Physics-Based Animation

Mohammad Sina Nabizadeh, Stephanie Wang, Ravi Ramamoorthi, Albert Chern

The animation of delicate vortical structures of gas and liquids has been of great interest in computer graphics. However, common velocity-based fluid solvers can damp the vortical flow, while vorticity-based fluid solvers suffer from performance drawbacks. We propose a new velocity-based fluid solver derived from a reformulated Euler equation using covectors. Our method generates rich vortex dynamics by an advection process that respects the Kelvin circulation theorem. The numerical algorithm requires only a small local adjustment to existing advection-projection methods and can easily leverage recent advances therein. The resulting solver emulates a vortex method without the expensive conversion between vortical variables and velocities. We demonstrate that our method preserves vorticity in both vortex filament dynamics and turbulent flows significantly better than previous methods, while also improving preservation of energy.

Covector Fluids

Cristian Romero, Dan Casas, Maurizio M. Chiaramonte, Miguel A. Otaduy

We propose a novel method to machine-learn highly detailed, nonlinear contact deformations for real-time dynamic simulation. We depart from previous deformation-learning strategies, and model contact deformations in a contact-centric manner. This strategy shows excellent generalization with respect to the object’s configuration space, and it allows for simple and accurate learning. We complement the contact-centric learning strategy with two additional key ingredients: learning a continuous vector field of contact deformations, instead of a discrete approximation; and sparsifying the mapping between the contact configuration and contact deformations. These two ingredients further contribute to the accuracy, efficiency, and generalization of the method. We integrate our learning-based contact deformation model with subspace dynamics, showing real-time dynamic simulations with fine contact deformation detail.

Contact-Centric Deformation Learning

Wojtek Pałubicki, Miłosz Makowski, Weronika Gajda, Torsten Hädrich, Dominik L. Michels, Sören Pirk

One of the greatest challenges to mankind is understanding the underlying principles of climate change. Over the last years, the role of forests in climate change has received increased attention. This is due to the observation that not only the atmosphere has a principal impact on vegetation growth but also that vegetation is contributing to local variations of weather resulting in diverse microclimates. The interconnection of plant ecosystems and weather is described and studied as ecoclimates. In this work we take steps towards simulating ecoclimates by modeling the feedback loops between vegetation, soil, and atmosphere. In contrast to existing methods that only describe the climate at a global scale, our model aims at simulating local variations of climate. Specifically, we model tree growth interactively in response to gradients of water, temperature and light. As a result, we are able to capture a range of ecoclimate phenomena that have not been modeled before, including geomorphic controls, forest edge effects, the Foehn effect and spatial vegetation patterning. To validate the plausibility of our method we conduct a comparative analysis to studies from ecology and climatology. Consequently, our method advances the state-of-the-art of generating highly realistic outdoor landscapes of vegetation.

Ecoclimates: Climate-Response Modeling of Vegetation

Yifei Li, Tao Du, Kui Wu, Jie Xu, Wojciech Matusik

Cloth simulation has wide applications in computer animation, garment design, and robot-assisted dressing. This work presents a differentiable cloth simulator whose additional gradient information facilitates cloth-related applications. Our differentiable simulator extends a state-of-the-art cloth simulator based on Projective Dynamics (PD) and with dry frictional contact. We draw inspiration from previous work to propose a fast and novel method for deriving gradients in PD-based cloth simulation with dry frictional contact. Furthermore, we conduct a comprehensive analysis and evaluation of the usefulness of gradients in contact-rich cloth simulation. Finally, we demonstrate the efficacy of our simulator in a number of downstream applications, including system identification, trajectory optimization for assisted dressing, closed-loop control, inverse design, and real-to-sim transfer. We observe a substantial speedup obtained from using our gradient information in solving most of these applications.

DiffCloth: Differentiable Cloth Simulation with Dry Frictional Contact

Han Shao, Libo Huang, Dominik L. Michels

Multigrid methods are quite efficient for solving the pressure Poisson equation in simulations of incompressible flow. However, for viscous liquids, geometric multigrid turned out to be less efficient for solving the variational viscosity equation. In this contribution, we present an Unsmoothed Aggregation Algebraic MultiGrid (UAAMG) method with a multi-color Gauss-Seidel smoother, which consistently solves the variational viscosity equation in a few iterations for various material parameters. Moreover, we augment the OpenVDB data structure with Intel SIMD intrinsic functions to perform sparse matrix-vector multiplications efficiently on all multigrid levels. Our framework is 2.0 to 14.6 times faster compared to the state-of-the-art adaptive octree solver in commercial software for the large-scale simulation of both non-viscous and viscous flow.

A Fast Unsmoothed Aggregation Algebraic Multigrid Framework for the Large-Scale Simulation of Incompressible Flow

Shiying Xiong, Zhecheng Wang, Mengdi Wang, Bo Zhu

We propose a novel Clebsch method to simulate the free-surface vortical flow. At the center of our approach lies a level-set method enhanced by a wave-function correction scheme and a wave-function extrapolation algorithm to tackle the Clebsch method’s numerical instabilities near a dynamic interface. By combining the Clebsch wave function’s expressiveness in representing vortical structures and the level-set function’s ability on tracking interfacial dynamics, we can model complex vortex-interface interaction problems that exhibit rich free-surface flow details on a Cartesian grid. We showcase the efficacy of our approach by simulating a wide range of new free-surface flow phenomena that were impractical for previous methods, including horseshoe vortex, sink vortex, bubble rings, and free-surface wake vortices.

