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Merged
merged 28 commits into from
May 4, 2025
Merged

update master #62

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0050ca3
initial commit
bigfooted Jan 4, 2025
7a683f1
small update
bigfooted Jan 6, 2025
aad5efe
regression
bigfooted Jan 15, 2025
2a28c0f
regression update
bigfooted Jan 17, 2025
f12a5cc
modify for regression test
bigfooted Jan 26, 2025
ea93d9c
modify for regression test
bigfooted Jan 26, 2025
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allow-run
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44a5ca1
change cores to 2
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c6f9d6c
change optimization
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change optimization
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n=0
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902b5e1
change optim.csv.ref
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move reference file
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b7bf654
add unsteady laminar cylinder
bigfooted Feb 1, 2025
2757349
Merge pull request #57 from su2code/design_pipe
pcarruscag Feb 1, 2025
85a3703
initial commit
bigfooted Feb 18, 2025
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remove duplicate files
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Merge branch 'develop' into tut_unst_cylinder
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change iterations
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Merge branch 'tut_unst_cylinder' of https://github.com/su2code/Tutori…
bigfooted Feb 26, 2025
11c5bb9
update iterations
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change screen output
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Merge branch 'tut_unst_cylinder' of https://github.com/su2code/Tutori…
bigfooted Feb 26, 2025
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sudo
pcarruscag Mar 1, 2025
60d11cd
Merge pull request #60 from su2code/corner_node
pcarruscag Mar 4, 2025
5791524
update paraview file
bigfooted Mar 7, 2025
95fe594
Merge pull request #58 from su2code/tut_unst_cylinder
bigfooted Mar 8, 2025
28b3a8a
Data-driven fluid modeling using physics-informed neural networks (#61)
EvertBunschoten Mar 26, 2025
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44 changes: 44 additions & 0 deletions compressible_flow/NICFD_nozzle/PhysicsInformed/0:generate_config.py
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###############################################################################################
# # _____ __ _____ ____ __ __ ____ # #
# # / ___// / / /__ \ / __ \____ _/ /_____ _/ |/ (_)___ ___ _____ # #
# # \__ \/ / / /__/ / / / / / __ `/ __/ __ `/ /|_/ / / __ \/ _ \/ ___/ # #
# # ___/ / /_/ // __/ / /_/ / /_/ / /_/ /_/ / / / / / / / / __/ / # #
# # /____/\____//____/ /_____/\__,_/\__/\__,_/_/ /_/_/_/ /_/\___/_/ # #
# # # #
###############################################################################################

############################# FILE NAME: 0:generate_config.py #################################
#=============================================================================================#
# author: Evert Bunschoten |
# :PhD Candidate , |
# :Flight Power and Propulsion |
# :TU Delft, |
# :The Netherlands |
# |
# |
# Description: |
# Generate configuration for defining a physics-informed neural network for modeling the |
# fluid properties of siloxane MM in NICFD with the data-driven fluid model in SU2. |
# |
# Version: 2.0.0 |
# |
#=============================================================================================#

from su2dataminer.config import Config_NICFD

# The fluid data for siloxane MM are generated with the CoolProp module using the Helmoltz
# equation of state.
fluid_name = "MM"
EoS_type = "HEOS"

Config = Config_NICFD()
Config.SetFluid(fluid_name)
Config.SetEquationOfState(EoS_type)

# Fluid data are generated on a density-energy grid rather than pressure-temperature.
Config.UsePTGrid(False)

# Display configuration settings and save config object.
Config.SetConfigName("SU2DataMiner_MM")
Config.PrintBanner()
Config.SaveConfig()
40 changes: 40 additions & 0 deletions compressible_flow/NICFD_nozzle/PhysicsInformed/1:generate_fluid_data.py
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###############################################################################################
# # _____ __ _____ ____ __ __ ____ # #
# # / ___// / / /__ \ / __ \____ _/ /_____ _/ |/ (_)___ ___ _____ # #
# # \__ \/ / / /__/ / / / / / __ `/ __/ __ `/ /|_/ / / __ \/ _ \/ ___/ # #
# # ___/ / /_/ // __/ / /_/ / /_/ / /_/ /_/ / / / / / / / / __/ / # #
# # /____/\____//____/ /_____/\__,_/\__/\__,_/_/ /_/_/_/ /_/\___/_/ # #
# # # #
###############################################################################################

########################### FILE NAME: 1:generate_fluid_data.py ###############################
#=============================================================================================#
# author: Evert Bunschoten |
# :PhD Candidate , |
# :Flight Power and Propulsion |
# :TU Delft, |
# :The Netherlands |
# |
# |
# Description: |
# Generate the single-phase fluid data for siloxane MM which is used to train the |
# physics-informed neural network. |
# |
# Version: 2.0.0 |
# |
#=============================================================================================#

from su2dataminer.config import Config_NICFD
from su2dataminer.generate_data import DataGenerator_CoolProp

# Load SU2 DataMiner configuration.
Config = Config_NICFD("SU2DataMiner_MM.cfg")

# Initiate data generator.
DG = DataGenerator_CoolProp(Config)
DG.PreprocessData()
DG.ComputeData()

# Visualize and save fluid data.
DG.VisualizeFluidData()
DG.SaveData()
53 changes: 53 additions & 0 deletions compressible_flow/NICFD_nozzle/PhysicsInformed/2:train_PINN.py
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###############################################################################################
# # _____ __ _____ ____ __ __ ____ # #
# # / ___// / / /__ \ / __ \____ _/ /_____ _/ |/ (_)___ ___ _____ # #
# # \__ \/ / / /__/ / / / / / __ `/ __/ __ `/ /|_/ / / __ \/ _ \/ ___/ # #
# # ___/ / /_/ // __/ / /_/ / /_/ / /_/ /_/ / / / / / / / / __/ / # #
# # /____/\____//____/ /_____/\__,_/\__/\__,_/_/ /_/_/_/ /_/\___/_/ # #
# # # #
###############################################################################################

################################ FILE NAME: 2:train_PINN.py ###################################
#=============================================================================================#
# author: Evert Bunschoten |
# :PhD Candidate , |
# :Flight Power and Propulsion |
# :TU Delft, |
# :The Netherlands |
# |
# |
# Description: |
# Initate physics-informed machine learning process for training the neural network used to |
# model the fluid properties of siloxane MM in NICFD with the SU2 data-driven fluid model. |
# |
# Version: 2.0.0 |
# |
#=============================================================================================#

from su2dataminer.config import Config_NICFD
from su2dataminer.manifold import TrainMLP_NICFD

# Load SU2 DataMiner configuration.
Config = Config_NICFD("SU2DataMiner_MM.cfg")

# Set learning rate parameters and define network architecture.
Eval = TrainMLP_NICFD(Config)

# Initial learning rate: 10^-3, learning rate decay parameter: 9.8787, mini-batch size: 2^6.
Eval.SetAlphaExpo(-3.0)
Eval.SetLRDecay(+9.8787e-01)
Eval.SetBatchExpo(6)

# Network architecture: two hidden layers with 12 nodes.
Eval.SetHiddenLayers([12,12])
# Hidden layer activation function: exp(x)
Eval.SetActivationFunction("exponential")
# Display training progress in the terminal.
Eval.SetVerbose(1)

# Initiate training process.
Eval.CommenceTraining()
Eval.TrainPostprocessing()

Config.UpdateMLPHyperParams(Eval)
Config.SaveConfig()
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