Differentiable Fluid Dynamics Package
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Updated
Jul 11, 2024 - Python
Differentiable Fluid Dynamics Package
High performance computational platform in Python for the spectral Galerkin method
Generative Adversarial Network (GAN) for physically realistic enrichment of turbulent flow fields
A synthetic, isotropic turbulence generator for constant density flows that enforces the discrete divergence-free condition.
Python implementation of Typhoon algorithm: dense estimation of 2D-3D optical flow on wavelet bases.
Post processing routines for analysing PTV data.
Multi-fidelity Generative Deep Learning Turbulent Flows
🌊 Framework for studying fluid dynamics with numerical simulations using Python (publish-only mirror). The main repo is hosted on https://foss.heptapod.net (Gitlab fork supporting Mercurial).
Simulation tool that utilises a Fourier domain adaptive optics model to enable rapid Monte Carlo characterisation of free space optical links between the Earth and satellites
This repository contains code to make a neural network that determines if an aircraft is flying through very turbulent, somewhat turbulent, or calm weather based on accelerometer readings. This also includes datasets and unlabeled data that requires processing to be used as datasets. The neural networks are written in Python, using Keras with Te…
ML-based turbulence modeling for astrophysics
Model of propagating blobs in 1D and 2D
Reproduction of main results of Computers & Fluids paper.
Code for the 1D vertical stochastic transport model of buoyant particles in the ocean described by Onink et al. (2022).
Patil, Aakash, et al. "Robust deep learning for emulating turbulent viscosities." Physics of Fluids 33.10 (2021): 105118.
Python Package for Statistical Analysis of Turbulence Data
Proof of principle implementation of a fully covariant filtering scheme for relativistic turbulence.
Postprocessing for turbulent channel flow
Applying a Multi-Layer Perceptron Deep Neural Network to predict Lift and Drag performance of airfoils
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