Category: Deformables

Automatic Construction of Coarse, High-Quality Tetrahedralizations that Enclose and Approximate Surfaces for Animation

David A. Stuart, Joshua A. Levine, Ben Jones, Adam Bargteil

Embedding high-resolution surface geometry in coarse control meshes is a standard approach to achieving high-quality computer animation at low computational expense. In this paper we present an effective, automatic method for generating such control meshes. The resulting high-quality, tetrahedral meshes enclose and approximate an input surface mesh, avoiding extrapolation artifacts and ensuring that the resulting coarse volumetric meshes are adequate collision proxies. Our approach comprises three steps: we begin with a tetrahedral mesh built from the body-centered cubic lattice that tessellates the bounding box of the input surface; we then perform a sculpting phase that carefully removes elements from the lattice; and finally a variational vertex adjustment phase iteratively adjusts vertex positions to more closely approximate the surface geometry. Our approach provides explicit trade-offs between mesh quality, resolution, and surface approximation. Our experiments demonstrate the technique can be used to build high-quality meshes appropriate for simulations within games.

Automatic Construction of Coarse, High-Quality Tetrahedralizations that  Enclose and Approximate Surfaces for Animation

A GPU-Based Streaming Algorithm for High Resolution Cloth Simulation

Min Tang, Ruofeng Tong, Rahul Narain, Chang Meng, Dinesh Manocha

We present a GPU-based streaming algorithm to perform high-resolution and accurate cloth simulation. We map all the components of cloth simulation pipeline, including time integration, collision detection, collision response, and velocity updating to GPU-based kernels and data structures. Our algorithm perform intra-object and inter-object collisions, handles contacts and friction, and is able to accurately simulate folds and wrinkles. We describe the streaming pipeline and address many issues in terms of obtaining high throughput on many-core GPUs. In practice, our algorithm can perform high-fidelity simulation on a cloth mesh with 2M triangles using 3GB of GPU memory. We highlight the parallel performance of our algorithm on three different generations of GPUs. On a high-end NVIDIA Tesla K20c, we observe up to two orders of magnitude performance improvement as compared to a single-threaded CPU-based algorithm, and about one order of magnitude improvement over a 16-core CPU-based parallel implementation.

A GPU-Based Streaming Algorithm for High Resolution Cloth Simulation

Implicit Integration for Particle-based Simulation of Elasto-plastic Solids

Yahan Zhou, Zhaoliang Lun, Evangelos Kalogerakis, Rui Wang

We present a novel particle-based method for stable simulation of elasto-plastic materials. The main contribution of our method is an implicit numerical integrator, using a physically-based model, for computing particles that undergo both elastic and plastic deformations. The main advantage of our implicit integrator is that it allows the use of large time steps while still preserving stable and physically plausible simulation results. As a key component of our algorithm, at each time step we compute the particle positions and velocities based on a sparse linear system, which we solve efficiently on the graphics hardware. Compared to existing techniques, our method allows for a much wider range of stiffness and plasticity settings. In addition, our method can significantly reduce the computation cost for certain range of material types. We demonstrate fast and stable simulations for a variety of elasto-plastic materials, ranging from highly stiff elastic materials to highly plastic ones.

Implicit Integration for Particle-based Simulation of Elasto-plastic Solids

An Efficient Construction of Reduced Deformable Objects

Christoph von Tycowicz, Christian Schulz, Hans-Peter Seidel, Klaus Hildebrandt

Many efficient computational methods for physical simulation are based on model reduction. We propose new model reduction techniques for the approximation of reduced forces and for the construction of reduced shape spaces of deformable objects that accelerate the construction of a reduced dynamical system, increase the accuracy of the approximation, and simplify the implementation of model reduction. Based on the techniques, we introduce schemes for real-time simulation of deformable objects and interactive deformation-based editing of triangle or tet meshes. We demonstrate the effectiveness of the new techniques in different experiments with elastic solids and shells and compare them to alternative approaches.

An Efficient Construction of Reduced Deformable Objects

Simulation and Control of Skeleton-Driven Soft Body Characters

Libin Liu, KangKang Yin, Bin Wang, Baining Guo

In this paper we present a physics-based framework for simulation and control of human-like skeleton-driven soft body characters. We couple the skeleton dynamics and the soft body dynamics to enable two-way interactions between the skeleton, the skin geometry, and the environment. We propose a novel pose-based plasticity model that extends the corotated linear elasticity model to achieve large skin deformation around joints. We further reconstruct controls from reference trajectories captured from human subjects by augmenting a sampling-based algorithm. We demonstrate the effectiveness of our framework by results not attainable with a simple combination of previous methods.

