Yy),max(Yy)],</span><span style="color: rgb(160, 32, 240);">'w'</span><span>,</span><span style="color: rgb(160, 32, 240);">'FaceAlpha'</span><span>,0.)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>hold </span><span style="color: rgb(160, 32, 240);">on</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>fill(xn(Shown_compo,:)',yn(Shown_compo,:)',Mc(Shown_compo),</span><span style="color: rgb(160, 32, 240);">'FaceAlpha'</span><span>,0.5)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(0, 0, 255);">if </span><span>strcmp(BC,</span><span style="color: rgb(160, 32, 240);">'L-shape'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> fill([fix((min(Xx)+max(Xx))/2),max(Xx),max(Xx),fix((min(Xx)+max(Xx))/2)],</span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> [fix((min(Yy)+max(Yy))/2),fix((min(Yy)+max(Yy))/2),max(Yy),max(Yy)],</span><span style="color: rgb(160, 32, 240);">'w'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span style="color: rgb(0, 0, 255);">end</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>caxis([0,1])</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>colormap </span><span style="color: rgb(160, 32, 240);">'jet'</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>axis </span><span style="color: rgb(160, 32, 240);">equal</span><span>; axis </span><span style="color: rgb(160, 32, 240);">off</span><span>;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>hold </span><span style="color: rgb(160, 32, 240);">on</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>scatter(Xx(fixednodes(fixed_dir==1)),Yy(fixednodes(fixed_dir==1)),</span><span style="color: rgb(160, 32, 240);">'>b'</span><span>,</span><span style="color: rgb(160, 32, 240);">'filled'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>scatter(Xx(fixednodes(fixed_dir==2)),Yy(fixednodes(fixed_dir==2)),</span><span style="color: rgb(160, 32, 240);">'^b'</span><span>,</span><span style="color: rgb(160, 32, 240);">'filled'</span><span>)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>scal=10;</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>quiver(Xx(excitation_node),Yy(excitation_node)+scal*(excitation_direction==2),excitation_direction==1,</span><span style="color: rgb(0, 0, 255);">...</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span> -(excitation_direction==2),scal,</span><span style="color: rgb(160, 32, 240);">'r'</span><span>,</span><span style="color: rgb(160, 32, 240);">'Linewidth'</span><span>,2)</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>colorbar</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>axis([min(Xx),max(Xx),min(Yy),max(Yy)])</span></span></div></div><div class="inlineWrapper"><div class = 'S4'><span style="white-space: pre;"><span>print([Path,</span><span style="color: rgb(160, 32, 240);">'component_'</span><span>,num2str(outit-1,</span><span style="color: rgb(160, 32, 240);">'%03d'</span><span>)],</span><span style="color: rgb(160, 32, 240);">'-dpng'</span><span>)</span></span></div></div><div class="inlineWrapper outputs"><div class = 'S7'><span style="white-space: pre;"><span>hold </span><span style="color: rgb(160, 32, 240);">off</span></span></div><div class = 'S8'><div class="inlineElement eoOutputWrapper embeddedOutputsFigure" uid="61570E1E" data-testid="output_279" style="width: 1756px;"><div class="figureElement"><img class="figureImage figureContainingNode" 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"></div></div></div></div></div></div><br>
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##### SOURCE BEGIN #####
%% Generalized Geometry Projection
% Author Simone Coniglio, 12/09/2019
%
% This is an introduction to a Matlab implementation of Generalized Geometry
% Projection approach for topology optimization.
%
% In this approach geometric primitives are projected on a Finite Element
% Mesh and assembled together to build the solution.
%% Problem set-up
% In this section of the Matlab code we define several *parameters* needed for
% the *Generalized Geometry Projection*.
%REPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASHREPLACE_WITH_DASH_DASH-
% This is the file GGP.html you can redistribute it and/or
% modify it under the terms of the GNU General Public License as
% published by the Free Software Foundation; either version 3 of
% the License, or (at your option) any later version.
