forked from ankrh/MCmatlab
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Example11_MultipleHeatSims.m
204 lines (174 loc) · 11 KB
/
Example11_MultipleHeatSims.m
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
%% Decription
% This example is very similar to example 4, the geometry and light
% propagation part being the same. It illustrates the ability to sequence
% together multiple pulse trains in the form of separate heat simulations,
% carrying over the temperature and thermal damage from one simulation to
% the next. A movie is generated that shows all the heat simulations.
%
% The first heat simulation has a single light pulse of 2 ms on-time
% followed by 3 ms off-time. The second heat simulation adds nine more
% pulses onto that with 0.5 ms on-time and 4.5 ms off-time.
%
% In these heat simulations, largeTimeSteps is set to true and nUpdates set
% to 10 rather than 100, which speeds up the simulations considerably.
%% MCmatlab abbreviations
% G: Geometry, MC: Monte Carlo, FMC: Fluorescence Monte Carlo, HS: Heat
% simulation, M: Media array, FR: Fluence rate, FD: Fractional damage.
%
% There are also some optional abbreviations you can use when referencing
% object/variable names: LS = lightSource, LC = lightCollector, FPID =
% focalPlaneIntensityDistribution, AID = angularIntensityDistribution, NI =
% normalizedIrradiance, NFR = normalizedFluenceRate.
%
% For example, "model.MC.LS.FPID.radialDistr" is the same as
% "model.MC.lightSource.focalPlaneIntensityDistribution.radialDistr"
%% Geometry definition
MCmatlab.closeMCmatlabFigures();
model = MCmatlab.model;
model.G.nx = 100; % Number of bins in the x direction
model.G.ny = 100; % Number of bins in the y direction
model.G.nz = 100; % Number of bins in the z direction
model.G.Lx = .1; % [cm] x size of simulation cuboid
model.G.Ly = .1; % [cm] y size of simulation cuboid
model.G.Lz = .1; % [cm] z size of simulation cuboid
model.G.mediaPropertiesFunc = @mediaPropertiesFunc; % Media properties defined as a function at the end of this file
model.G.geomFunc = @geometryDefinition; % Function to use for defining the distribution of media in the cuboid. Defined at the end of this m file.
model = plot(model,'G');
%% Monte Carlo simulation
model.MC.simulationTimeRequested = .1; % [min] Time duration of the simulation
model.MC.matchedInterfaces = true; % Assumes all refractive indices are the same
model.MC.boundaryType = 1; % 0: No escaping boundaries, 1: All cuboid boundaries are escaping, 2: Top cuboid boundary only is escaping, 3: Top and bottom boundaries are escaping, while the side boundaries are cyclic
model.MC.wavelength = 532; % [nm] Excitation wavelength, used for determination of optical properties for excitation light
model.MC.lightSource.sourceType = 4; % 0: Pencil beam, 1: Isotropically emitting line or point source, 2: Infinite plane wave, 3: Laguerre-Gaussian LG01 beam, 4: Radial-factorizable beam (e.g., a Gaussian beam), 5: X/Y factorizable beam (e.g., a rectangular LED emitter)
model.MC.lightSource.focalPlaneIntensityDistribution.radialDistr = 0; % Radial focal plane intensity distribution - 0: Top-hat, 1: Gaussian, Array: Custom. Doesn't need to be normalized.
model.MC.lightSource.focalPlaneIntensityDistribution.radialWidth = .03; % [cm] Radial focal plane 1/e^2 radius if top-hat or Gaussian or half-width of the full distribution if custom
model.MC.lightSource.angularIntensityDistribution.radialDistr = 0; % Radial angular intensity distribution - 0: Top-hat, 1: Gaussian, 2: Cosine (Lambertian), Array: Custom. Doesn't need to be normalized.
