AnuGA for the simulation of the shallow water equation
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Updated
Apr 21, 2024 - Python
AnuGA for the simulation of the shallow water equation
A two-dimensional triangular mesh generator with pre- and post-processing utilities written in pure MATLAB (no toolboxes required, some support for Octave) designed specifically to build models that solve shallow-water equations or wave equations in a coastal environment (ADCIRC, FVCOM, WaveWatch3, SWAN, SCHISM, Telemac, etc.).
Curated list of some open source codes employing lattice Boltzmann methods
A parallel shallow water equations solver
Real time simulation and rendering of free surface fluid
A numerical CFD solver for the Shallow Water Equations
The TITAN2D toolkit is used for modeling of geophysical mass flows over natural terrain (volcanic flows, avalanches, landslides, ...).
GPU-comcot offloads the computational component on the outermost layer of COMCOT to Nvidia GPU. Currently, the speed up achieved by parallelized code on GTX-1060 comparing to serial one on AMD-FX8150 is nearly 200X. The code is still under development to fulfill the full functionality of the original model.
Discontinuous Galerkin FEM Runge-Kutta solver for hyperbolic systems of equations, in particular for shallow water equations.
Non-intrusive reduced order models using proper orthogonal decomposition (POD) and radial basis function (RBF) interpolation for shallow water equations
High-order finite volume solver for the shallow water equations
Structure-preserving numerical methods for dispersive shallow water models
🌊 Simple Finite Volumes models that solve the shallow water equations
Water wave models in one dimension
Implementation of Shallow Water Equations (works with Python 3.5 and Python 2.7)
Solve the 2D shallow water equations with a finite volume method based on a Q-scheme
A Deep Learning solver for the Shallow Water Equations
blitzdg is an open-source project aiming to implement parallel discontinuous Galerkin (dg) solvers for common partial differential equations systems using blitz++ for array and tensor manipulations and MPI for distributed parallelism.
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