%
% This code is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% (file COPYING) along with this file. If not, see
% <http://www.gnu.org/licenses/>.
%
% Version Nov 2019.
% Simone Coniglio <simone.coniglio@airbus.com>
% Propulsion Airframe Stress Transverse,
% 31300 Toulouse, France.
%
% GGP parameters
stopping_criteria='change'; %stopping criteria of the optimization algorithm either change or KKT norm
nelx=60;nely=30;
BC='Short_Cantilever';%L-shape %Short_Cantilever%MBB
p.method='GP';%MMC%MNA %GP this change the function employed for the evaluation of local volume fraction
q=1;%q=1
p.zp=1 ;% parameter for p-norm/mean regularization
p.alp=1; %parameter for MMC
p.epsi=0.866;% parameter for MMC
p.bet=1e-3; %parameter for MMC
p.deltamin=1e-6; %parameter for GP
p.r=.5;%parameter for GP
minh=1;% minimal bar thickness
p.sigma=1;%parameter for MNA
p.gammav=1;%parameter for GP
p.gammac=3;%parameter for GP
p.penalty=3;%parameter for MNA
p.aggregation='KSl'; %parameter for the aggregation function to be used
% IE= Induced Exponential % KS= KS function %KSl= lowerbound KS function
% p-norm %p-mean
p.ka=10; % parameter for the aggregation constant
p.saturation=true; % switch for saturation
ncx=1; % number of components in the x direction
ncy=1; % number of components in the y direction
Ngp=2; % number of Gauss point per sampling window
R=0.5; % radius of the sampling window (infty norm)
initial_d=0.5; % initial mass variable adopted for MNA and GP
%%
% Generate a *folder* and a prefix to save images *optimization history*:
rs=replace(num2str(R,'%3.2f'),'.','_');
folder_name=['Optimization_history_',BC,p.method,'nelx_',num2str(nelx),...
'nely_',num2str(nely),'_R_',rs,'_Ngp_',num2str(Ngp),'_SC_',stopping_criteria];
image_prefix=[BC,p.method,'nelx_',num2str(nelx),'nely_',num2str(nely),'_R_',rs,'_Ngp_',num2str(Ngp)];
mkdir(folder_name)
Path=[folder_name,'/'];
%%
% Define *Material properties*:
% MATERIAL PROPERTIES
p.E0 = 1;
p.Emin = 1e-6;
nu = 0.3;
%%
% Prepare *finite element analysis*
% PREPARE FINITE ELEMENT ANALYSIS
A11 = [12 3 -6 -3; 3 12 3 0; -6 3 12 -3; -3 0 -3 12];
A12 = [-6 -3 0 3; -3 -6 -3 -6; 0 -3 -6 3; 3 -6 3 -6];
B11 = [-4 3 -2 9; 3 -4 -9 4; -2 -9 -4 -3; 9 4 -3 -4];
B12 = [ 2 -3 4 -9; -3 2 9 -2; 4 9 2 3; -9 -2 3 2];
KE = 1/(1-nu^2)/24*([A11 A12;A12' A11]+nu*[B11 B12;B12' B11]);
nodenrs = reshape(1:(1+nelx)*(1+nely),1+nely,1+nelx);
edofVec = reshape(2*nodenrs(1:end-1,1:end-1)+1,nelx*nely,1);
edofMat = repmat(edofVec,1,8)+repmat([0 1 2*nely+[2 3 0 1] -2 -1],nelx*nely,1);
iK = reshape(kron(edofMat,ones(8,1))',64*nelx*nely,1);
