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12-steps-to-navier-stokes

Lorena A. Barba's "12 steps to Navier-Stokes", implemented with C++ & SDL 2.

academicpages.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

adv-intro-cfd-2012

Code for Advanced Intro to CFD class taught at Virginia Tech in Fall 2012

aeropython

Classical Aerodynamics of potential flow using Python and Jupyter Notebooks

basicopenfoamprogrammingtutorials

Introduces basic C++ concepts to beginner users of the OpenFOAM open-source CFD libraries.

cfd_julia

This repository contains fundamental codes related to CFD that can be included in any graduate level CFD coursework.

cfdofreactiveflows

Collection of codes in Matlab(R) and C++ for solving basic problems presented and discussed in the "Computational Fluid Dynamics of Reactive Flows" course (Politecnico di Milano)

cfdpython

A sequence of Jupyter notebooks featuring the "12 Steps to Navier-Stokes" http://lorenabarba.com/

chlorenz.github.io

Github Pages test page

colah.github.io

computational-fluid-dynamics

Selected MATLAB code I wrote while taking a CFD class in graduate school. Project descriptions are included.

cppns

Reimplementation of the 12 steps to Navier Stokes in C++, with Eigen and MathGL

cpraveen.github.io

Praveen Chandrashekar

deephpms

Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations

deeplearningtutorial

Tutorial on a number of topics in Deep Learning

deepturbulence

Deep Learning of Turbulent Scalar Mixing

deepviv

Deep Learning of Vortex Induced Vibrations

fbsnns

Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations

hfm

Hidden Fluid Mechanics

hpm

Hidden physics models: Machine learning of nonlinear partial differential equations

learn-python3

Jupyter notebooks for teaching/learning Python 3

linux_command_line

:computer: Introduction to Linux commands and Shell scripting

multistepnns

Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems

nmor

Deep learning framework for model reduction of dynamical systems

numerical-mooc

A course in numerical methods with Python for engineers and scientists: currently 5 learning modules, with student assignments.

openmp_c_12_steps_to_navier_stokes

Parallelization attempt to the “12 steps to Navier–Stokes” lessons using OpenMP/C

papers_open_source_softwares

pde_gp

Machine learning of linear differential equations using Gaussian processes

petibm

PetIBM - toolbox and applications of the immersed-boundary method on distributed-memory architectures

pinns

Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations