hwfluid's repositories
automatic_model_selection
Framework for selecting a suitable ML model given a specific problem
gplearn
Genetic Programming in Python, with a scikit-learn inspired API
DNNLESMODEL
This repository contains the python code, weight and bias matrices for the INU model
NASA_RUL_-CMAPS-
Remaining Useful Life (NASA CMAPS Dataset)
lesTools
A toolbox for the construction and assessment of subgrid-scale models for large-eddy simulations
tempoGAN
Source code for the SIGGRAPH paper "tempoGAN: A Temporally Coherent, Volumetric GAN for Super-resolution Fluid Flow"
mlflip
A quick implementation of MLFLIP
GAN_flownet
Use Generative Adversarial Networks to improve Steady-State-Flow-With-Neural-Nets
Deep-Learning-Turbulence-model
Use deep learning to learn a turbulence model from high fedelity data. The model can reasonably predict other turbulent flows.
Machine_Learning_Fluid_Dynamics
A curated list of awesome Machine Learning projects in Fluid Dynamics
turbulence-modeling-PIML
Data-driven Reynolds stress modeling with physics-informed machine learning
CNNforCFD
This folder contains a sample code for the use of convolutional neural network for fluid force prediction of bluff body flows.
CNN-for-Airfoil
CNN for airfoil lift-to-drag-ratio prediction
deep-fluids
Deep Fluids: A Generative Network for Parameterized Fluid Simulations
Deep-Flow-Prediction
A framework for fluid flow (Reynolds-averaged Navier Stokes) predictions with deep learning
rans-uncertainty
Uncertainty Quantification of RANS Data-Driven Turbulence Modeling
SmoothParticleNets
A set of custom deep network layers written in PyTorch to enable computation with unordered particle sets with an emphasis on fluid dynamics.
dscaptstone
Data Science Turbulence Capstone Repo
deep_flow_control
Source code for "Deep Dynamical Modeling and Control of Unsteady Fluid Flows" from NeurIPS 2018
Computational-Physics-and-Machine-Learning-Reading-List
A list of papers relating Computational Physics and Machine Learning
DeepEddy
Python code for "Applications of Deep Learning to Ocean Data Inference and Sub-Grid Parameterisation" (https://doi.org/10.1029/2018MS001472).
RUL-Net
Deep learning approach for estimation of Remaining Useful Life (RUL) of an engine
DeepVIV
Deep Learning of Vortex Induced Vibrations
Steady-State-Flow-With-Neural-Nets
A Tensorflow re-implementation of the paper Convolutional Neural Networks for Steady Flow Approximation
VortexFitting
Tools for detection, identification and fitting of vortices