The subset of physics-based animation papers includes:
Preview-Based Sampling for Controlling Gaseous Simulations
Ruogang Huang, Zeki Melek, John Keyser
In this work, we describe an automated method for directing the control of a high resolution gaseous fluid simulation based on the results of a lower resolution preview simulation. Small variations in accuracy between low and high resolution grids can lead to divergent simulations, which is problematic for those wanting to achieve a desired behavior. Our goal is to provide a simple method for ensuring that the high resolution simulation matches key properties from the lower resolution simulation. We first let a user specify a fast, coarse simulation that will be used for guidance. Our automated method samples the data to be matched at various positions and scales in the simulation, or allows the user to identify key portions of the simulation to maintain. During the high resolution simulation, a matching process ensures that the properties sampled from the low resolution simulation are maintained. This matching process keeps the different resolution simulations aligned even for complex systems, and can ensure consistency of not only the velocity field, but also advected scalar values. Because the final simulation is naturally similar to the preview simulation, only minor controlling adjustments are needed, allowing a simpler control method than that used in prior keyframing approaches.
Large-Scale Dynamic Simulation of Highly Constrained Strands
Shinjiro Sueda, Garrett L. Jones, David I. W. Levin, Dinesh K. Pai
A significant challenge in applications of computer animation is the simulation of ropes, cables, and other highly constrained strand-like physical curves. Such scenarios occur frequently, for instance, when a strand wraps around rigid bodies or passes through narrow sheaths. Purely Lagrangian methods designed for less constrained applications such as hair simulation suffer from difficulties in these important cases. To overcome this, we introduce a new framework that combines Lagrangian and Eulerian approaches. The two key contributions are the reduced node, whose degrees of freedom precisely match the constraint, and the Eulerian node, which allows constraint handling that is independent of the initial discretization of the strand. The resulting system generates robust, efficient, and accurate simulations of massively constrained systems of rigid bodies and strands.
Large-Scale Dynamic Simulation of Highly Constrained Strands
A Level-set Method for Skinning Animated Particle Data
Haimasree Bhattacharya, Yue Gao, Adam W. Bargteil
In this paper, we present a straightforward, easy to implement method for particle skinning—generating surfaces from animated particle data. We cast the problem in terms of constrained optimization and solve the optimization using a level-set approach. The optimization seeks to minimize the thin-plate energy of the surface, while staying between surfaces defined by the union of spheres centered at the particles. Our approach skins each frame independently while preserving the temporal coherence of the underlying particle animation. Thus, it is well-suited for environments where particle skinning is treated as a post-process, with each frame generated in parallel. We demonstrate our method on data generated by a variety of fluid simulation techniques and simple particle systems.
Eulerian Solid Simulation with Contact
David I. W. Levin, Joshua Litven, Garrett L. Jones, Shinjiro Sueda, Dinesh K. Pai
Simulating viscoelastic solids undergoing large, nonlinear deformations in close contact is challenging. In addition to inter-object contact, methods relying on Lagrangian discretizations must handle degenerate cases by explicitly remeshing or resampling the object. Eulerian methods, which discretize space itself, provide an interesting alternative due to the fixed nature of the discretization. In this paper we present a new Eulerian method for viscoelastic materials that features a collision detection and resolution scheme which does not require explicit surface tracking to achieve accurate collision response. Time-stepping with contact is performed by the efficient solution of large sparse quadratic programs; this avoids constraint sticking and other difficulties. Simulation and collision processing can share the same uniform grid, making the algorithm easy to parallelize. We demonstrate an implementation of all the steps of the algorithm on the GPU. The method is effective for simulation of complicated contact scenarios involving multiple highly deformable objects, and can directly simulate volumetric models obtained from medical imaging techniques such as CT and MRI.
