Physics-Based Animation

• Learning Physics with a Hierarchical Graph Network
• Physically Based Shape Matching
• Fast Numerical Coarsening with Local Factorizations
• Stability Analysis of Explicit MPM
• Wassersplines for Neural Vector-Field Controlled Animation
• Voronoi Filters for Simulation Enrichment
• Differentiable Simulation for Outcome-Driven Orthognathic Surgery Planning
• High-Order Elasticity Interpolants for Microstructure Simulation
• Surface-Only Dynamic Deformables using a Boundary Element Method
• A Second Order Cone Programming Approach for Simulating Biphasic Materials
• A Second-Order Explicit Pressure Projection Method for Eulerian Fluid Simulation

Somehow I seem to have missed making a page for SCA 2021, so here it is!

• Coupling Friction with Visual Appearance
• Volume Preserving Simulation of Soft Tissue with Skin
• Fast Corotated Elastic SPH Solids with Implicit Zero-Energy Mode Control
• Neural UpFlow: A Scene Flow Learning Approach to Increase the Apparent Resolution of Particle-Based Liquids
• Visual Simulation of Soil-Structure Destruction with Seepage Flows
• Particle Merging-and-Splitting (TVCG Talk)

A. Bernardin, E. Coevoet, P.G. Kry, S. Andrews, C. Duriez, and M. Marchal

In this paper, we propose a physics-based model of suction phenomenon to achieve simulation of deformable objects like suction cups. Our model uses a constraint-based formulation to simulate the variations of pressure inside suction cups. The respective internal pressures are represented as pressure constraints which are coupled with anti-interpenetration and friction constraints. Furthermore, our method is able to detect multiple air cavities using information from collision detection. We solve the pressure constraints based on the ideal gas law while considering several cavity states. We test our model with a number of scenarios reflecting a variety of uses, for instance, a spring loaded jumping toy, a manipulator performing a pick and place task, and an octopus tentacle grasping a soda can. We also evaluate the ability of our model to reproduce the physics of suction cups of varying shapes, lifting objects of different masses, and sliding on a slippery surface. The results show promise for various applications such as the simulation in soft robotics and computer animation.

Constraint-based Simulation of Passive Suction Cups

Purvi Goel, Doug L. James

Manually tuning physics-based animation parameters to explore a simulation outcome space or achieve desired motion outcomes can be notoriously tedious. Unfortunately, this problem has motivated many sophisticated and specialized optimization-based methods for fine-grained (keyframe) control, each of which are typically limited to specific animation phenomena, usually complicated, and, unfortunately, not widely used. In this paper, we propose Unified Many-Worlds Browsing (UMWB), a practical method for sample-level control and exploration of arbitrary physics-based animations. Our approach supports browsing of large simulation ensembles of arbitrary animation phenomena by using a unified volumetric WorldPack representation based on spatiotemporally compressed voxel data associated with geometric occupancy and other low-fidelity animation state. Beyond memory reduction, the WorldPack representation also enables unified query support for interactive browsing: it provides fast evaluation of approximate spatiotemporal queries, such as occupancy tests that find ensemble samples (“worlds”) where material is either IN or NOT IN a user-specified spacetime region. The WorldPack representation also supports real-time hardware-accelerated voxel rendering by exploiting the spatially hierarchical and temporal RLE raster data structure to accelerate GPU ray tracing of compressed animations. Our UMWB implementation supports interactive browsing (and offline refinement) of ensembles containing thousands of simulation samples, and fast spatiotemporal queries and ranking. We show UMWB results using a wide variety of different physics-based animation phenomena—not just Jell-O.

Unified Many Worlds Browsing of Arbitrary Physics-Based Animations

Joel Wretborn, Sean Flynn, Alexey Stomakhin

We present a method for enhancing fluid simulations with realistic bubble and foam detail. We treat bubbles as discrete air particles, two-way coupled with a sparse volumetric Euler flow, as first suggested in [Stomakhin et al. 2020]. We elaborate further on their scheme and introduce a bubble inertia correction term for improved convergence. We also show how one can add bubbles to an already existing fluid simulation using our novel guiding technique, which performs local re-simulation of fluid to achieve more interesting bubble dynamics through coupling. As bubbles reach the surface, they are converted into foam and simulated separately. Our foam is discretized with smoothed particle hydrodynamics (SPH), and we replace forces normal to the fluid surface with a fluid surface manifold advection constraint to achieve more robust and stable results. The SPH forces are derived through proper constitutive modeling of an incompressible viscous liquid, and we explain why this choice is appropriate for “wet” types of foam. This allows us to produce believable dynamics from close-up scenarios to large oceans, with just a few parameters that work intuitively across a variety of scales. Additionally, we present relevant research on air entrainment metrics and bubble distributions that have been used in this work.

Guided Bubbles and Wet Foam for Realistic Whitewater Simulation

Linxu Fan, Lloyd M. Chitalu, Taku Komura

Large-scale topological changes play a key role in capturing the fine debris of fracturing virtual brittle material. Real-world, tough brittle fractures have dynamic branching behaviour but numerical simulation of this phenomena is notoriously challenging. In order to robustly capture these
visual characteristics, we simulate brittle fracture by combining elastodynamic continuum mechanical models with rigid-body methods: A continuum damage mechanics (CDM) problem is solved, following rigid-body impact, to simulate crack propagation by tracking a damage field. We combine the result of this elastostatic continuum model with a novel technique to approximate cracks as a non-manifold mid-surface, which enables accurate and robust modelling of material fragment volumes to compliment fast-and-rigid shatter effects. For enhanced realism, we add fracture detail, incorporating particle damage-time to inform localised perturbation of the crack surface with artistic control. We evaluate our method with numerous examples and comparisons, showing that it produces a breadth of brittle material fracture effects and with low simulation resolution to require much less time compared to fully elastodynamic simulations.

