Author Archives: christopherbatty

Implicit Position-Based Fluids

Elie Diaz, Jerry Hsu, Eisen Montalvo-Ruiz, Chris Giles, Cem Yuksel The efficient simulation of incompressible fluids remains a difficult and open problem. Prior works often make various tradeoffs between incompressibility, stability, and cost. Yet, it is rare to obtain all … Continue reading

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A Stack-Free Parallel ℎ-Adaptation Algorithm for Dynamically Balanced Trees on GPUs

Lixin Ren, Xiaowei He, Shusen Liu, Yuzhong Guo, Enhua Wu Prior research has demonstrated the efficacy of balanced trees as spatially adaptive grids for large-scale simulations. However, state-of-the-art methods for balanced tree construction are restricted by the iterative nature of … Continue reading

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Viscous Vortex Dynamics on Surfaces

Cuncheng Zhu, Hang Yin, Albert Chern We present a vorticity method for simulating incompressible viscous flows on curved surfaces governed by the Navier–Stokes equations. Unlike previous approaches, our formulation incorporates the often-overlooked Gaussian-curvature-dependent term in the viscous force, which influences … Continue reading

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FLAMEFORGE: Combustion Simulation of Wooden Structures

Daoming Liu, Jonathan Klein, Florian Rist, Wojtek Pałubicki, Sören Pirk, Dominik L. Michels We propose a unified volumetric combustion simulator that supports general wooden structures capturing the multi-phase combustion of charring materials. Complex geometric structures can conveniently be represented in … Continue reading

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Two-Pass Shock Propagation for Stable Stacking with Gauss–Seidel

Ziyan Xiong, Andrew Leach, Griffith Thomas, Shinjiro Sueda Rigid body simulators using the Gauss–Seidel method have been widely adopted for their simplicity, efficiency, and robustness. However, these methods struggle when simulating stable stacking with frictional contact because, unlike global methods, … Continue reading

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SIGGRAPH Asia 2025

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Fast Reconstruction of Implicit Surfaces Using Convolutional Neural Networks

Chen Zhao, Tamar Shinar, Craig Schroeder Recently, Zhao et al . [2024] proposed a new method for constructing signed distance functions from fluid simulation particles. This method was able to achieve superior surface smoothness, noise reduction, and temporal coherence compared … Continue reading

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Lifting the Winding Number: Precise Discontinuities in Neural Fields for Physics Simulation

Yue Chang, Mengfei Liu, Zhecheng Wang, Peter Yichen Chen, Eitan Grinspun Cutting thin-walled deformable structures is common in daily life, but poses significant challenges for simulation due to the introduced spatial discontinuities. Traditional methods rely on mesh-based domain representations, which … Continue reading

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Representing Flow Fields with Divergence-Free Kernels for Reconstruction

Xingyu Ni, Jingrui Xing, Xingqiao Li, Bin Wang, Baoquan Chen Accurately reconstructing continuous flow fields from sparse or indirect measurements remains an open challenge, as existing techniques often suffer from oversmoothing artifacts, reliance on heterogeneous architectures, and the computational burden … Continue reading

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Real-Time Triangle-SDF Continuous Collision Detection

Joël Pelletier-Guénette, Alexandre Mercier-Aubin, Sheldon Andrews We introduce an efficient solution to the problem of continuous collision detection (CCD) between triangle geometry and signed distance fields (SDFs). We formulate the triangle-SDF collision problem as a novel spatio-temporal local optimization that … Continue reading

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