jK = reshape(kron(edofMat,ones(1,8))',64*nelx*nely,1);
U = zeros(2*(nely+1)*(nelx+1),1);
%define the nodal coordinates
[Yy,Xx]=find(nodenrs);
Yy=nely+1-Yy;
Xx=Xx-1;
% Element connectivity
enodeMat=edofMat(:,[2,4,6,8])/2;
% DEFINE LOADS AND SUPPORTS
switch BC
case 'MBB'
excitation_node=1;excitation_direction=2;
amplitude=-1;
F = sparse(2*(excitation_node-1)+excitation_direction,1,amplitude,2*(nely+1)*(nelx+1),1);
fixednodes=[find(Xx==min(Xx));(nelx+1)*(nely+1)];fixed_dir=[ones(nely+1,1);2];
fixeddofs=2*(fixednodes-1)+fixed_dir;
emptyelts=[]; fullelts = [];
case 'Short_Cantilever'
excitation_node=find((Xx==max(Xx))&(Yy==fix(0.5*min(Yy)+0.5*max(Yy))));excitation_direction=2;
amplitude=-1;
F = sparse(2*(excitation_node-1)+excitation_direction,1,amplitude,2*(nely+1)*(nelx+1),1);
fixednodes=repmat(find(Xx==min(Xx)),2,1);fixed_dir=[ones(nely+1,1);2*ones(nely+1,1)];
fixeddofs=2*(fixednodes-1)+fixed_dir(:);
emptyelts=[]; fullelts = [];
case 'L-shape'
excitation_node=find((Xx==max(Xx))&(Yy==fix(0.5*min(Yy)+0.5*max(Yy))));excitation_direction=2;
amplitude=-1;
F = sparse(2*(excitation_node-1)+excitation_direction,1,amplitude,2*(nely+1)*(nelx+1),1);
fixednodes=repmat(find(Yy==max(Yy)),2,1);fixed_dir=[ones(nelx+1,1),2*ones(nelx+1,1)];
fixeddofs=2*(fixednodes-1)+fixed_dir(:);
emptyelts=find(xc>=(((max(Xx)+min(Xx))/2))&(yc>=((max(Yy)+min(Yy))/2)));
fullelts = [];
otherwise
error('BC string should be a valid entry: ''MBB'',''L-Shape'',''Short_Cantilever''')
end
alldofs = [1:2*(nely+1)*(nelx+1)];
freedofs = setdiff(alldofs,fixeddofs);
%% Prepare the *Generalized Geometry Projection:*
% Compute the element centroid coordinates:
xc=mean(Xx(enodeMat'));
yc=mean(Yy(enodeMat'));
centroid_coordinate=[xc(:),yc(:)];
%%
% Compute *Gauss point coordinates and weights *in a squared sampling window
% $[2R\times2R]$ centred in the origin
a=-R;
b=R;
[gpc,wc]=lgwt(Ngp,a,b);
[gpcx,gpcy]=meshgrid(gpc,gpc);
gauss_weight=wc*wc';
%%
% Repeat the value ones for each element in the mesh
gpcx=reshape((repmat(gpcx(:),1,size(centroid_coordinate,1)))',[],1);
gpcy=reshape((repmat(gpcy(:),1,size(centroid_coordinate,1)))',[],1);
gauss_weight=reshape((repmat(gauss_weight(:),1,size(centroid_coordinate,1)))',[],1);
%%
% translate the sampling window Gauss points of the element centroid coordinates
cc=repmat(centroid_coordinate,Ngp^2,1);
gauss_point=cc+[gpcx,gpcy];
%%
% Avoid to evaluate repeated value of sampling window gauss point coordinates:
[ugp,~,idgp]=unique(gauss_point,'rows');
%% Initialize design variable vector:
% The initial design is composed of couples of crossed components regularly
% disposed in the mesh.