model.MC.lightSource.angularIntensityDistribution.radialWidth = 0; % [rad] Radial angular 1/e^2 half-angle if top-hat or Gaussian or half-angle of the full distribution if custom. For a diffraction limited Gaussian beam, this should be set to model.MC.wavelength*1e-9/(pi*model.MC.lightSource.focalPlaneIntensityDistribution.radialWidth*1e-2))
model.MC.lightSource.xFocus = 0; % [cm] x position of focus
model.MC.lightSource.yFocus = 0; % [cm] y position of focus
model.MC.lightSource.zFocus = 0; % [cm] z position of focus
model.MC.lightSource.theta = 0; % [rad] Polar angle of beam center axis
model.MC.lightSource.phi = 0; % [rad] Azimuthal angle of beam center axis
model = runMonteCarlo(model);
model = plot(model,'MC');
%% First pulse heat simulation
model.MC.P = 4; % [W] Incident pulse peak power (in case of infinite plane waves, only the power incident upon the cuboid's top surface)
model.HS.useAllCPUs = true; % If false, MCmatlab will leave one processor unused. Useful for doing other work on the PC while simulations are running.
model.HS.makeMovie = true; % Requires silentMode = false.
model.HS.deferMovieWrite = true; % (Default: false) If true, will not write the movie to file upon completion, but will store the raw frames in HSoutput for future writing
model.HS.largeTimeSteps = true; % (Default: false) If true, calculations will be faster, but some voxel temperatures may be slightly less precise. Test for yourself whether this precision is acceptable for your application.
model.HS.heatBoundaryType = 0; % 0: Insulating boundaries, 1: Constant-temperature boundaries (heat-sinked)
model.HS.durationOn = 0.002; % [s] Pulse on-duration
model.HS.durationOff = 0.003; % [s] Pulse off-duration
model.HS.durationEnd = 0.000; % [s] Non-illuminated relaxation time to add to the end of the simulation to let temperature diffuse after the pulse train
model.HS.T = 37; % [deg C] Initial temperature
model.HS.nPulses = 1; % Number of consecutive pulses, each with an illumination phase and a diffusion phase. If simulating only illumination or only diffusion, use nPulses = 1.
model.HS.plotTempLimits = [37 100]; % [deg C] Expected range of temperatures, used only for setting the color scale in the plot
model.HS.nUpdates = 10; % Number of times data is extracted for plots during each pulse. A minimum of 1 update is performed in each phase (2 for each pulse consisting of an illumination phase and a diffusion phase)
model.HS.slicePositions = [.5 0.6 1]; % Relative slice positions [x y z] for the 3D plots on a scale from 0 to 1
model.HS.tempSensorPositions = [0 0 0.038
0 0 0.04
0 0 0.042
0 0 0.044]; % Each row is a temperature sensor's absolute [x y z] coordinates. Leave the matrix empty ([]) to disable temperature sensors.
model = simulateHeatDistribution(model);
%% Remaining pulse train heat simulation
% The model.HS struct is modified slightly but keeps its data from the
% previous pulse (HS.T, HS.sensorTemps, HS.Omega, etc.)
model.HS.deferMovieWrite = false; % (Default: false) If true, will not write the movie to file upon completion, but will store the raw frames in HSoutput for future writing
model.HS.durationOn = 0.0005; % [s] Pulse on-duration
model.HS.durationOff = 0.0045; % [s] Pulse off-duration
model.HS.durationEnd = 0.01; % [s] Non-illuminated relaxation time to add to the end of the simulation to let temperature diffuse after the pulse train
model.HS.nPulses = 9; % Number of consecutive pulses, each with an illumination phase and a diffusion phase. If simulating only illumination or only diffusion, use nPulses = 1.
