Merge pull request #448 from rmcdermo/master

NIST Pool Fires: add NIST puffing frequency results
MaCFP · Sep 11, 2023 · 184155b · 184155b
2 parents 736acc6 + dd9a0fa
commit 184155b
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diff --git a/.github/workflows/Liquid_Pool_Fires.yml b/.github/workflows/Liquid_Pool_Fires.yml
@@ -48,6 +48,10 @@ jobs:
           echo $GITHUB_WORKSPACE
           cd $GITHUB_WORKSPACE/Liquid_Pool_Fires/NIST_Pool_Fires/Computational_Results/2023/NIST
           python NIST_Pool_Fires_plot_cmp.py
+          python NIST_Pool_Fires_1m_methanol_power_spectrum.py
+          python NIST_Pool_Fires_30cm_methanol_power_spectrum.py
+          python NIST_Pool_Fires_37cm_20kW_propane_power_spectrum.py
+          python NIST_Pool_Fires_37cm_34kW_propane_power_spectrum.py
 
       # Step 2: push the plots to the releases page
       - name: Push NIST NIST Pool Fires Results to release

diff --git a/..._Pool_Fires/Computational_Results/2023/NIST/NIST_Pool_Fires_1m_methanol_power_spectrum.py b/..._Pool_Fires/Computational_Results/2023/NIST/NIST_Pool_Fires_1m_methanol_power_spectrum.py
@@ -0,0 +1,77 @@
+# McDermott
+# 25 March 2021
+# power_spectrum.py
+
+import sys
+# sys.path.append('<path to macfp-db>/macfp-db/Utilities/')
+sys.path.append('../../../../../../macfp-db/Utilities/')
+
+import macfp
+import importlib
+importlib.reload(macfp)
+import matplotlib.pyplot as plt
+from scipy import signal
+import pandas as pd
+import numpy as np
+
+# get the model results
+M1 = pd.read_csv('./Output/NIST_Methanol_1m_GEOM_Predicted_10cm_cat_devc.csv', header=1, sep=' *, *', engine='python')
+M2 = pd.read_csv('./Output/NIST_Methanol_1m_GEOM_Predicted_5cm_cat_devc.csv', header=1, sep=' *, *', engine='python')
+M3 = pd.read_csv('./Output/NIST_Methanol_1m_GEOM_Predicted_2p5cm_cat_devc.csv', header=1, sep=' *, *', engine='python')
+
+fs1 = len(M1['Time'])/max(M1['Time'])
+fs2 = len(M2['Time'])/max(M2['Time'])
+fs3 = len(M3['Time'])/max(M3['Time'])
+
+x1 = M1['"w"'][M1['Time']>30.]
+x2 = M2['"w"'][M2['Time']>30.]
+x3 = M3['"w"'][M3['Time']>30.]
+
+f1, Pxx_den_1 = signal.periodogram(x1, fs1)
+f2, Pxx_den_2 = signal.periodogram(x2, fs2)
+f3, Pxx_den_3 = signal.periodogram(x3, fs3)
+
+# plot experimental result
+
+fpuff = 1.37
+funce = 0.0
+fmeas = np.array([fpuff, fpuff])
+PSDmeas = np.array([0., 2.])