xp=linspace(min(Xx),max(Xx),ncx+2);
yp=linspace(min(Yy),max(Yy),ncy+2);
[xx,yy]=meshgrid(xp,yp);
Xc=repmat(xx(:),2,1); %component center X
Yc=repmat(yy(:),2,1); %component center Y
Lc=2*sqrt((nelx/(ncx+2))^2+(nely/(ncy+2))^2)*ones(size(Xc)); %component length L
Tc=atan2(nely/ncy,nelx/ncx)*[ones(length(Xc)/2,1);-ones(length(Xc)/2,1)];% component orientation angle tetha
hc=2*ones(length(Xc),1); % component h
Mc=initial_d*ones(size(Xc)); % component mass (For MNA and GP)
Xg=reshape([Xc,Yc,Lc,hc,Tc,Mc]',[],1);
%% Build upper and lower bounds of the design problem
Xl=min(Xx-1)*ones(size(Xc));Xu=max(Xx+1)*ones(size(Xc));
Yl=min(Yy-1)*ones(size(Xc));Yu=max(Yy+1)*ones(size(Xc));
Ll=0*ones(size(Xc));Lu=sqrt(nelx^2+nely^2)*ones(size(Xc));
hl=minh*ones(size(Xc));hu=sqrt(nelx^2+nely^2)*ones(size(Xc));
Tl=-2*pi*ones(size(Xc));Tu=2*pi*ones(size(Xc));
Ml=0*ones(size(Xc));Mu=ones(size(Xc));
lower_bound=reshape([Xl,Yl,Ll,hl,Tl,Ml]',[],1);
upper_bound=reshape([Xu,Yu,Lu,hu,Tu,Mu]',[],1);
%%
% *Scale* the *design variable vector* accordingly $(X\in[0,1])$:
X=(Xg-lower_bound)./(upper_bound-lower_bound);
%% MMA initialization:
loop = 0;
m = 1;
n = length(X(:));
epsimin = 0.0000001;
eeen = ones(n,1);
eeem = ones(m,1);
zeron = zeros(n,1);
zerom = zeros(m,1);
xval = X(:);
xold1 = xval;
xold2 = xval;
xmin = zeron;
xmax = eeen;
low = xmin;
upp = xmax;
C = 1000*eeem;
d = 0*eeem;
a0 = 1;
a = zerom;
outeriter = 0;
maxoutit = 2000;
kkttol =0.001;
changetol=0.001;
kktnorm = kkttol+10;
outit = 0;
change=1;
%%
% choose the allowable *volfrac:*
volfrac=.4;
%%
% Prepare plots and quantity storage:
cvec=zeros(maxoutit,1);
vvec=cvec;ovvec=cvec;gvec=cvec;pvec=cvec;
plot_rate=10;
%initialize variables for plot
tt=0:0.005:(2*pi);tt=repmat(tt,length(Xc),1);
cc=cos(tt);ss=sin(tt);
%%
% Initialize the stopping criterion
switch stopping_criteria
case 'kktnorm'
stop_cond=outit < maxoutit && kktnorm>kkttol;
case 'change'
stop_cond=outit < maxoutit &&change>changetol;
end
%% Start the design loop:
while stop_cond
outit = outit+1;
outeriter = outeriter+1;
%Compute the smooth characteristic functions and gradients for each component
% on each sampling window Gauss point (Can support GPU)
[W,dW_dX,dW_dY,dW_dT,dW_dL,dW_dh]=Wgp(ugp(:,1),ugp(:,2),Xg,p);
%Compute local volume fractions and gradients using generalized projection
% delta is for densities, deltac for Young modulus
delta=sum(reshape(W(:,idgp).*repmat(gauss_weight(:)',size(W,1),1),size(W,1),[],Ngp^2),3)...
./sum(reshape(repmat(gauss_weight(:)',size(W,1),1),size(W,1),[],Ngp^2),3);
ddelta_dX=sum(reshape(dW_dX(:,idgp).*repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3)...
./sum(reshape(repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3);
ddelta_dY=sum(reshape(dW_dY(:,idgp).*repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3)...
./sum(reshape(repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3);
ddelta_dT=sum(reshape(dW_dT(:,idgp).*repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3)...
./sum(reshape(repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3);
ddelta_dL=sum(reshape(dW_dL(:,idgp).*repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3)...
./sum(reshape(repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3);
ddelta_dh=sum(reshape(dW_dh(:,idgp).*repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3)...