model = simulateHeatDistribution(model);
model = plot(model,'HS');
%% Geometry function(s) (see readme for details)
function M = geometryDefinition(X,Y,Z,parameters)
% Blood vessel example:
zsurf = 0.01;
epd_thick = 0.006;
vesselradius = 0.0100;
vesseldepth = 0.04;
M = ones(size(X)); % fill background with water (gel)
M(Z > zsurf) = 2; % epidermis
M(Z > zsurf + epd_thick) = 3; % dermis
M(X.^2 + (Z - (zsurf + vesseldepth)).^2 < vesselradius^2) = 4; % blood
end
%% Media Properties function (see readme for details)
function mediaProperties = mediaPropertiesFunc(parameters)
mediaProperties = MCmatlab.mediumProperties;
j=1;
mediaProperties(j).name = 'water';
mediaProperties(j).mua = 0.00036; % [cm^-1]
mediaProperties(j).mus = 10; % [cm^-1]
mediaProperties(j).g = 1.0;
mediaProperties(j).VHC = 4.19; % [J cm^-3 K^-1]
mediaProperties(j).TC = 5.8e-3; % [W cm^-1 K^-1]
j=2;
mediaProperties(j).name = 'epidermis';
mediaProperties(j).mua = @func_mua2;
function mua = func_mua2(wavelength)
B = 0; % Blood content
S = 0.75; % Blood oxygen saturation
W = 0.75; % Water content
M = 0.03; % Melanin content
F = 0; % Fat content
mua = calc_mua(wavelength,S,B,W,F,M); % Jacques "Optical properties of biological tissues: a review" eq. 12
end
mediaProperties(j).mus = @func_mus2;
function mus = func_mus2(wavelength)
aPrime = 40; % musPrime at 500 nm
fRay = 0; % Fraction of scattering due to Rayleigh scattering
bMie = 1; % Scattering power for Mie scattering
g = 0.9; % Scattering anisotropy
mus = calc_mus(wavelength,aPrime,fRay,bMie,g); % Jacques "Optical properties of biological tissues: a review" eq. 2
end
mediaProperties(j).g = 0.9;
mediaProperties(j).VHC = 3391*1.109e-3; % [J cm^-3 K^-1]
mediaProperties(j).TC = 0.37e-2; % [W cm^-1 K^-1]
j=3;
mediaProperties(j).name = 'dermis';
mediaProperties(j).mua = @func_mua3;
function mua = func_mua3(wavelength)
B = 0.002; % Blood content
S = 0.67; % Blood oxygen saturation
W = 0.65; % Water content
M = 0; % Melanin content
F = 0; % Fat content
mua = calc_mua(wavelength,S,B,W,F,M); % Jacques "Optical properties of biological tissues: a review" eq. 12
end
mediaProperties(j).mus = @func_mus3;
function mus = func_mus3(wavelength)
aPrime = 42.4; % musPrime at 500 nm
fRay = 0.62; % Fraction of scattering due to Rayleigh scattering
bMie = 1; % Scattering power for Mie scattering
g = 0.9; % Scattering anisotropy
mus = calc_mus(wavelength,aPrime,fRay,bMie,g); % Jacques "Optical properties of biological tissues: a review" eq. 2
end
mediaProperties(j).g = 0.9;
mediaProperties(j).VHC = 3391*1.109e-3; % [J cm^-3 K^-1]
mediaProperties(j).TC = 0.37e-2; % [W cm^-1 K^-1]
j=4;
mediaProperties(j).name = 'blood';
mediaProperties(j).mua = @func_mua4;
function mua = func_mua4(wavelength)
B = 1; % Blood content
S = 0.75; % Blood oxygen saturation
W = 0.95; % Water content
M = 0; % Melanin content
F = 0; % Fat content
mua = calc_mua(wavelength,S,B,W,F,M); % Jacques "Optical properties of biological tissues: a review" eq. 12
end
mediaProperties(j).mus = @func_mus4;
function mus = func_mus4(wavelength)
aPrime = 10; % musPrime at 500 nm
fRay = 0; % Fraction of scattering due to Rayleigh scattering
bMie = 1; % Scattering power for Mie scattering
g = 0.9; % Scattering anisotropy
mus = calc_mus(wavelength,aPrime,fRay,bMie,g); % Jacques "Optical properties of biological tissues: a review" eq. 2
end
mediaProperties(j).g = 0.9;
mediaProperties(j).VHC = 3617*1.050e-3; % [J cm^-3 K^-1]
mediaProperties(j).TC = 0.52e-2; % [W cm^-1 K^-1]
mediaProperties(j).E = 422.5e3; % J/mol PLACEHOLDER DATA ONLY
mediaProperties(j).A = 7.6e66; % 1/s PLACEHOLDER DATA ONLY
end