+fh=macfp.plot_to_fig(fmeas, PSDmeas,
+                  plot_type='linear',
+                  x_min=0.5,x_max=4,y_min=0,y_max=15,
+                  x_label='frequency [Hz]',
+                  y_label='PSD [V**2/Hz]',
+                  line_style='--',
+                  line_width=2,
+                  line_color='black',
+                  institute_label='NIST predicted MLR',
+                  revision_label='MaCFP-3, Tsukuba, Japan',
+                  data_label='Exp',
+                  plot_title='NIST 1 m Methanol Puffing Frequency',
+                  show_legend=True,
+                  legend_location='right')
+
+# add error to measuered puffing freq
+plt.fill_betweenx(PSDmeas, np.array([fpuff-funce, fpuff-funce]), np.array([fpuff+funce, fpuff+funce]), color='lightgrey', figure=fh)
+
+fh=macfp.plot_to_fig(f1, Pxx_den_1, plot_type='linear',x_min=0.5,x_max=4,y_min=0,y_max=2.5,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',data_label='FDS $\Delta x=10$ cm', line_style='-', line_width=1,line_color='black',  marker_style='o',marker_size=4,marker_edge_color='black', marker_fill_color='None',figure_handle=fh,show_legend=True,legend_location='right')
+fh=macfp.plot_to_fig(f2, Pxx_den_2, plot_type='linear',x_min=0.5,x_max=4,y_min=0,y_max=2.5,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',data_label='FDS $\Delta x=5$ cm', line_style='-', line_width=1,line_color='magenta',marker_style='^',marker_size=4,marker_edge_color='magenta',marker_fill_color='None',figure_handle=fh,show_legend=True,legend_location='right')
+fh=macfp.plot_to_fig(f3, Pxx_den_3, plot_type='linear',x_min=0.5,x_max=4,y_min=0,y_max=2.5,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',data_label='FDS $\Delta x=2.5$ cm', line_style='-.',line_width=1,line_color='red',marker_style='s',marker_size=4,marker_edge_color='red', marker_fill_color='None',figure_handle=fh,show_legend=True,legend_location='right')
+
+print(f3[np.where(Pxx_den_3==Pxx_den_3.max())])
+
+# plt.show()
+
+plt.savefig('./Plots/NIST_1m_Methanol_puffing_frequency.pdf')
+
+# loglog spectrum
+fh2=macfp.plot_to_fig(f3, Pxx_den_3, plot_type='loglog',x_min=0.5,x_max=1000,y_min=.00001,y_max=100,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',plot_title='NIST 1 m Methanol Power Spectrum',data_label='FDS $\Delta x=2.5$ cm',line_style='-', line_width=1,line_color='black',show_legend=True,legend_location='center right',legend_framealpha=1.,institute_label='NIST predicted MLR')
+macfp.plot_to_fig(f3, f3**(-5./3.),plot_type='loglog',x_min=0.5,x_max=1000,y_min=.00001,y_max=100,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',data_label='f**-5/3',line_style='--', line_width=2,line_color='black',show_legend=True,legend_location='center right',legend_framealpha=1.,figure_handle=fh2)
+fnyquist = np.array([0.5*fs3, 0.5*fs3])
+macfp.plot_to_fig(fnyquist, PSDmeas,plot_type='loglog',x_min=0.5,x_max=1000,y_min=.00001,y_max=100,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',data_label='f Nyquist',line_style='--', line_width=1,line_color='red',show_legend=True,legend_location='center right',legend_framealpha=1.,figure_handle=fh2)
+macfp.plot_to_fig(fmeas, PSDmeas,plot_type='loglog',x_min=0.5,x_max=1000,y_min=.00001,y_max=100,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',data_label='f puffing',line_style='--', line_width=1,line_color='green',show_legend=True,legend_location='center right',legend_framealpha=1.,figure_handle=fh2)
+
+# plt.show()
+
+plt.savefig('./Plots/NIST_1m_Methanol_Power_Spectrum.pdf')
diff --git a/...ool_Fires/Computational_Results/2023/NIST/NIST_Pool_Fires_30cm_methanol_power_spectrum.py b/...ool_Fires/Computational_Results/2023/NIST/NIST_Pool_Fires_30cm_methanol_power_spectrum.py
@@ -0,0 +1,82 @@
+# McDermott
+# 25 March 2021
+# power_spectrum.py
+
+import sys
+# sys.path.append('<path to macfp-db>/macfp-db/Utilities/')
+sys.path.append('../../../../../../macfp-db/Utilities/')
+
+import macfp
+import importlib
+importlib.reload(macfp)
+import matplotlib.pyplot as plt
+from scipy import signal
+import pandas as pd
+import numpy as np
+
+# get the model results
+M1 = pd.read_csv('./Output/NIST_Methanol_GEOM_Predicted_4cm_cat_devc.csv', header=1, sep=' *, *', engine='python')
+M2 = pd.read_csv('./Output/NIST_Methanol_GEOM_Predicted_2cm_cat_devc.csv', header=1, sep=' *, *', engine='python')
+M3 = pd.read_csv('./Output/NIST_Methanol_GEOM_Predicted_1cm_cat_devc.csv', header=1, sep=' *, *', engine='python')
+M4 = pd.read_csv('./Output/NIST_Methanol_GEOM_Predicted_p5cm_cat_devc.csv', header=1, sep=' *, *', engine='python')
+
+fs1 = len(M1['Time'])/max(M1['Time'])
+fs2 = len(M2['Time'])/max(M2['Time'])
+fs3 = len(M3['Time'])/max(M3['Time'])
+fs4 = len(M4['Time'])/max(M4['Time'])
+
+x1 = M1['"w"'][M1['Time']>30.]