./sum(reshape(repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3);
delta_c=sum(reshape(W(:,idgp).^q.*repmat(gauss_weight(:)',size(W,1),1),size(W,1),[],Ngp^2),3)...
./sum(reshape(repmat(gauss_weight(:)',size(W,1),1),size(W,1),[],Ngp^2),3);
ddelta_c_dX=sum(reshape(q*dW_dX(:,idgp).*W(:,idgp).^(q-1).*repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3)...
./sum(reshape(repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3);
ddelta_c_dY=sum(reshape(q*dW_dY(:,idgp).*W(:,idgp).^(q-1).*repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3)...
./sum(reshape(repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3);
ddelta_c_dT=sum(reshape(q*dW_dT(:,idgp).*W(:,idgp).^(q-1).*repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3)...
./sum(reshape(repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3);
ddelta_c_dL=sum(reshape(q*dW_dL(:,idgp).*W(:,idgp).^(q-1).*repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3)...
./sum(reshape(repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3);
ddelta_c_dh=sum(reshape(q*dW_dh(:,idgp).*W(:,idgp).^(q-1).*repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3)...
./sum(reshape(repmat(gauss_weight(:)',size(dW_dX,1),1),size(dW_dX,1),[],Ngp^2),3);
% model update
% compute young modulus and gradients
[E,dE,dE_dm]=model_updateM(delta_c,p,X);
dE_dX=dE.*ddelta_c_dX;
dE_dY=dE.*ddelta_c_dY;
dE_dT=dE.*ddelta_c_dT;
dE_dL=dE.*ddelta_c_dL;
dE_dh=dE.*ddelta_c_dh;
E=full(reshape(E(:),nely,nelx));
%compute densities
[rho,drho_ddelta,drho_dm]=model_updateV(delta,p,X);
drho_dX=drho_ddelta.*ddelta_dX;
drho_dY=drho_ddelta.*ddelta_dY;
drho_dT=drho_ddelta.*ddelta_dT;
drho_dL=drho_ddelta.*ddelta_dL;
drho_dh=drho_ddelta.*ddelta_dh;
xPhys=full(reshape(rho(:),nely,nelx));
%Take in account passive elements
xPhys(emptyelts) = 0;
xPhys(fullelts) = 1;
E(emptyelts) = p.Emin;
E(fullelts) = p.E0;
% FE-ANALYSIS
sK = reshape(KE(:)*(E(:)'),64*nelx*nely,1);
K = sparse(iK,jK,sK); K = (K+K')/2;
U(freedofs) = K(freedofs,freedofs)\F(freedofs);
% OBJECTIVE FUNCTION AND SENSITIVITY ANALYSIS
ce = reshape(sum((U(edofMat)*KE).*U(edofMat),2),nely,nelx);
c = sum(sum((E).*ce));
v=mean(xPhys(:));
dc_dE = -ce;
dc_dE(emptyelts) = 0;
dc_dE(fullelts) = 0;
dc_dX=dE_dX*dc_dE(:);
dc_dY=dE_dY*dc_dE(:);
dc_dL=dE_dL*dc_dE(:);
dc_dh=dE_dh*dc_dE(:);
dc_dT=dE_dT*dc_dE(:);
dc_dm=dE_dm*dc_dE(:);
dc=zeros(size(X));
dc(1:6:end)=dc_dX;
dc(2:6:end)=dc_dY;
dc(3:6:end)=dc_dL;
dc(4:6:end)=dc_dh;
dc(5:6:end)=dc_dT;
dc(6:6:end)=dc_dm;
dv_dxPhys = ones(nely,nelx)/nelx/nely;
dv_dxPhys(emptyelts) = 0;
dv_dxPhys(fullelts) = 0;
dv_dX=drho_dX*dv_dxPhys(:);
dv_dY=drho_dY*dv_dxPhys(:);
dv_dL=drho_dL*dv_dxPhys(:);
dv_dh=drho_dh*dv_dxPhys(:);
dv_dT=drho_dT*dv_dxPhys(:);
dv_dm=drho_dm*dv_dxPhys(:);
dv=zeros(size(X));
dv(1:6:end)=dv_dX;
dv(2:6:end)=dv_dY;
dv(3:6:end)=dv_dL;
dv(4:6:end)=dv_dh;
dv(5:6:end)=dv_dT;
dv(6:6:end)=dv_dm;
% store the output for plot
cvec(outit)=c;vvec(outit)=v;
%% PRINT RESULTS
fprintf(' It.:%5i Obj.:%4.3e Vol.:%7.3f kktnorm.:%7.3f ch.:%7.3f\n',outit,c, ...
