An energy-based formulation for soft-bodied virtual creatures
A curated collection of Python examples for optimization-based solid simulation, emphasizing algorithmic convergence, penetration-free, and inversion-free conditions, designed for readability and understanding.
Using Physics-Informed Deep Learning (PIDL) techniques (W-PINNs-DE & W-PINNs) to solve forward and inverse hydrodynamic shock-tube problems and plane stress linear elasticity boundary value problems
[SIGGRAPH Asia 2022] Assemble Them All: Physics-Based Planning for Generalizable Assembly by Disassembly
The mdbook source of a free online book on the theory and algorithms of physics-based simulations. You are welcome to make contributions by submitting pull requests or directly contacting the authors.
A curated set of C++ examples for optimization-based elastodynamic contact simulation using CUDA, emphasizing algorithmic convergence, penetration-free, and inversion-free conditions. Designed for readability and understanding, this tutorial helps beginners learn how to write simple GPU code for efficient solid simulations.
A free online book on the theory and algorithms of physics-based simulations. To make a contribution, please submit pull requests on the mdbook-src repository (not this one), or directly contact the authors.
Hookean springs in PyTorch
Numerical integration methods for mass-springs systems using PyTorch's autodiff
Knowledge hub to share and learn the state-of-the-art developments in computer graphics.
A Python package describing Stochastic Nucleation of Water in vials
Uses SFML for a compact physics simulation illustrating elastic collisions in C++.
A simple implementation of mass-spring system for cloth simulation in C++
A framework for physics-based rendering of underwater images using Mitsuba 0.6 This work is part of simulation work done in[1]. [1] Adi Vainiger, Yoav Y. Schechner, Tali Treibitz, Aviad Avni, and David S. Timor, "Optical wide-field tomography of sediment resuspension," Opt. Express 27, A766-A778 (2019) https://opg.optica.org/oe/abstract.cfm?uri=o
Source code used in simulations for the paper "A Framework for Automatic Behavior Generation in Multi-Function Swarms" accepted by Frontiers in Robotics and AI Oct. 2020.
PySB add-on providing utilities to add units to models and perform dimensional analysis.
CPSC 526 final project - fall 2017
Evolutionary algorithm research on a neural network physics-based car controller
Add a description, image, and links to the physics-based-simulation topic page so that developers can more easily learn about it.
To associate your repository with the physics-based-simulation topic, visit your repo's landing page and select "manage topics."