Sensitive Couture for Interactive Garment Editing and Modeling
Nobuyuki Umetani, Danny M. Kaufman, Takeo Igarashi, Eitan Grinspun
We present a novel interactive tool for garment design that enables, for the first time, interactive bidirectional editing between 2D patterns and 3D high-fidelity simulated draped forms. This provides a continuous, interactive, and natural design modality in which 2D and 3D representations are simultaneously visible and seamlessly maintain correspondence. Artists can now interactively edit 2D pattern designs and immediately obtain stable accurate feedback online, thus enabling rapid prototyping and an intuitive understanding of complex drape form.
Sensitive Couture for Interactive Garment Editing and Modeling
Physics-inspired Upsampling for Cloth Simulation in Games
Ladislav Kavan, Dan Gerszewski, Peter-Pike Sloan, Adam W. Bargteil
We propose a method for learning linear upsampling operators for physically-based cloth simulation, allowing us to enrich coarse meshes with mid-scale details in minimal time and memory budgets, as required in computer games. In contrast to classical subdivision schemes, our operators adapt to a specific context (e.g. a flag flapping in the wind or a skirt worn by a character), which allows them to achieve higher detail. Our method starts by pre-computing a pair of coarse and fine training simulations aligned with tracking constraints using harmonic test functions. Next, we train the upsampling operators with a new regularization method that enables us to learn mid-scale details without overfitting. We demonstrate generalizability to unseen conditions such as different wind velocities or novel character motions. Finally, we discuss how to re-introduce high frequency details not explainable by the coarse mesh alone using oscillatory modes.
Element-Wise Mixed Implicit-Explicit Integration for Stable Dynamic Simulation of Deformable Objects
Basil Fierz, Jonas Spillman, Matthias Harders
In order to evolve a deformable object in time, the underlying equations of motion have to be numerically integrated. This is commonly done by employing either an explicit or an implicit integration scheme. While explicit methods are only stable for small time steps, implicit methods are unconditionally stable. In this paper, we present a novel methodology to combine explicit and implicit linear integration approaches, based on element-wise stability considerations. First, we detect the ill-shaped simulation elements which hinder the stable explicit integration of the element nodes as a pre-computation step. These nodes are then simulated implicitly, while the remaining parts of the mesh are explicitly integrated. As a consequence, larger integration time steps than in purely explicit methods are possible, while the computation time per step is smaller than in purely implicit integration. During modifications such as cutting or fracturing, only newly created or modified elements need to be reevaluated, thus making the technique usable in real-time simulations. In addition, our method reduces problems due to numerical dissipation.
Element-Wise Mixed Implicit-Explicit Integration for Stable Dynamic Simulation of Deformable Objects
A Particle-based Method for Preserving Fluid Sheets
Ryoichi Ando, Reiji Tsuruno
We present a new particle-based method that explicitly preserves thin fluid sheets for animating liquids. Our primary contribution is a meshless particle-based framework that splits at thin points and collapses at dense points to prevent the breakup of liquid. In contrast to existing surface tracking methods, the proposed framework does not suffer from numerical diffusion or tangles, and robustly handles topology changes by the meshless representation. As the underlying fluid model, we use Fluid-Implicit-Particle (FLIP) with weak spring forces to generate smooth particle-based liquid animation that maintains an even spatial particle distribution in the presence of eddying or inertial motions. The thin features are detected by examining stretches of distributions of neighboring particles by performing Principle Component Analysis (PCA), which is used to reconstruct thin surfaces with anisotropic kernels. Our algorithm is intuitively implemented, easy to parallelize and capable of producing visually complex thin liquid animations.
SPH Granular Flow with Friction and Cohesion
Ivan Alduan, Miguel Otaduy
Combining mechanical properties of solids and fluids, granular materials pose important challenges for the design of algorithms for realistic animation. In this paper, we present a simulation algorithm based on smoothed particle hydrodynamics (SPH) that succeeds in modeling important features of the behavior of granular materials. These features are unilateral incompressibility, friction and cohesion. We extend an existing unilateral incompressibility formulation to be added at almost no effort to an existing SPH-based algorithm for fluids. The main advantages of this extension are the ease of implementation, the lack of grid artifacts, and the simple two-way coupling with other objects. Our friction and cohesion models can also be incorporated in a seamless manner in the overall SPH simulation algorithm.