mean(xPhys(:)),kktnorm,change);
% pass scaled objective and constraint function and sensitivities to MMA
f0val=log(c+1);
fval=[(v-volfrac)/volfrac]*100;
df0dx=(dc(:)/(c+1).*(upper_bound(:)-lower_bound(:)));
dfdx=[dv(:)'/volfrac]*100.*(upper_bound(:)-lower_bound(:))';
%plot every plot_rate iterations
if rem(outit,plot_rate)==0
%convergence plot
figure(3)
subplot(2,1,1)
plot(1:outit,cvec(1:outit),'bo','MarkerFaceColor','b')
grid on
hold on
scatter(outit,c,'k','fill')
hold off
text(outit,c,['C =',num2str(c,'%4.2f'),' at iteration ', num2str(outit)],...
'VerticalAlignment','bottom','HorizontalAlignment','right','FontSize',24,'FontWeight','bold')
xlabel('iter')
ylabel('C')
subplot(2,1,2)
plot(1:outit,vvec(1:outit)*100,'ro','MarkerFaceColor','r')
grid on
hold on
scatter(outit,mean(xPhys(:))*100,'k','fill')
hold off
text(outit,mean(xPhys(:))*100,['V = ',num2str(mean(xPhys(:))*100,'%4.2f'),'% at iteration ', num2str(outit)],...
'VerticalAlignment','bottom','HorizontalAlignment','right','FontSize',24,'FontWeight','bold')
xlabel('iter')
ylabel('V [%]')
print([Path,image_prefix,'convergence'],'-dpng')
%% PLOT DENSITIES
figure(1)
map=colormap(gray);
map=map(end:-1:1,:);
caxis([0 1])
patchplot2 = patch('Vertices',[Xx,Yy],'Faces',edofMat(:,[2,4,6,8])/2,'FaceVertexCData',(1-xPhys(:))*[1 1 1],...
'FaceColor','flat','EdgeColor','none'); axis equal; axis off; hold on
hold on
fill([min(Xx),max(Xx),max(Xx),min(Xx)],[min(Yy),min(Yy),max(Yy),max(Yy)],'w','FaceAlpha',0.)
scatter(Xx(fixednodes(fixed_dir==1)),Yy(fixednodes(fixed_dir==1)),'>b','filled')
scatter(Xx(fixednodes(fixed_dir==2)),Yy(fixednodes(fixed_dir==2)),'^b','filled')
scal=10;
quiver(Xx(excitation_node),Yy(excitation_node)+scal*(excitation_direction==2),excitation_direction==1,...
