-
Notifications
You must be signed in to change notification settings - Fork 104
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Merge pull request #46 from su2code/develop
Develop
- Loading branch information
Showing
35 changed files
with
1,850 additions
and
84 deletions.
There are no files selected for viewing
141 changes: 141 additions & 0 deletions
141
compressible_flow/NICFD_nozzle/DataDriven/Generate_Dataset.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,141 @@ | ||
#!/usr/bin/env python | ||
|
||
## \file Generate_Dataset.py | ||
# \brief Example python script for generating training data for | ||
# data-driven fluid model in SU2 | ||
# \author E.C.Bunschoten | ||
# \version 7.5.1 "Blackbird" | ||
# | ||
# SU2 Project Website: https://su2code.github.io | ||
# | ||
# The SU2 Project is maintained by the SU2 Foundation | ||
# (http://su2foundation.org) | ||
# | ||
# Copyright 2012-2023, SU2 Contributors (cf. AUTHORS.md) | ||
# | ||
# SU2 is free software; you can redistribute it and/or | ||
# modify it under the terms of the GNU Lesser General Public | ||
# License as published by the Free Software Foundation; either | ||
# version 2.1 of the License, or (at your option) any later version. | ||
# | ||
# SU2 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 | ||
# Lesser General Public License for more details. | ||
# | ||
# You should have received a copy of the GNU Lesser General Public | ||
# License along with SU2. If not, see <http://www.gnu.org/licenses/>. | ||
|
||
# make print(*args) function available in PY2.6+, does'nt work on PY < 2.6 | ||
|
||
import CoolProp | ||
import numpy as np | ||
from tqdm import tqdm | ||
import csv | ||
|
||
# Name of the fluid in the CoolProp library. | ||
fluidName = 'Air' | ||
|
||
# Type of equation of state to be used by CoolProp. | ||
CP_eos = "HEOS" | ||
|
||
# Minimum and maximum dataset temperatures [K]. | ||
T_min = 280 | ||
T_max = 1000 | ||
|
||
# Minimum and maximum dataset pressures [Pa]. | ||
P_min = 5e4 | ||
P_max = 2e6 | ||
|
||
# Number of data points along each axis. | ||
Np_grid = 500 | ||
|
||
# Fraction of data points to be used as training data for MLP training (0-1). | ||
f_train = 0.8 | ||
|
||
# Fraction of data poins to be used as test data for MLP validation (0-1). | ||
f_test = 0.1 | ||
|
||
|
||
# Prepare data grid | ||
T_range = np.linspace(T_min, T_max, Np_grid) | ||
P_range = np.linspace(P_min, P_max, Np_grid) | ||
|
||
T_grid, P_grid = np.meshgrid(T_range, P_range) | ||
|
||
T_dataset = T_grid.flatten() | ||
P_dataset = P_grid.flatten() | ||
|
||
density_dataset = np.zeros(np.shape(T_dataset)) | ||
energy_dataset = np.zeros(np.shape(T_dataset)) | ||
s_dataset = np.zeros(np.shape(T_dataset)) | ||
dsde_dataset = np.zeros(np.shape(T_dataset)) | ||
dsdrho_dataset = np.zeros(np.shape(T_dataset)) | ||
d2sde2_dataset = np.zeros(np.shape(T_dataset)) | ||
d2sdedrho_dataset = np.zeros(np.shape(T_dataset)) | ||
d2sdrho2_dataset = np.zeros(np.shape(T_dataset)) | ||
|
||
# Evaluate CoolProp on data grid. | ||
fluid = CoolProp.AbstractState(CP_eos, fluidName) | ||
idx_failed_below = [] | ||
idx_failed_above = [] | ||
print("Generating CoolProp data set...") | ||
for i in tqdm(range(len(T_dataset))): | ||
try: | ||
fluid.update(CoolProp.PT_INPUTS, P_dataset[i], T_dataset[i]) | ||
|
||
density_dataset[i] = fluid.rhomass() | ||
energy_dataset[i] = fluid.umass() | ||
s_dataset[i] = fluid.smass() | ||
dsde_dataset[i] = fluid.first_partial_deriv(CoolProp.iSmass, CoolProp.iUmass, CoolProp.iDmass) | ||
