Physics simulation methods explained for graphics and animation
Simulation Methods for Multiphysics Phenomena in Visual Computing
Graphics
Summary
Simulating how things like fluids, solids, and grains move and interact can be really complex, especially when they affect each other in different ways. The authors describe a variety of methods used in computer graphics to mimic these behaviors realistically. They explain the math behind these techniques, how different materials are modeled, and how multiple types of physical phenomena can be combined. They also highlight software that already supports these simulations and mention new trends like using machine learning to improve animations.
What this means in practice
- •For computer graphics developers: Use comprehensive multiphysics simulation methods to create realistic animations of interacting materials in games or visual effects.
- •For virtual reality builders: Integrate physically accurate models of fluids and deformable objects to enhance immersion in virtual environments.
A survey. It maps existing work.
Authors
Fabian Löschner, Stefan Rhys Jeske, José Antonio Fernández-Fernández, Jan Bender
Abstract
Physics simulation is a cornerstone of many computer graphics applications, ranging from video games and virtual reality to visual effects and computational design. The number of techniques for physically-based modeling and animation has thus skyrocketed over the past few decades, facilitating the simulation of a wide variety of materials and physical phenomena. These course notes provide an in-depth introduction to multiphysics simulation methods for computer graphics, covering the mathematical foundations, key algorithms, and practical considerations behind the most widely used approaches. We focus on methods developed by the computer graphics community for simulating various physical phenomena and materials -- including rigid and deformable bodies, fluids, and granular materials -- as well as the interactions between them. For each method, we present the underlying mathematical framework with detailed derivations and discuss how different materials and coupling strategies fit into the formulation. A selection of software frameworks that offer out-of-the-box multiphysics modeling capabilities is also presented. Finally, we touch on emerging trends in physics-based animation, including machine learning-based methods which have become increasingly popular in recent years.