+x2 = M2['"w"'][M2['Time']>30.]
+x3 = M3['"w"'][M3['Time']>30.]
+x4 = M4['"w"'][M4['Time']>30.]
+
+f1, Pxx_den_1 = signal.periodogram(x1, fs1)
+f2, Pxx_den_2 = signal.periodogram(x2, fs2)
+f3, Pxx_den_3 = signal.periodogram(x3, fs3)
+f4, Pxx_den_4 = signal.periodogram(x4, fs4)
+
+# plot experimental result
+
+fpuff = 2.64
+funce = 0.06
+fmeas = np.array([fpuff, fpuff])
+PSDmeas = np.array([0., .75])
+fh=macfp.plot_to_fig(fmeas, PSDmeas,
+                  plot_type='linear',
+                  x_min=0.5,x_max=4,y_min=0,y_max=15,
+                  x_label='frequency [Hz]',
+                  y_label='PSD [V**2/Hz]',
+                  line_style='--',
+                  line_width=2,
+                  line_color='black',
+                  institute_label='NIST predicted MLR',
+                  revision_label='MaCFP-3, Tsukuba, Japan',
+                  data_label='Exp',
+                  plot_title='NIST 30 cm Methanol Puffing Frequency',
+                  show_legend=True,
+                  legend_location='right')
+
+# add error to measuered puffing freq
+plt.fill_betweenx(PSDmeas, np.array([fpuff-funce, fpuff-funce]), np.array([fpuff+funce, fpuff+funce]), color='lightgrey', figure=fh)
+
+fh=macfp.plot_to_fig(f1, Pxx_den_1, plot_type='linear',x_min=0.5,x_max=4,y_min=0,y_max=1,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',data_label='FDS $\Delta x=4$ cm', line_style='-', line_width=1,line_color='black',  marker_style='o',marker_size=4,marker_edge_color='black', marker_fill_color='None',figure_handle=fh,show_legend=True,legend_location='center left')
+fh=macfp.plot_to_fig(f2, Pxx_den_2, plot_type='linear',x_min=0.5,x_max=4,y_min=0,y_max=1,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',data_label='FDS $\Delta x=2$ cm', line_style='-', line_width=1,line_color='magenta',marker_style='^',marker_size=4,marker_edge_color='magenta',marker_fill_color='None',figure_handle=fh,show_legend=True,legend_location='center left')
+fh=macfp.plot_to_fig(f3, Pxx_den_3, plot_type='linear',x_min=0.5,x_max=4,y_min=0,y_max=1,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',data_label='FDS $\Delta x=1$ cm', line_style='-.',line_width=1,line_color='red',marker_style='s',marker_size=4,marker_edge_color='red', marker_fill_color='None',figure_handle=fh,show_legend=True,legend_location='center left')
+fh=macfp.plot_to_fig(f4, Pxx_den_4, plot_type='linear',x_min=0.5,x_max=4,y_min=0,y_max=1,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',data_label='FDS $\Delta x=0.5$ cm', line_style='-.',line_width=1,line_color='blue',marker_style='>',marker_size=4,marker_edge_color='blue', marker_fill_color='None',figure_handle=fh,show_legend=True,legend_location='center left')
+
+print(f4[np.where(Pxx_den_4==Pxx_den_4.max())])
+
+# plt.show()
+
+plt.savefig('./Plots/NIST_30cm_Methanol_puffing_frequency.pdf')
+
+# loglog spectrum
+fh2=macfp.plot_to_fig(f4, Pxx_den_4, plot_type='loglog',x_min=0.5,x_max=1000,y_min=.00001,y_max=100,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',plot_title='NIST 30 cm Methanol Power Spectrum',data_label='FDS $\Delta x=0.5$ cm',line_style='-', line_width=1,line_color='black',show_legend=True,legend_location='center right',legend_framealpha=1.,institute_label='NIST predicted MLR')
+macfp.plot_to_fig(f4, f4**(-5./3.),plot_type='loglog',x_min=0.5,x_max=1000,y_min=.00001,y_max=100,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',data_label='f**-5/3',line_style='--', line_width=2,line_color='black',show_legend=True,legend_location='center right',legend_framealpha=1.,figure_handle=fh2)