dsdrho_dataset[i] = fluid.first_partial_deriv(CoolProp.iSmass, CoolProp.iDmass, CoolProp.iUmass) | ||
d2sde2_dataset[i] = fluid.second_partial_deriv(CoolProp.iSmass, CoolProp.iUmass, CoolProp.iDmass, CoolProp.iUmass, CoolProp.iDmass) | ||
d2sdedrho_dataset[i] = fluid.second_partial_deriv(CoolProp.iSmass, CoolProp.iUmass, CoolProp.iDmass, CoolProp.iDmass, CoolProp.iUmass) | ||
d2sdrho2_dataset[i] = fluid.second_partial_deriv(CoolProp.iSmass, CoolProp.iDmass, CoolProp.iUmass, CoolProp.iDmass, CoolProp.iUmass) | ||
except: | ||
idx_failed_below.append(i) | ||
print("CoolProp failed at temperature "+str(T_dataset[i]) + ", pressure "+str(P_dataset[i])) | ||
print("Done!") | ||
|
||
# Collect all data arrays and fill in failed data points. | ||
collected_data = np.vstack([density_dataset, | ||
energy_dataset, | ||
s_dataset, | ||
dsde_dataset, | ||
dsdrho_dataset, | ||
d2sde2_dataset, | ||
d2sdedrho_dataset, | ||
d2sdrho2_dataset]).T | ||
for i_failed in idx_failed_below: | ||
collected_data[i_failed, :] = 0.5*(collected_data[i_failed+1, :] + collected_data[i_failed-1, :]) | ||
|
||
# Shuffle data set and extract training, validation, and test data. | ||
np.random.shuffle(collected_data) | ||
np_train = int(f_train*len(density_dataset)) | ||
np_val = int(f_test*len(density_dataset)) | ||
np_test = len(density_dataset) - np_train - np_val | ||
|
||
train_data = collected_data[:np_train, :] | ||
dev_data = collected_data[np_train:(np_train+np_val), :] | ||
test_data = collected_data[(np_train+np_val):, :] | ||
|
||
# Write output files. | ||
with open(fluidName + "_dataset_full.csv", "w+") as fid: | ||
fid.write("Density,Energy,s,dsde_rho,dsdrho_e,d2sde2,d2sdedrho,d2sdrho2\n") | ||
csvWriter = csv.writer(fid,delimiter=',') | ||
csvWriter.writerows(collected_data) | ||
|
||
with open(fluidName + "_dataset_train.csv", "w+") as fid: | ||
fid.write("Density,Energy,s,dsde_rho,dsdrho_e,d2sde2,d2sdedrho,d2sdrho2\n") | ||
csvWriter = csv.writer(fid,delimiter=',') | ||
csvWriter.writerows(train_data) | ||
|
||
with open(fluidName + "_dataset_dev.csv", "w+") as fid: | ||
fid.write("Density,Energy,s,dsde_rho,dsdrho_e,d2sde2,d2sdedrho,d2sdrho2\n") | ||
csvWriter = csv.writer(fid,delimiter=',') | ||
csvWriter.writerows(dev_data) | ||
|
||
with open(fluidName + "_dataset_test.csv", "w+") as fid: | ||
fid.write("Density,Energy,s,dsde_rho,dsdrho_e,d2sde2,d2sdedrho,d2sdrho2\n") | ||
csvWriter = csv.writer(fid,delimiter=',') | ||
csvWriter.writerows(test_data) |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,131 @@ | ||
%!/usr/bin/env matlab | ||
|
||
%% \file LUTWriter.m | ||
% \brief Example MATLAB script for generating a look-up table file | ||
% compatible with the CDataDriven_Fluid class in SU2. | ||
% \author E.C.Bunschoten | ||
% \version 7.5.1 "Blackbird" | ||
% | ||
% SU2 Project Website: https://su2code.github.io | ||
% | ||
% The SU2 Project is maintained by the SU2 Foundation | ||
% (http://su2foundation.org) | ||
% | ||
% Copyright 2012-2023, SU2 Contributors (cf. AUTHORS.md) | ||
% | ||
% SU2 is free software; you can redistribute it and/or | ||
% modify it under the terms of the GNU Lesser General Public | ||
% License as published by the Free Software Foundation; either | ||
% version 2.1 of the License, or (at your option) any later version. | ||
% | ||
% SU2 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 | ||
% Lesser General Public License for more details. | ||
% | ||
