zonexo's Stars
erdc/aa_autoencoder_mca
Supporting code for "reduced order modeling using advection-aware autoencoders"
arashsaber/Deep-Convolutional-AutoEncoder
This is a tutorial on creating a deep convolutional autoencoder with tensorflow.
Seratna/TensorFlow-Convolutional-AutoEncoder
This is an implementation of Convolutional AutoEncoder using only TensorFlow
plasma-umass/scalene
Scalene: a high-performance, high-precision CPU, GPU, and memory profiler for Python with AI-powered optimization proposals
kazutotess/ML-ROM_Various_Shapes
This repository contains the simple source codes of "Machine-learning-based reduced-order modeling for unsteady flows around bluff bodies of various shapes"
mjecke/pyfrontal
A fast method for approximating frontal area projection from an STL mesh for vehicle aero/CFD calculations.
nathanrooy/p-area
The easiest way to compute the frontal/projected area of an STL geometry file. Useful for aerodynamic/CFD applications.
wiewel/LatentSpacePhysics
Towards Learning the Temporal Evolution of Fluid Flow
harsha070/Reconstruction-of-Flows
Super resolution reconstruction in computational fluid dynamics. Proposed a novel autoencoder architecture to improve over existing results.
thunil/Deep-Flow-Prediction
A framework for fluid flow (Reynolds-averaged Navier Stokes) predictions with deep learning
mdribeiro/DeepCFD
DeepCFD: Efficient Steady-State Laminar Flow Approximation with Deep Convolutional Neural Networks
LionelAgo/Vortex_AE
Exploit Auto-encoder for exploring and predict flow dynamic
kfukami/CNN-SINDy-MLROM
Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.
opaliss/dmd_autoencoder
Enhancing Dynamic Mode Decomposition using Autoencoder Networks.
JRice15/physics-informed-autoencoders
Research project conducted at Pacific Northwest National Laboratory, exploring the use of physics-informed autoencoders to predict fluid flow dynamics
cfl-minds/twin_autoencoder
A twin auto-encoder structure for flow prediction with built-in outlier detection and uncertainty prediction
salehisaeed/semiImplicitSlip
benmoseley/FBPINNs
Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs)
smenon/dynamicTopoFvMesh
Parallel Adaptive Simplical Remeshing for OpenFOAM
linuxguy123/30P-30N-Validation-Case
A multi element airfoil validation case for meshing and OpenFOAM
dvucinic/cfMesh-external-aerodynamics
Exploration of external aerodynamic simulations with cfMesh and OpenFOAM
kakkapriyesh/AE-ConvLSTM-Flow-Dynamics
This repository contains an Auto-encoder ConvLSTM network (Pytorch) which can be used to predict a large number of time steps (100+). The network prediction is sequence-to-sequence which works well to predict 5 to 10-time steps in one pass through the neural network. The network is trained for unsteady fluid simulations using data. Another training method tested is the physics constraint method, where governing equations of fluid motion are used to optimize loss. Few attempts to train unsteady Navier-Stokes are made, but it dint work.
airshaper/adaptive-mesh-refinement
OpenFoam® motorBike case with adaptive volume & surface mesh refinement based on curl(U) or grad(p)
venturi123/DRLinFluids-examples
nschloe/meshio
:spider_web: input/output for many mesh formats
venturi123/DRLinFluids
An open-source Python platform of coupling deep reinforcement learning and OpenFOAM
DonsetPG/fenics-DRL
Repository from the paper https://arxiv.org/abs/1908.04127, to train Deep Reinforcement Learning in Fluid Mechanics Setup.
sahilgupta2105/Deep-Reinforcement-Learning
This repository contains code for simulating coupled motion of rigid ball and fluid in 2D and this is used as an environment in Gym to train a controller to balance the ball in air.
jerabaul29/Cylinder2DFlowControlDRLParallel
Parallelizing DRL for Active Flow control
perillamint/amazfit-bip-cjk-font
FontROM builder for Xiaomi Amazfit Bip