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1dbloodflowpinns

2d-3d-cnn

2d-sdf-net

This is a neural network approximating the two-dimensional signed distance functions of polygons.

airfoil-gcnn

Graph Convolutional Networks for Unstructured Flow Fields

an-improved-pinns-with-the-adaptive-weight-sampling-and-de-algorithm

An improved and generic PINNs for fluid dynamic analysis is proposed. This approach incorporates three key improvements: residual-based adaptive sampling, which automatically samples points in areas with larger residuals; adaptive loss weights, which balance the loss terms effectively; and the utilization of the DE optimization algorithm

assessment-of-hybrid-dl-rom

POD-RNN and CRAN

attnpinn-for-rul-estimation

A Framework for Remaining Useful Life Prediction Based on Self-Attention and Physics-Informed Neural Networks

cann

Constitutive Artificial Neural Networks (CANNs) for modeling of hyperelastic materials

causalpinns

cfd101

💧CFD(计算流体力学)资料汇总、学习笔记，欢迎补充...

chatpaper

Use ChatGPT to summarize the arXiv papers. 全流程加速科研，利用chatgpt进行论文总结+润色+审稿+审稿回复

cnn_spallart_allmaras

Turbulent viscosity field prediction using convolution neural networks

cnnforcfd

This folder contains a sample code for the use of convolutional neural network for fluid force prediction of bluff body flows.

computational-fluid-dynamics-machine-learning-examples

This repo contains some tutorial type programs showing some basic ways machine learning can be applied to CFD.

computational-physics-and-machine-learning-reading-list

A list of papers relating Computational Physics and Machine Learning

conservative_pinns

We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation property of cPINN is obtained by enforcing the flux continuity in the strong form along the sub-domain interfaces.

coord-trans-encoding

This is the source code for our paper "Towards high-accuracy deep learning inference of compressible turbulent flows over aerofoils"

cvpr2023-papers-with-code

CVPR 2023 论文和开源项目合集

deep-flow-prediction

A framework for fluid flow (Reynolds-averaged Navier Stokes) predictions with deep learning

deep-learning-for-indentation

Extraction of mechanical properties of materials through deep learning from instrumented indentation

deep_plates

Physics-guided neural network framework for elastic plates

deeplstm

Deep LSTM for highly nonlinear system modeling

deepsdf

Learning Continuous Signed Distance Functions for Shape Representation

deepviv

Deep Learning of Vortex Induced Vibrations

diffusion-based-fluid-super-resolution

PyTorch implementation of the diffusion-based method for CFD data super-resolution proposed in the paper "A Physics-informed Diffusion Model for High-fidelity Flow Field Reconstruction".

eqdiscovery

Physics-informed learning of governing equations from scarce data

finnet

codes for FinNet: Finite Difference Network for solving differential equations

fluid-engine-dev

Fluid simulation engine for computer graphics applications

fourier_neural_operator

Use Fourier transform to learn operators in differential equations.

galerkin-transformer

[NeurIPS 2021] Galerkin Transformer: a linear attention without softmax