% You should have received a copy of the GNU Lesser General Public | ||
% License along with SU2. If not, see <http://www.gnu.org/licenses/>. | ||
|
||
% make print(*args) function available in PY2.6+, does'nt work on PY < 2.6 | ||
|
||
% CoolProp input data file. | ||
input_datafile = "Air_dataset_full.csv"; | ||
|
||
% Data point frequency (the larger, the coarser the table). | ||
data_freq = 2; | ||
|
||
% LUT output file name. | ||
output_LUTfile = "reftable.drg"; | ||
|
||
%% provide import data file | ||
% space delimited | ||
data_ref = importdata(input_datafile); | ||
|
||
% Identify data entries | ||
rho = data_ref.data(1:data_freq:end, 1); | ||
e = data_ref.data(1:data_freq:end, 2); | ||
s = data_ref.data(1:data_freq:end, 3); | ||
ds_de = data_ref.data(1:data_freq:end, 4); | ||
ds_drho = data_ref.data(1:data_freq:end, 5); | ||
d2s_de2 = data_ref.data(1:data_freq:end, 6); | ||
d2s_dedrho = data_ref.data(1:data_freq:end, 7); | ||
d2s_drho2 = data_ref.data(1:data_freq:end, 8); | ||
|
||
rho_min = min(rho); | ||
rho_max = max(rho); | ||
e_min = min(e); | ||
e_max = max(e); | ||
|
||
% Normalize density and energy | ||
rho_norm = (rho - rho_min)/(rho_max - rho_min); | ||
e_norm = (e - e_min)/(e_max - e_min); | ||
|
||
%% Define table connectivity | ||
T = delaunayTriangulation(rho_norm, e_norm); | ||
|
||
data_LUT = [rho, e, s, ds_de, ds_drho, d2s_de2, d2s_dedrho, d2s_drho2]; | ||
|
||
[~, boundNodes] = boundaryFacets(alphaShape(rho_norm, e_norm, 0.05)); | ||
hullIDs = find(ismember([rho_norm, e_norm], boundNodes, "rows")); | ||
|
||
%% Write table data to output | ||
fid = fopen(output_LUTfile, 'w+'); | ||
|
||
header = ['Dragon library' newline newline]; | ||
|
||
header = [header '<Header>' newline]; | ||
|
||
header = [header '[Version]' newline '1.0.1' newline newline]; | ||
|
||
header = [header '[Number of points]' newline]; | ||
header = [header sprintf('%3d',length(rho)) newline newline]; | ||
|
||
header = [header '[Number of triangles]' newline]; | ||
header = [header sprintf('%3d',length(T.ConnectivityList)) newline newline]; | ||
|
||
header = [header '[Number of hull points]' newline]; | ||
header = [header sprintf('%3d',length(hullIDs)) newline newline]; | ||
|
||
header = [header '[Number of variables]' newline]; | ||
header = [header sprintf('%3d',8) newline newline]; | ||
|
||
header = [header '[Variable names]' newline]; | ||
header = [header sprintf('1:Density\n2:Energy\n3:s\n4:dsde_rho\n5:dsdrho_e\n6:d2sde2\n7:d2sdedrho\n8:d2sdrho2\n')]; | ||
|
||
header = [header newline '</Header>' newline newline]; | ||
header = [header '<Data>']; | ||
|
||
fprintf(fid,'%s', header); | ||
printformat = '\n'; | ||
for iTabVar=1:8 | ||
printformat = [printformat '%.14e\t']; | ||
end | ||
fprintf(fid,printformat,data_LUT'); | ||
fprintf(fid,'%s', newline); | ||
fprintf(fid,'%s', '</Data>'); | ||
|
||
fprintf(fid,'%s', newline); | ||
fprintf(fid,'%s', newline); | ||
fprintf(fid,'%s', '<Connectivity>'); | ||
|
||
printformat = ['\n' '%5i\t' '%5i\t' '%5i\t']; | ||
|
||
fprintf(fid,printformat,T.ConnectivityList'); | ||
|
||
fprintf(fid,'%s', newline); | ||
fprintf(fid,'%s', '</Connectivity>'); | ||
|
||
%% print hull block | ||
fprintf(fid,'%s', newline); | ||
fprintf(fid,'%s', newline); | ||
fprintf(fid,'%s', '<Hull>'); | ||
|
||
printformat = ['\n' '%5i\t']; | ||
|
||
fprintf(fid,printformat,hullIDs); | ||
|
||
fprintf(fid,'%s', newline); | ||
fprintf(fid,'%s', '</Hull>'); | ||
|
||
%% close .dat file | ||
fclose(fid); |
Oops, something went wrong.