-(excitation_direction==2), scal,'r','Linewidth',2)
colormap(map)
colorbar
drawnow
hold off
axis([min(Xx),max(Xx),min(Yy),max(Yy)])
print([Path,'density_',num2str(outit-1,'%03d')],'-dpng')
%% Component Plot
figure(2)
Xc=Xg(1:6:end);
Yc=Xg(2:6:end);
Lc=Xg(3:6:end);
hc=Xg(4:6:end);
Tc=Xg(5:6:end) ;
Mc=Xg(6:6:end) ;
C0=repmat(cos(Tc),1,size(cc,2));S0=repmat(sin(Tc),1,size(cc,2));
xxx=repmat(Xc(:),1,size(cc,2))+cc;
yyy=repmat(Yc(:),1,size(cc,2))+ss;
xi=C0.*(xxx-Xc)+S0.*(yyy-Yc);
Eta=-S0.*(xxx-Xc)+C0.*(yyy-Yc);
[dd]=norato_bar(xi,Eta,repmat(Lc(:),1,size(cc,2)),repmat(hc(:),1,size(cc,2)));
xn=repmat(Xc,1,size(cc,2))+dd.*cc;
yn=repmat(Yc,1,size(cc,2))+dd.*ss;
tolshow=0.1;
Shown_compo=find(Mc>tolshow);
fill([min(Xx),max(Xx),max(Xx),min(Xx)],[min(Yy),min(Yy),max(Yy),max(Yy)],'w','FaceAlpha',0.)
hold on
fill(xn(Shown_compo,:)',yn(Shown_compo,:)',Mc(Shown_compo),'FaceAlpha',0.5)
if strcmp(BC,'L-shape')
fill([fix((min(Xx)+max(Xx))/2),max(Xx),max(Xx),fix((min(Xx)+max(Xx))/2)],[fix((min(Yy)+max(Yy))/2),...
fix((min(Yy)+max(Yy))/2),max(Yy),max(Yy)],'w')
end
caxis([0,1])
colormap 'jet'
axis equal; axis off;
hold on
scatter(Xx(fixednodes(fixed_dir==1)),Yy(fixednodes(fixed_dir==1)),'>b','filled')
scatter(Xx(fixednodes(fixed_dir==2)),Yy(fixednodes(fixed_dir==2)),'^b','filled')
scal=10;
quiver(Xx(excitation_node),Yy(excitation_node)+scal*(excitation_direction==2),excitation_direction==1,...
-(excitation_direction==2),scal,'r','Linewidth',2)
colorbar
axis([min(Xx),max(Xx),min(Yy),max(Yy)])
print([Path,'component_',num2str(outit-1,'%03d')],'-dpng')
hold off
end
%% MMA code optimization
[X,ymma,zmma,lam,xsi,eta,mu,zet,S,low,upp] = ...
mmasub(m,n,outeriter,xval,xmin,xmax,xold1,xold2, ...
f0val,df0dx,fval,dfdx,low,upp,a0,a,C,d);
xold2 = xold1;
xold1 = xval;
xval = X;
Xg=lower_bound+(upper_bound-lower_bound).*X;
change=norm(xval-xold1);
%% The residual vector of the KKT conditions is calculated:
[residu,kktnorm,residumax] = ...
kktcheck(m,n,X,ymma,zmma,lam,xsi,eta,mu,zet,S, ...
xmin,xmax,df0dx,fval,dfdx,a0,a,C,d);
% update the stopping criterion
switch stopping_criteria
case 'kktnorm'
stop_cond=outit < maxoutit && kktnorm>kkttol;
case 'change'
stop_cond=outit < maxoutit &&change>changetol;
end
end
% Make the plot of the solution
% convergence plot
figure(3)
subplot(2,1,1)
plot(1:outit,cvec(1:outit),'bo','MarkerFaceColor','b')
grid on
hold on
scatter(outit,c,'k','fill')
hold off
text(outit,c,['C =',num2str(c,'%4.2f'),' at iteration ', num2str(outit)],...
'VerticalAlignment','bottom','HorizontalAlignment','right','FontSize',24,'FontWeight','bold')
xlabel('iter')
ylabel('C')
subplot(2,1,2)
plot(1:outit,vvec(1:outit)*100,'ro','MarkerFaceColor','r')
grid on
hold on
scatter(outit,mean(xPhys(:))*100,'k','fill')
hold off
text(outit,mean(xPhys(:))*100,['V = ',num2str(mean(xPhys(:))*100,'%4.2f'),'% at iteration ', num2str(outit)],...
