Pinned Repositories
academicpages.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
aerodynamics
blade-geometry
Coordinates calculation for numerical flow investigation based on experimental data from Rotor 37.
cfd-gcn
CFL3D
CFL3D_ACC
a frame of CFL3D with OpenACC
CFL3D_Post
Compressible
Towards A Differentiable Solver
CSBook
Deep-Flow-Prediction
A framework for fluid flow (Reynolds-averaged Navier Stokes) predictions with deep learning
Hypersonichen's Repositories
Hypersonichen/CFL3D
Hypersonichen/academicpages.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
Hypersonichen/aerodynamics
Hypersonichen/blade-geometry
Coordinates calculation for numerical flow investigation based on experimental data from Rotor 37.
Hypersonichen/cfd-gcn
Hypersonichen/CFL3D_ACC
a frame of CFL3D with OpenACC
Hypersonichen/CFL3D_Post
Hypersonichen/Compressible
Towards A Differentiable Solver
Hypersonichen/CSBook
Hypersonichen/Deep-Flow-Prediction
A framework for fluid flow (Reynolds-averaged Navier Stokes) predictions with deep learning
Hypersonichen/DiffEqFlux.jl
Universal neural differential equations with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods
Hypersonichen/Grokking-Deep-Learning-with-Julia
Hypersonichen/machinelearninginaction
Source Code for the book: Machine Learning in Action published by Manning
Hypersonichen/MathematicsCapstone-NeuralODE
Hypersonichen/opensbli
A framework for the automated derivation and parallel execution of finite difference solvers on a range of computer architectures.
Hypersonichen/SimDL.github.io
Hypersonichen/Solver-in-the-Loop
Solver-in-the-Loop: Learning from Differentiable Physics to Interact with Iterative PDE-Solvers
Hypersonichen/spectralDNS
Spectral Navier Stokes (and similar) solvers in Python
Hypersonichen/StatsWithJuliaBook
Hypersonichen/SU2
SU2 Suite
Hypersonichen/xfoil-optimization-toolbox
The Python XFOIL optimization toolbox can be used to optimize airfoils for a specific operating range, and might be useful to you for its XFOIL communication module, airfoil parametrizations, and optimization algorithms, i.e. all you need to do funky stuff with 2D airfoils.