13269252368 Goto Github PK

tensordiffeq

Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed computing

tetgen

This is a clone of "A Quality Tetrahedral Mesh Generator and a 3D Delaunay Triangulator" tetgen; Official website:

tetgen-1

A Python interface to the C++ TetGen library to generate tetrahedral meshes of any 3D polyhedral domains

tetsim

Javascript Tetrahedral FEM Simulation

three-3mj-viewer

Drag-and-drop preview for 3MJ models in WebGL using three.js.

three-mesh-ui

⏹ Make VR user interfaces for Three.js

three.js

JavaScript 3D library.

threecsg

tigl

The TiGL Geometry Library to process aircraft geometries in pre-design.

time-series-generator

The generator of artificial time series for testing purposes.

tinyfem

A software for Finite Element Method Calculation.refered code:VTK

tooptix

ToOptix is used for multiphysical topology optimization. There are different methods for combining structural, thermal, ... load cases.

topology-optimization-benchmark

topopt.jl

A WIP topology optimization package in pure Julia.

topopt.jl_wcsmo21

Demos and benchmarks for TopOpt.jl @WCSMO-21

topopt_in_petsc

topoptlevelset.jl

Level set method implementation using automatic differentiation.

topoptproblems.jl

A collection of standard topology optimisation problems.

torchuq

A library for uncertainty quantification based on PyTorch

tovtk

Python meshtal -> VTK converter

tsp

Travel Salesman Path (TSP) problem

ttk

TTK - Topological Data Analysis and Visualization - Source Code

ttk-data

TTK data examples

ttk-paraview

TTK's custom ParaView source tree

turbulucid

A Python package for visualising 2D CFD datasets.

tutorial-vtk-pyqt

Learn how to integrate vtk with pyqt in python

tutorial-vtk-python

Material for teaching vtk python

tutorials

Various tutorial cases for the coupling library preCICE with real solvers. These files are meant to be rendered on precice.org, so don't look at the README files here.

two-stage-stochastic-optimization

Minimizing costs in reservoir storage systems has been a challenging problem over the years. Several methods have been used previously to solve this problem. This paper would be considering the Two-Stage Stochastic Programming technique in solving this problem but the objective function would be a quadratic function. This function is the squared difference between release and the demand. Risk is also considered in solving this problem and the results are benchmarked against that of the Fletcher-Ponnambalam method. The results are also compared to that of the deterministic solution and the case of perfect information. The Two-Stage Stochastic Programming applied to a quadratic objective function gave promising results. As the number of scenarios increased, the optimal value approached that of the FP method. The stochastic solution from the TSP was shown to give 16.8% improvement in costs compared to the deterministic solution and the results of EVPI showed that getting perfect information for our problem would be highly beneficial leading to an 86.7% reduction in cost over time.

unidoe

R Package for Generating Uniform Design of Experiments