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A .NET source generator for generating object mappings. No runtime reflection.
Build interactive console applications with .NET Razor and Spectre.Console
Microsoft BASIC for 6502 Microprocessor - Version 1.1
An improved chemistry integration module for OpenFOAM-10. It accelerates the chemistry solver but does not yet support tabulation or reduction methods. Only support ideal gas
An End-to-End CFD Agent with Domain-Specific Structured Thinking
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
Tool to add SSMS 21 to the list of targts for an existing VSIX file
High-Performance Symbolic Regression in Python and Julia
A lightweight and fast parsing library for C#.
Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey
Computational Fluid Dynamics framework for heterogeneous reacting flows
This is the gh-pages branch of the VTK Examples Web Site and is set up to host web pages.
Fierro is a C++ code designed to aid the research and development of numerical methods, testing of user-specified models, and creating multi-scale models related to quasi-static solid mechanics and…
ElsevierSoftwareX / SOFTX-D-20-00017
Forked from WENO-OF/WENOEXTWeighted essentially non-oscillatory library for the framework of OpenFOAM. To cite this software publication: https://www.sciencedirect.com/science/article/pii/S2352711020303241
A load-balanced chemistry model for OpenFOAM
Experiment with an AI-powered conversational editor
MatterSim: A deep learning atomistic model across elements, temperatures and pressures.
This project contains additional material for the textbook Deep Learning for Physics Research by Martin Erdmann, Jonas Glombitza, Gregor Kasieczka, and Uwe Klemradt.
Generate and edit PDF documents in your .NET applications using the open-source QuestPDF library and its C# Fluent API. Build invoices, reports and data exports with ease.
A flexible distributed key-value database that is optimized for caching and other realtime workloads.
RapidCFD is an OpenFOAM fork running fully on CUDA platform. Brought to you by
We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation property of cPINN is obtained by enforcing the flux continui…