Simulating Brittle Fracture with Material Points

Zhen Chen, Hsiao-yu Chen, Danny M Kaufman, Mélina Skouras, Etienne Vouga

We propose a new model and algorithm to capture the high-definition statics of thin shells via coarse meshes. This model predicts global, fine-scale wrinkling at frequencies much higher than the resolution of the coarse mesh; moreover, it is grounded in the geometric analysis of elasticity, and does not require manual guidance, a corpus of training examples, nor tuning of ad hoc parameters. We first approximate the coarse shape of the shell using tension field theory, in which material forces do not resist compression. We then augment this base mesh with wrinkles, parameterized by an amplitude and phase field that we solve for over the base mesh, which together characterize the geometry of the wrinkles. We validate our approach against both physical experiments and numerical simulations, and we show that our algorithm produces wrinkles qualitatively similar to those predicted by traditional shell solvers requiring orders of magnitude more degrees of freedom.

Fine Wrinkling on Coarsely Meshed Thin Shells

Michael Tao, Christopher Batty, Mirela Ben-Chen, Eugene Fiume, David I. W. Levin

The comprehensive visual modeling of fluid motion has historically been a challenging task, due in no small part to the difficulties inherent in geometries that are non-manifold, open, or thin. Modern geometric cut-cell mesh generators have been shown to produce, both robustly and quickly, workable volumetric elements in the presence of these problematic geometries, and the resulting volumetric representation would seem to offer an ideal infrastructure with which to perform fluid simulations. However, cut-cell mesh elements are general polyhedra that often contain holes and are non-convex; it is therefore difficult to construct the explicit function spaces required to employ standard functional discretizations, such as the Finite Element Method. The Virtual Element Method (VEM) has recently emerged as a functional discretization that successfully operates with complex polyhedral elements through a weak formulation of its function spaces. We present a novel cut-cell fluid simulation framework that exactly represents boundary geometry during the simulation. Our approach enables, for the first time, detailed fluid simulation with “in-the-wild” obstacles, including ones that contain non-manifold parts, self-intersections, and extremely thin features. Our key technical contribution is the generalization of the Particle-In-Cell fluid simulation methodology to arbitrary polyhedra using VEM. Coupled with a robust cut-cell generation scheme, this produces a fluid simulation algorithm that can operate on previously infeasible geometries without requiring any additional mesh modification or repair.

VEMPIC: Particle-in-Polyhedron Fluid Simulation for Intricate Solid Boundaries

Alejandro Rodriguez, Gabriel Cirio

Seams play a fundamental role in the way a garment looks, fits, feels and behaves. Seams can have very different shapes and mechanical properties depending on how fabric is overlapped, folded and stitched together, with garment designers often choosing specific seam and stitch type combinations depending on the appearance and behavior they want for the garment. Yet, virtually all 3D CAD tools for fashion and visual effects ignore most of the visual and mechanical complexity of seams, and just treat them as joint edges, their simplest possible form, drastically limiting the fidelity of digital garments. In this paper, we present a method that models seams following their true, real-life construction. Each seam brings together and overlaps the fabric pieces to be sewn, folds the fabric according to the type of seam, and stitches the resulting assembly following the type of stitch. To avoid dealing with the complexities of folding in 3D space, we cast the problem into a sequence of simpler 2D problems where we can easily shape the seam and produce a result free of self-intersections, before lifting the folded geometry back to 3D space. We run a series of constrained optimizations to enforce spatial properties in these 2D settings, allowing us to treat asymmetric seams, gatherings and overlapping construction orders. Using a variety of common seams and stitches, we show how our approach substantially improves the visual appearance of full garments, for a better and more predictive digital replica.

True Seams: Modeling Seams in Digital Garments

Botao Wu, Zhendong Wang, Huamin Wang

In this paper, we wish to push the limit of real-time cloth and deformable body simulation to a higher level with 50K to 500K vertices, based on the development of a novel GPU-based multilevel additive Schwarz (MAS) preconditioner. Similar to other preconditioners under the MAS framework, our preconditioner naturally adopts multilevel and domain decomposition concepts. But contrary to previous works, we advocate the use of small, non-overlapping domains that can well explore the parallel computing power on a GPU. Based on this idea, we investigate and invent a series of algorithms for our preconditioner, including multilevel domain construction using Morton codes, low-cost matrix precomputation by one-way Gauss-Jordan elimination, and conflict-free symmetric-matrix-vector multiplication in runtime preconditioning. The experiment shows that our preconditioner is effective, fast, cheap to precompute and scalable with respect to stiffness and problem size. It is compatible with many linear and nonlinear solvers used in cloth and deformable body simulation with dynamic contacts, such as PCG, accelerated gradient descent and L-BFGS. On a GPU, our preconditioner speeds up a PCG solver by approximately a factor of four, and its CPU version outperforms a number of competitors, including ILU0 and ILUT.

A GPU-Based Multilevel Additive Schwarz Preconditioner for Cloth and Deformable Body Simulation