+fnyquist = np.array([0.5*fs4, 0.5*fs4])
+macfp.plot_to_fig(fnyquist, PSDmeas,plot_type='loglog',x_min=0.5,x_max=1000,y_min=.00001,y_max=100,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',data_label='f Nyquist',line_style='--', line_width=1,line_color='red',show_legend=True,legend_location='center right',legend_framealpha=1.,figure_handle=fh2)
+macfp.plot_to_fig(fmeas, PSDmeas,plot_type='loglog',x_min=0.5,x_max=1000,y_min=.00001,y_max=100,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',data_label='f puffing',line_style='--', line_width=1,line_color='green',show_legend=True,legend_location='center right',legend_framealpha=1.,figure_handle=fh2)
+
+# plt.show()
+
+plt.savefig('./Plots/NIST_30cm_Methanol_Power_Spectrum.pdf')
diff --git a/...Fires/Computational_Results/2023/NIST/NIST_Pool_Fires_37cm_20kW_propane_power_spectrum.py b/...Fires/Computational_Results/2023/NIST/NIST_Pool_Fires_37cm_20kW_propane_power_spectrum.py
@@ -0,0 +1,76 @@
+# McDermott
+# 25 March 2021
+# power_spectrum.py
+
+import sys
+# sys.path.append('<path to macfp-db>/macfp-db/Utilities/')
+sys.path.append('../../../../../../macfp-db/Utilities/')
+
+import macfp
+import importlib
+importlib.reload(macfp)
+import matplotlib.pyplot as plt
+from scipy import signal
+import pandas as pd
+import numpy as np
+
+# get the model results
+M1 = pd.read_csv('./Output/NIST_Propane_20kW_GEOM_Prescribed_4cm_cat_devc.csv', header=1, sep=' *, *', engine='python')
+M2 = pd.read_csv('./Output/NIST_Propane_20kW_GEOM_Prescribed_2cm_cat_devc.csv', header=1, sep=' *, *', engine='python')
+M3 = pd.read_csv('./Output/NIST_Propane_20kW_GEOM_Prescribed_1cm_cat_devc.csv', header=1, sep=' *, *', engine='python')
+
+fs1 = len(M1['Time'])/max(M1['Time'])
+fs2 = len(M2['Time'])/max(M2['Time'])
+fs3 = len(M3['Time'])/max(M3['Time'])
+
+x1 = M1['"w"'][M1['Time']>30.]
+x2 = M2['"w"'][M2['Time']>30.]
+x3 = M3['"w"'][M3['Time']>30.]
+
+f1, Pxx_den_1 = signal.periodogram(x1, fs1)
+f2, Pxx_den_2 = signal.periodogram(x2, fs2)
+f3, Pxx_den_3 = signal.periodogram(x3, fs3)
+
+# plot experimental result
+fpuff = 2.31
+funce = 0.10
+fmeas = np.array([fpuff, fpuff])
+PSDmeas = np.array([0., 5.])
+fh=macfp.plot_to_fig(fmeas, PSDmeas,
+                  plot_type='linear',
+                  x_min=0.5,x_max=4,y_min=0,y_max=15,
+                  x_label='frequency [Hz]',
+                  y_label='PSD [V**2/Hz]',
+                  line_style='--',
+                  line_width=2,
+                  line_color='black',
+                  institute_label='NIST',
+                  revision_label='MaCFP-3, Tsukuba, Japan',
+                  data_label='Exp',
+                  plot_title='NIST 37 cm 20 kW Propane Puffing Frequency',
+                  show_legend=True,
+                  legend_location='right')
+
+# add error to measuered puffing freq
+plt.fill_betweenx(PSDmeas, np.array([fpuff-funce, fpuff-funce]), np.array([fpuff+funce, fpuff+funce]), color='lightgrey', figure=fh)
+
+fh=macfp.plot_to_fig(f1, Pxx_den_1, plot_type='linear',x_min=0.5,x_max=4,y_min=0,y_max=6,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',data_label='FDS $\Delta x=4$ cm', line_style='-', line_width=1,line_color='black',  marker_style='o',marker_size=4,marker_edge_color='black', marker_fill_color='None',figure_handle=fh,show_legend=True,legend_location='center left')