Simulation and Control of Skeleton-Driven Soft Body Characters

Fast Simulation of Mass-Spring Systems

Tiantian Liu, Adam Bargteil, James F. O’Brien, Ladislav Kavan

We describe a scheme for time integration of mass-spring systems that makes use of a solver based on block coordinate descent. This scheme provides a fast solution for classical linear (Hookean) springs. We express the widely used implicit Euler method as an energy minimization problem and introduce spring directions as auxiliary unknown variables. The system is globally linear in the node positions, and the non-linear terms involving the directions are strictly local. Because the global linear system does not depend on run-time state, the matrix can be pre-factored, allowing for very fast iterations. Our method converges to the same final result as would be obtained by solving the standard form of implicit Euler using Newton’s method. Although the asymptotic convergence of Newton’s method is faster than ours, the initial ratio of work to error reduction with our method is much faster than Newton’s. For real-time visual applications, where speed and stability are more important than precision, we obtain visually acceptable results at a total cost per timestep that is only a fraction of that required for a single Newton iteration. When higher accuracy is required, our algorithm can be used to compute a good starting point for subsequent Newton’s iteration.

Fast Simulation of Mass-Spring Systems

A Material Point Method for Snow Simulation

Alexey Stomakhin, Craig Schroeder, Lawrence Chai, Joseph Teran, Andrew Selle

Snow is a challenging natural phenomenon to visually simulate. While the graphics community has previously considered accumulation and rendering of snow, animation of snow dynamics has not been fully addressed. Additionally, existing techniques for solids and fluids have difficulty producing convincing snow results. Specifically, wet or dense snow that has both solid- and fluid-like properties is difficult to handle. Consequently, this paper presents a novel snow simulation method utilizing a usercontrollable elasto-plastic constitutive model integrated with a hybrid Eulerian/Lagrangian Material Point Method. The method is continuum based and its hybrid nature allows us to use a regular Cartesian grid to automate treatment of self-collision and fracture. It also naturally allows us to derive a grid-based semi-implicit integration scheme that has conditioning independent of the number of Lagrangian particles. We demonstrate the power of our method with a variety of snow phenomena including complex character interactions.

A Material Point Method for Snow Simulation

A Level Set Method for Ductile Fracture

Jan Hegemann, Chenfanfu Jiang, Craig Schroeder, Joseph M. Teran

We utilize the shape derivative of the classical Griffith’s energy in a level set method for the simulation of dynamic ductile fracture. The level set is defined in the undeformed configuration of the object, and its evolution is designed to represent a transition from undamaged to failed material. No re-meshing is needed since the resulting topological changes are handled naturally by the level set method. We provide a new mechanism for the generation of fragments of material during the progression of the level set in the Griffith’s energy minimization. Collisions between different material pieces are resolved with impulses derived from the material point method over a background Eulerian grid. This provides a stable means for colliding with embedded interfaces. Simulation of corotational elasticity is based on an implicit finite element discretization.

A Level Set Method for Ductile Fracture

Efficient Simulation of Secondary Motion in Rig-Space

Fabian Hahn, Bernhard Thomaszewski, Stelian Coros, Sebastian Martin, Robert Sumner, Markus Gross

We present an efficient method for augmenting keyframed character animations with physically-simulated secondary motion. Our method achieves a performance improvement of one to two orders of magnitude over previous work without compromising on quality. This performance is based on a linearized formulation of rig-space dynamics that uses only rig parameters as degrees of freedom, a physics-based volumetric skinning method that allows our method to predict the motion of internal vertices solely from deformations of the surface, as well as a deferred Jacobian update scheme that drastically reduces the number of required rig evaluations. We demonstrate the performance of our method by comparing it to previous work and showcase its potential on a production-quality character rig.

Efficient Simulation of Secondary Motion in Rig-Space

Subspace Integration with Local Deformations

David Harmon, Denis Zorin

Subspace techniques greatly reduce the cost of nonlinear simulation by approximating deformations with a small custom basis. In order to represent the deformations well (in terms of a global metric), the basis functions usually have global support, and cannot capture localized deformations. While reduced-space basis functions can be localized to some extent, capturing truly local deformations would still require a very large number of precomputed basis functions, significantly degrading both precomputation and online performance. We present an efficient approach to handling local deformations that cannot be predicted, most commonly arising from contact and collisions, by augmenting the subspace basis with custom functions derived from analytic solutions to static loading problems. We also present a new cubature scheme designed to facilitate fast computation of the necessary runtime quantities while undergoing a changing basis. Our examples yield a two order of magnitude speedup over full-coordinate simulations, striking a desirable balance between runtime speeds and expressive ability.

Subspace Integration with Local Deformations