Going with the Flow

Yousuf Soliman, Marcel Padilla, Oliver Gross, Felix Knöppel, Ulrich Pinkall, Peter Schröder Given a sequence of poses of a body we study the motion resulting when the body is immersed in a (possibly) moving, incompressible medium. With the poses given, say, by an animator, the governing second-order ordinary differential equations are those of a rigid […]

Neural Monte Carlo Fluid Simulation

Pranav Jain, Peter Yichen Chen, Ziyin Qu, Oded Stein The idea of using a neural network to represent continuous vector fields (i.e., neural fields) has become popular for solving PDEs arising from physics simulations. Here, the classical spatial discretization (e.g., finite difference) of PDE solvers is replaced with a neural network that models a differentiable […]

Velocity-Based Monte Carlo Fluids

Ryusuke Sugimoto, Christopher Batty, Toshiya Hachisuka We present a velocity-based Monte Carlo fluid solver that overcomes the limitations of its existing vorticity-based counterpart. Because the velocity-based formulation is more commonly used in graphics, our Monte Carlo solver can be readily extended with various techniques from the fluid simulation literature. We derive our method by solving […]

Kinetic Simulation of Turbulent Multifluid Flows

Wei Li, Kui Wu, Mathieu Desbrun Despite its visual appeal, the simulation of separated multiphase flows (i.e., streams of fluids separated by interfaces) faces numerous challenges in accurately reproducing complex behaviors such as guggling, wetting, or bubbling. These difficulties are especially pronounced for high Reynolds numbers and large density variations between fluids, most likely explaining […]

Lightning-fast Method of Fundamental Solutions

Jiong Chen, Florian Schäfer, Mathieu Desbrun The method of fundamental solutions (MFS) and its associated boundary element method (BEM) have gained popularity in computer graphics due to the reduced dimensionality they offer: for three-dimensional linear problems, they only require variables on the domain boundary to solve and evaluate the solution throughout space, making them a […]

SIGGRAPH North America 2024

Physically-based analytical erosion for fast terrain generation

Petros Tzathas, Boris Gailleton, Philippe Steer, Guillaume Cordonnier Terrain generation methods have long been divided between procedural and physically-based. Procedural methods build upon the fast evaluation of a mathematical function but suffer from a lack of geological consistency, while physically-based simulation enforces this consistency at the cost of thousands of iterations unraveling the history of […]

Neural Garment Dynamics via Manifold-Aware Transformers

Peizhuo Li, Tuanfeng Y. Wang, Timur Levent Kesdogan, Duygu Ceylan, Olga Sorkine-Hornung Data driven and learning based solutions for modeling dynamic garments have significantly advanced, especially in the context of digital humans. However, existing approaches often focus on modeling garments with respect to a fixed parametric human body model and are limited to garment geometries […]

Monte Carlo Vortical Smoothed Particle Hydrodynamics for Simulating Turbulent Flows

Xingyu Ye, Xiaokun Wang, Yanrui Xu, Jirí Kosinka, Alexandru C. Telea, Lihua You, Jian Jun Zhang, Jian Chang For vortex particle methods relying on SPH-based simulations, the direct approach of iterating all fluid particles to capture velocity from vorticity can lead to a significant computational overhead during the Biot-Savart summation process. To address this challenge, […]

The Impulse Particle-In-Cell Method

Sergio Sancho, Jingwei Tang, Christopher Batty, Vinicius Azevedo An ongoing challenge in fluid animation is the faithful preservation of vortical details, which impacts the visual depiction of flows. We propose the Impulse Particle-In-Cell (IPIC) method, a novel extension of the popular Affine Particle-In-Cell (APIC) method that makes use of the impulse gauge formulation of the […]