+fh=macfp.plot_to_fig(f2, Pxx_den_2, plot_type='linear',x_min=0.5,x_max=4,y_min=0,y_max=6,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',data_label='FDS $\Delta x=2$ cm', line_style='-', line_width=1,line_color='magenta',marker_style='^',marker_size=4,marker_edge_color='magenta',marker_fill_color='None',figure_handle=fh,show_legend=True,legend_location='center left')
+fh=macfp.plot_to_fig(f3, Pxx_den_3, plot_type='linear',x_min=0.5,x_max=4,y_min=0,y_max=6,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',data_label='FDS $\Delta x=1$ cm', line_style='-.',line_width=1,line_color='red',marker_style='s',marker_size=4,marker_edge_color='red', marker_fill_color='None',figure_handle=fh,show_legend=True,legend_location='center left')
+
+print(f3[np.where(Pxx_den_3==Pxx_den_3.max())])
+
+# plt.show()
+
+plt.savefig('./Plots/NIST_37cm_20kW_Propane_puffing_frequency.pdf')
+
+# loglog spectrum
+fh2=macfp.plot_to_fig(f3, Pxx_den_3, plot_type='loglog',x_min=0.5,x_max=1000,y_min=.00001,y_max=100,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',plot_title='NIST 37 cm 20 kW Propane Power Spectrum',data_label='FDS $\Delta x=1$ cm',line_style='-', line_width=1,line_color='black',show_legend=True,legend_location='center right',legend_framealpha=1.,institute_label='NIST')
+macfp.plot_to_fig(f3, f3**(-5./3.),plot_type='loglog',x_min=0.5,x_max=1000,y_min=.00001,y_max=100,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',data_label='f**-5/3',line_style='--', line_width=2,line_color='black',show_legend=True,legend_location='center right',legend_framealpha=1.,figure_handle=fh2)
+fnyquist = np.array([0.5*fs3, 0.5*fs3])
+macfp.plot_to_fig(fnyquist, PSDmeas,plot_type='loglog',x_min=0.5,x_max=1000,y_min=.00001,y_max=100,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',data_label='f Nyquist',line_style='--', line_width=1,line_color='red',show_legend=True,legend_location='center right',legend_framealpha=1.,figure_handle=fh2)
+macfp.plot_to_fig(fmeas, PSDmeas,plot_type='loglog',x_min=0.5,x_max=1000,y_min=.00001,y_max=100,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',data_label='f puffing',line_style='--', line_width=1,line_color='green',show_legend=True,legend_location='center right',legend_framealpha=1.,figure_handle=fh2)
+
+# plt.show()
+
+plt.savefig('./Plots/NIST_37cm_20kW_Propane_Power_Spectrum.pdf')
diff --git a/...Fires/Computational_Results/2023/NIST/NIST_Pool_Fires_37cm_34kW_propane_power_spectrum.py b/...Fires/Computational_Results/2023/NIST/NIST_Pool_Fires_37cm_34kW_propane_power_spectrum.py
@@ -0,0 +1,76 @@
+# McDermott
+# 25 March 2021
+# power_spectrum.py
+
+import sys
+# sys.path.append('<path to macfp-db>/macfp-db/Utilities/')
+sys.path.append('../../../../../../macfp-db/Utilities/')
+
+import macfp
+import importlib
+importlib.reload(macfp)
+import matplotlib.pyplot as plt
+from scipy import signal
+import pandas as pd
+import numpy as np
+
+# get the model results
+M1 = pd.read_csv('./Output/NIST_Propane_34kW_GEOM_Prescribed_2cm_cat_devc.csv', header=1, sep=' *, *', engine='python')
+M2 = pd.read_csv('./Output/NIST_Propane_34kW_GEOM_Prescribed_1cm_cat_devc.csv', header=1, sep=' *, *', engine='python')
+M3 = pd.read_csv('./Output/NIST_Propane_34kW_GEOM_Prescribed_p5cm_cat_devc.csv', header=1, sep=' *, *', engine='python')
+
+fs1 = len(M1['Time'])/max(M1['Time'])
+fs2 = len(M2['Time'])/max(M2['Time'])
+fs3 = len(M3['Time'])/max(M3['Time'])
+
+x1 = M1['"w"'][M1['Time']>30.]
+x2 = M2['"w"'][M2['Time']>30.]
+x3 = M3['"w"'][M3['Time']>30.]
