Month: September 2023

Wei Li, Tongtong Wang, Zherong Pan, Xifeng Gao, Kui Wu, Mathieu Desbrun

Kinetic solvers for incompressible fluid simulation were designed to run efficiently on massively parallel architectures such as GPUs. While these lattice Boltzmann solvers have recently proven much faster and more accurate than the macroscopic Navier-Stokes-based solvers traditionally used in graphics, it systematically comes at the price of a very large memory requirement: a mesoscopic discretization of statistical mechanics requires over an order of magnitude more variables per grid node than most fluid solvers in graphics. In order to open up kinetic simulation to gaming and simulation software packages on commodity hardware, we propose a High-Order Moment-Encoded Lattice-Boltzmann-Method solver which we coined HOME-LBM, requiring only the storage of a few moments per grid node, with little to no loss of accuracy in the typical simulation scenarios encountered in graphics. We show that our lightweight and lightspeed fluid solver requires three times less memory and runs ten times faster than state-of-the-art kinetic solvers, for a nearly-identical visual output.

High-Order Moment-Encoded Kinetic Simulation of Turbulent Flows

Xuan Li, Yu Fang, Lei Lan, Huamin Wang, Yin Yang, Minchen Li, Chenfanfu Jiang

We propose an efficient cloth simulation method that combines the merits of two drastically different numerical procedures, namely the subspace integration and parallelizable iterative relaxation. We show those two methods can be organically coupled within the framework of projective dynamics (PD), where both low- and high-frequency cloth motions are effectively and efficiently computed. Our method works seamlessly with the state-of-the-art contact handling algorithm, the incremental potential contact (IPC), to offer the non-penetration guarantee of the resulting animation. Our core ingredient centers around the utilization of subspace for the expedited convergence of Jacobi-PD. This involves solving the reduced global system and smartly employing its precomputed factorization. In addition, we incorporate a time-splitting strategy to handle the frictional self-contacts. Specifically, during the PD solve, we employ a quadratic proxy to approximate the contact barrier. The prefactorized subspace system matrix is exploited in a reduced-space LBFGS. The LBFGS method starts with the reduced system matrix of the rest shape as the initial
Hessian approximation, incorporating contact information into the reduced system progressively, while the full-space Jacobi iteration captures high-frequency details. Furthermore, we address penetration issues through a penetration correction step. It minimizes an incremental potential without elasticity using Newton-PCG. Our method can be efficiently executed on modern GPUs. Experiments show significant performance improvements over existing GPU solvers for high-resolution cloth simulation.

Subspace-Preconditioned GPU Projective Dynamics with Contact for Cloth Simulation

Christian Hafner, Bernd Bickel

The Kirchhoff rod model describes the bending and twisting of slender elastic rods in three dimensions, and has been widely studied to enable the prediction of how a rod will deform, given its geometry and boundary conditions. In this work, we study a number of inverse problems with the goal of computing the geometry of a straight rod that will automatically deform to match a curved target shape after attaching its endpoints to a support structure. Our solution lets us finely control the static equilibrium state of a rod by varying the cross-sectional profiles along its length. We also show that the set of physically realizable equilibrium states admits a concise geometric description in terms of linear line complexes, which leads to very efficient computational design algorithms. Implemented in an interactive software tool, they allow us to convert three-dimensional hand-drawn spline curves to elastic rods, and give feedback about the feasibility and practicality of a design in real time. We demonstrate the efficacy of our method by designing and manufacturing several physical prototypes with applications to interior design and soft robotics.

The Design Space of Kirchhoff Rods

Lorenzo Diazzi, Daniele Panozzo, Amir Vaxman, Marco Attene

We present a numerically robust algorithm for computing the constrained Delaunay tetrahedrization (CDT) of a piecewise-linear complex, which has a 100% success rate on the 4408 valid models in the Thingi10k dataset. We build on the underlying theory of the well-known TetGen software, but use a floating-point implementation based on indirect geometric predicates to implicitly represent Steiner points: this new approach dramatically simplifies the implementation, removing the need for ad-hoc tolerances in geometric operations. Our approach leads to a robust and parameter-free implementation, with an empirically manageable number of added Steiner points. Furthermore, our algorithm addresses a major gap in TetGen’s theory which may lead to algorithmic failure on valid models, even when assuming perfect precision in the calculations. Our output tetrahedrization conforms with the input geometry without approximations. We can further round our output to floating-point coordinates for downstream applications, which almost always results in valid floating-point meshes unless the input triangulation is very close to being degenerate.

Constrained Delaunay Tetrahedrization: A Robust and Practical Approach

• Constrained Delaunay Tetrahedrization: A Robust and Practical Approach
• The Design Space of Kirchhoff Rods
• High-Order Moment-Encoded Kinetic Simulation of Turbulent Flows
• Subspace-Preconditioned GPU Projective Dynamics with Contact for Cloth Simulation
• Real-time Height-field Simulation of Sand and Water Mixtures
• A Physically-inspired Approach to the Simulation of Plant Wilting
• Power Plastics: A Hybrid Lagrangian/Eulerian Solver for Mesoscale Inelastic Flows
• Neural Stress Fields for Reduced-order Elastoplasticity and Fracture
• Kirchhoff-Love Shells with Arbitrary Hyperelastic Materials
• Second-Order Finite Elements for Deformable Surfaces
• Fluid Simulation on Neural Flow Maps
• Capturing Animation-Ready Isotropic Materials Using Systematic Poking
• DiffFR: Differentiable SPH-based Fluid-Rigid Coupling for Rigid Body Control
• 3D Bézier Guarding: Boundary-Conforming Curved Tetrahedral Meshing
• A Parametric Kinetic Solver for Simulating Boundary-Dominated Turbulent Flow Phenomena
• Stable Discrete Bending by Analytic Eigensystem and Adaptive Orthotropic Geometric Stiffness
• Progressive Shell Quasistatics for Unstructured Meshes
• GARM-LS: A Gradient-Augmented Reference-Map Method for Level-Set Fluid Simulation
• Neural Metamaterial Networks for Nonlinear Material Design
• An Implicitly Stable Mixture Model for Dynamic Multi-fluid Simulations
• High Density Ratio Multi-fluid Simulation with Peridynamics
• Real-Time Reconstruction of Fluid Flow under Unknown Disturbance
• Authoring and Simulating Meandering Rivers
• Neural Collision Fields for Triangle Primitives
• Learning Contact Deformations with General Collider Descriptors
• ClothCombo: Modeling Inter-Cloth Interaction for Draping Multi-Layered Clothes
• LiCROM: Linear-Subspace Continuous Reduced Order Modeling with Neural Fields
• Subspace Mixed Finite Elements for Real-Time Heterogeneous Elastodynamics
• ViCMA: Visual Control of Multibody Animations
• Non-Newtonian ViRheometry via Similarity Analysis