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dl-flow

Efficient Deep Learning Techniques for Multiphase Flow Simulation in Heterogeneous Porous Media

it_book

本项目收藏这些年来看过或者听过的一些不错的常用的上千本书籍，没准你想找的书就在这里呢，包含了互联网行业大多数书籍和面试经验题目等等。有人工智能系列（常用深度学习框架TensorFlow、pytorch、keras。NLP、机器学习，深度学习等等），大数据系列(Spark,Hadoop,Scala,kafka等)，程序员必修系列（C、C++、java、数据结构、linux，设计模式、数据库等等）

lbpm

Pore scale modelling

openlbmpm

openLBMPM is an open source lattice Boltzmann method (LBM) package for multicomponent and multiphase (MCMP) flow and transport in porous media. Currently, it includes Shan-Chen method and color gradient method for MCMP system. There are two options for Shan-Chen method: (1) Original Shan-Chen method, which integrates the force term to the equilibrium velocity and cannot reach high viscosity ratio; (2) Explicit forcing model developed by M.Porter et al (2012). For color gradient model, the methods developed by Liu et.al (2014), Huang et al (2014) and Takashi et al (2018) are included. For running the codes, CUDA and numba (from Anaconda) are required

packing-generation

Hard-sphere packing generation with the Lubachevsky–Stillinger, Jodrey–Tory, and force-biased algorithms and packing post-processing.

particleflow

Machine-learned, GPU-accelerated particle flow reconstruction

porousmediagan

Reconstruction of three-dimensional porous media using generative adversarial neural networks

pythontomatlab.py

储箱设计

quantum-carleman-lattice-boltzmann-simulation-of-fluids

This is a repository of the code accompanying "Quantum Carleman Lattice Boltzmann Simulation of Fluids". It implements the linear embedding introduced by Kowalski to describe nonlinear dynamics in terms of bosonic Hamiltonians.

rockflow

Generative flow models for creating porous media images

taichi-lbm