+
+f1, Pxx_den_1 = signal.periodogram(x1, fs1)
+f2, Pxx_den_2 = signal.periodogram(x2, fs2)
+f3, Pxx_den_3 = signal.periodogram(x3, fs3)
+
+# plot experimental result
+fpuff = 2.31
+funce = 0.10
+fmeas = np.array([fpuff, fpuff])
+PSDmeas = np.array([0., 1.5])
+fh=macfp.plot_to_fig(fmeas, PSDmeas,
+                  plot_type='linear',
+                  x_min=0.5,x_max=4,y_min=0,y_max=15,
+                  x_label='frequency [Hz]',
+                  y_label='PSD [V**2/Hz]',
+                  line_style='--',
+                  line_width=2,
+                  line_color='black',
+                  institute_label='NIST',
+                  revision_label='MaCFP-3, Tsukuba, Japan',
+                  data_label='Exp',
+                  plot_title='NIST 37 cm 34 kW Propane Puffing Frequency',
+                  show_legend=True,
+                  legend_location='right')
+
+# add error to measuered puffing freq
+plt.fill_betweenx(PSDmeas, np.array([fpuff-funce, fpuff-funce]), np.array([fpuff+funce, fpuff+funce]), color='lightgrey', figure=fh)
+
+fh=macfp.plot_to_fig(f1, Pxx_den_1, plot_type='linear',x_min=0.5,x_max=4,y_min=0,y_max=2,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',data_label='FDS $\Delta x=2$ cm', line_style='-', line_width=1,line_color='black',  marker_style='o',marker_size=4,marker_edge_color='black', marker_fill_color='None',figure_handle=fh,show_legend=True,legend_location='center left')
+fh=macfp.plot_to_fig(f2, Pxx_den_2, plot_type='linear',x_min=0.5,x_max=4,y_min=0,y_max=2,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',data_label='FDS $\Delta x=1$ cm', line_style='-', line_width=1,line_color='magenta',marker_style='^',marker_size=4,marker_edge_color='magenta',marker_fill_color='None',figure_handle=fh,show_legend=True,legend_location='center left')
+fh=macfp.plot_to_fig(f3, Pxx_den_3, plot_type='linear',x_min=0.5,x_max=4,y_min=0,y_max=2,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',data_label='FDS $\Delta x=0.5$ cm', line_style='-.',line_width=1,line_color='red',marker_style='s',marker_size=4,marker_edge_color='red', marker_fill_color='None',figure_handle=fh,show_legend=True,legend_location='center left')
+
+print(f3[np.where(Pxx_den_3==Pxx_den_3.max())])
+
+# plt.show()
+
+plt.savefig('./Plots/NIST_37cm_34kW_Propane_puffing_frequency.pdf')
+
+# loglog spectrum
+fh2=macfp.plot_to_fig(f3, Pxx_den_3, plot_type='loglog',x_min=0.5,x_max=1000,y_min=.00001,y_max=100,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',plot_title='NIST 37 cm 34 kW Propane Power Spectrum',data_label='FDS $\Delta x=0.5$ cm',line_style='-', line_width=1,line_color='black',show_legend=True,legend_location='center right',legend_framealpha=1.,institute_label='NIST')
+macfp.plot_to_fig(f3, f3**(-5./3.),plot_type='loglog',x_min=0.5,x_max=1000,y_min=.00001,y_max=100,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',data_label='f**-5/3',line_style='--', line_width=2,line_color='black',show_legend=True,legend_location='center right',legend_framealpha=1.,figure_handle=fh2)
+fnyquist = np.array([0.5*fs3, 0.5*fs3])
+macfp.plot_to_fig(fnyquist, PSDmeas,plot_type='loglog',x_min=0.5,x_max=1000,y_min=.00001,y_max=100,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',data_label='f Nyquist',line_style='--', line_width=1,line_color='red',show_legend=True,legend_location='center right',legend_framealpha=1.,figure_handle=fh2)
+macfp.plot_to_fig(fmeas, PSDmeas,plot_type='loglog',x_min=0.5,x_max=1000,y_min=.00001,y_max=100,x_label='frequency [Hz]',y_label='PSD [V**2/Hz]',data_label='f puffing',line_style='--', line_width=1,line_color='green',show_legend=True,legend_location='center right',legend_framealpha=1.,figure_handle=fh2)
+
+# plt.show()
+
+plt.savefig('./Plots/NIST_37cm_34kW_Propane_Power_Spectrum.pdf')