'VerticalAlignment','bottom','HorizontalAlignment','right','FontSize',24,'FontWeight','bold')
xlabel('iter')
ylabel('V [%]')
print([Path,image_prefix,'convergence'],'-dpng')
%% PLOT DENSITIES
figure(1)
map=colormap(gray);
map=map(end:-1:1,:);
caxis([0 1])
patchplot2 = patch('Vertices',[Xx,Yy],'Faces',edofMat(:,[2,4,6,8])/2,'FaceVertexCData',(1-xPhys(:))*[1 1 1],...
'FaceColor','flat','EdgeColor','none'); axis equal; axis off; hold on
hold on
fill([min(Xx),max(Xx),max(Xx),min(Xx)],[min(Yy),min(Yy),max(Yy),max(Yy)],'w','FaceAlpha',0.)
scatter(Xx(fixednodes(fixed_dir==1)),Yy(fixednodes(fixed_dir==1)),'>b','filled')
scatter(Xx(fixednodes(fixed_dir==2)),Yy(fixednodes(fixed_dir==2)),'^b','filled')
scal=10;
quiver(Xx(excitation_node),Yy(excitation_node)+scal*(excitation_direction==2),excitation_direction==1,...
-(excitation_direction==2), scal,'r','Linewidth',2)
colormap(map)
colorbar
drawnow
hold off
axis([min(Xx),max(Xx),min(Yy),max(Yy)])
print([Path,'density_',num2str(outit-1,'%03d')],'-dpng')
%% Component Plot
figure(2)
Xc=Xg(1:6:end);
Yc=Xg(2:6:end);
Lc=Xg(3:6:end);
hc=Xg(4:6:end);
Tc=Xg(5:6:end) ;
Mc=Xg(6:6:end) ;
C0=repmat(cos(Tc),1,size(cc,2));S0=repmat(sin(Tc),1,size(cc,2));
xxx=repmat(Xc(:),1,size(cc,2))+cc;
yyy=repmat(Yc(:),1,size(cc,2))+ss;
xi=C0.*(xxx-Xc)+S0.*(yyy-Yc);
Eta=-S0.*(xxx-Xc)+C0.*(yyy-Yc);
[dd]=norato_bar(xi,Eta,repmat(Lc(:),1,size(cc,2)),repmat(hc(:),1,size(cc,2)));
xn=repmat(Xc,1,size(cc,2))+dd.*cc;
yn=repmat(Yc,1,size(cc,2))+dd.*ss;
tolshow=0.1;
Shown_compo=find(Mc>tolshow);
fill([min(Xx),max(Xx),max(Xx),min(Xx)],[min(Yy),min(Yy),max(Yy),max(Yy)],'w','FaceAlpha',0.)
hold on
fill(xn(Shown_compo,:)',yn(Shown_compo,:)',Mc(Shown_compo),'FaceAlpha',0.5)
if strcmp(BC,'L-shape')
fill([fix((min(Xx)+max(Xx))/2),max(Xx),max(Xx),fix((min(Xx)+max(Xx))/2)],...
[fix((min(Yy)+max(Yy))/2),fix((min(Yy)+max(Yy))/2),max(Yy),max(Yy)],'w')
end
caxis([0,1])
colormap 'jet'
axis equal; axis off;
hold on
scatter(Xx(fixednodes(fixed_dir==1)),Yy(fixednodes(fixed_dir==1)),'>b','filled')
scatter(Xx(fixednodes(fixed_dir==2)),Yy(fixednodes(fixed_dir==2)),'^b','filled')
scal=10;
quiver(Xx(excitation_node),Yy(excitation_node)+scal*(excitation_direction==2),excitation_direction==1,...
-(excitation_direction==2),scal,'r','Linewidth',2)
colorbar
axis([min(Xx),max(Xx),min(Yy),max(Yy)])
print([Path,'component_',num2str(outit-1,'%03d')],'-dpng')
hold off
##### SOURCE END #####
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