A Clebsch method for free-surface vortical flow simulation

Georg Sperl, Rosa M. Sánchez-Banderas, Manwen Li, Chris Wojtan, Miguel A. Otaduy

This paper introduces a methodology for inverse-modeling of yarn-level mechanics of cloth, based on the mechanical response of fabrics in the real world. We compiled a database from physical tests of several different knitted fabrics used in the textile industry. These data span different types of complex knit patterns, yarn compositions, and fabric finishes, and the results demonstrate diverse physical properties like stiffness, nonlinearity, and anisotropy. We then develop a system for approximating these mechanical responses with yarn-level cloth simulation. To do so, we introduce an efficient pipeline for converting between fabric-level data and yarn-level simulation, including a novel swatch-level approximation for speeding up computation, and some small-but-necessary extensions to yarn-level models used in computer graphics.

Estimation of Yarn-Level Simulation Models for Production Fabrics

Marcel Padilla, Oliver Gross, Felix Knoppel, Albert Chern, Ulrich Pinkall, Peter Schroder

Simulation of stellar atmospheres, such as that of our own sun, is a common task in CGI for scientific visualization, movies and games. A fibrous volumetric texture is a visually dominant feature of the solar corona—the plasma that extends from the solar surface into space. These coronal fibers can be modeled as magnetic filaments whose shape is governed by the magnetohydrostatic equation. The magnetic filaments provide a Lagrangian curve representation and their initial configuration can be prescribed by an artist or generated from magnetic flux given as a scalar texture on the sun’s surface. Subsequently the shape of the filaments is determined based on a variational formulation. The output is a visual rendering of the whole sun. We demonstrate the fidelity of our method by comparing the resulting renderings with actual images of our sun’s corona.

Filament Based Plasma

Jerry Hsu, Nghia Truong,Cem Yuksel, Kui Wu

Initializing simulations of deformable objects involves setting the rest state of all internal forces at the rest shape of the object. However, often times the rest shape is not explicitly provided. In its absence, it is common to initialize by treating the given initial shape as the rest shape. This leads to sagging, the undesirable deformation under gravity as soon as the simulation begins. Prior solutions to sagging are limited to specific simulation systems and material models, most of them cannot handle frictional contact, and they require solving expensive global nonlinear optimization problems. We introduce a novel solution to the sagging problem that can be applied to a variety of simulation systems and materials. The key feature of our approach is that we avoid solving a global nonlinear optimization problem by performing the initialization in two stages. First, we use a global linear optimization for static equilibrium. Any nonlinearity of the material definition is handled in the local stage, which solves many small local problems efficiently and in parallel. Notably, our method can properly handle frictional contact orders of magnitude faster than prior work. We show that our approach can be applied to various simulation systems by presenting examples with mass-spring systems, cloth simulations, the finite element method, the material point method, and position-based dynamics.

A General Two-Stage Initialization for Sag-Free Deformable Simulations

Fresh new 2022 SIGGRAPH papers, coming in hot!

• Filament Based Plasma
• Estimation of Yarn-Level Simulation Models for Production Fabrics
• A Clebsch Method for Free-Surface Vortical Flow Simulation
• A Fast Unsmoothed Aggregation Algebraic Multigrid Framework for the Large-Scale Simulation of Incompressible Flow
• Ecoclimates: Climate-Response Modeling of Vegetation
• DiffCloth: Differentiable Cloth Simulation with Dry Frictional Contact
• A General Two-Stage Initialization for Sag-Free Deformable Simulations
• Contact-Centric Deformation Learning
• Covector Fluids
• Simulation and Optimization of Magnetoelastic Thin Shells
• A Moving Eulerian-Lagrangian Particle Method for Thin Film and Foam Simulation
• A GPU-Based Multilevel Additive Schwarz Preconditioner for Cloth and Deformable Body Simulation
• A Unified Newton Barrier Method for Multibody Dynamics
• The Power Particle-In-Cell Method
• Penetration-free Projective Dynamics on the GPU
• Affine Body Dynamics: Fast, Stable & Intersection-free Simulation of Stiff Materials
• Energetically Consistent Inelasticity for Optimization Time Integration
• Adaptive Rigidification of Elastic Solids
• Efficient Kinetic Simulation of Two-Phase Flows
• Go Green: General Regularized Green’s Functions for Elasticity
• Guided Bubbles and Wet Foam for Realistic Whitewater Simulation
• Implicit Neural Representation for Physics-driven Actuated Soft Bodies
• Loki: A Unified Multiphysics Simulation Framework for Production
• Unified Many-Worlds Browsing of Arbitrary Physics-Based Animations
• VEMPIC: Particle-in-polyhedron Fluid Simulation for Intricate Solid Boundaries
• Analytically Integratable Zero-Restlength Springs for Capturing Dynamic Modes Unrepresented by Quasistatic Neural Networks
• Compact Poisson Filters for Fast Fluid Simulation
• Automatic Quantization for Physics-based Simulation
• True Seams: Modeling Seams in Digital Garments
  

TOG:

• An Efficient B-Spline Lagrangian/Eulerian Method for Compressible Flow, Shock Waves, and Fracturing Solids
• Fine Wrinkling on Coarsely Meshed Thin Shells
• Simulating Brittle Fracture With Material Points
• Physics-based Combustion Simulation