Physics-Based Animation

Bo Zhu, Michiaki Iwata, Ryo Haraguchi, Takashi Ashahara, Nobukuyuki Umetani, Takeo Igarashi, Kazuo Nakazawa

This paper presents a lightweight sketching system that enables interactive illustration of complex fluid systems. Users can sketch on a 2.5-dimensional (2.5D) canvas to design the shapes and connections of a fluid circuit. These input sketches are automatically analyzed and abstracted into a hydraulic graph, and a new hybrid fluid model is used in the background to enhance the illustrations. The system provides rich simple operations for users to edit the fluid system incrementally, and the new internal flow patterns can be simulated in real time. Our system is used to illustrate various fluid systems in medicine, biology, and engineering. We asked professional medical doctors to try our system and obtained positive feedback from them.

Sketch-Based Dynamic Illustration of Fluid Systems

Zhi Yuan, Fan Chen, Ye Zhao

Fluid animation practitioners face great challenges from the complexity of flow dynamics and the high cost of numerical simulation. A major hindrance is the uncertainty of fluid behavior after simulation resolution increases and extra turbulent effects are added. In this paper, we propose to regulate fluid animations with predesigned flow patterns. Animators can design their desired fluid behavior with fast, low-cost simulations. Flow patterns are then extracted from the results by the Lagrangian Coherent Structure (LCS) that represents major flow skeleton. Therefore, the final high-quality animation is confined towards the designed behavior by applying the patterns to drive high-resolution and turbulent simulations. The pattern regulation is easily computed and achieves controllable variance in the output. The method makes it easy to design special fluid effects, which increases the usability and scalability of various advanced fluid modeling technologies.

Pattern Guided Smoke Animation with Lagrangian Coherent Structure

Min Tang, Dinesh Manocha, Sung-Eui Yoon, Peng Du, Jae-Pil Heo, Ruofeng Tong

We present a novel culling algorithm to perform fast and robust continuous collision detection between deforming volume meshes. This includes a continuous separating axis test that can conservatively check whether two volume meshes overlap during a given time interval. Moreover, we present efficient methods to eliminate redundant elementary tests between the features (e.g., vertices, edges, and faces) of volume elements (e.g., tetrahedra). Our approach is applicable to various deforming meshes, including those with changing topologies, and efficiently computes the first time of contact. We are able to perform inter-object and intra-object collision queries in models represented with tens of thousands of volume elements at interactive rates on a single CPU core. Moreover, we observe more than an order of magnitude performance improvement over prior methods.

VolCCD: Fast Continuous Collision Culling Between Deforming Volume Meshes

Karthik Raveendran, Chris Wojtan, Greg Turk

We present a new algorithm for enforcing incompressibility for Smoothed Particle Hydrodynamics (SPH) by preserving uniform density across the domain. We propose a hybrid method that uses a Poisson solve on a coarse grid to enforce a divergence free velocity field, followed by a local density correction of the particles. This avoids typical grid artifacts and maintains the Lagrangian nature of SPH by directly transferring pressures onto particles. Our method can be easily integrated with existing SPH techniques such as the incompressible PCISPH method as well as weakly compressible SPH by adding an additional force term. We show that this hybrid method accelerates convergence towards uniform density and permits a significantly larger time step compared to earlier approaches while producing similar results. We demonstrate our approach in a variety of scenarios with significant pressure gradients such as splashing liquids.

Hybrid Smoothed Particle Hydrodynamics

Nuttapong Chentanez, Matthias Mueller

We present a multigrid method for solving the linear complementarity problem (LCP) resulting from discretizing the Poisson equation subject to separating solid boundary conditions in an Eulerian liquid simulation’s pressure projection step. The method requires only a few small changes to a multigrid solver for linear systems. Our generalized solver is fast enough to handle 3D liquid simulations with separating boundary conditions in practical domain sizes. Previous methods could only handle relatively small 2D domains in reasonable time because they used expensive quadratic programming (QP) solvers. We demonstrate our technique in several practical scenarios in which the omission of separating boundary conditions results in disturbing artifacts of liquid sticking to walls.

A Fluid Pressure Solver Handling Separating Solid Boundary Conditions

David Harmon, Qingnan Zhou, Denis Zorin

Asynchronous variational integration of layered contact models provides a framework for robust collision handling, correct physical behavior, and guaranteed eventual resolution of even the most difficult contact problems. Yet, even for low-contact scenarios, this approach is significantly slower compared to its less robust alternatives — often due to handling of stiff elastic forces in an explicit framework. We propose a method that retains the guarantees, but allows for variational implicit integration of some of the forces, while maintaining asynchronous integration needed for contact handling. Our method uses phantom meshes for calculations with stiff forces, which are then coupled to the original mesh through constraints. We use the augmented discrete Lagrangian of the constrained system to derive a variational integrator with the desired conservation properties.

Asynchronous Integration with Phantom Meshes

The subset of physics-based animation papers includes:

• Pattern-Guided Smoke Animation with Lagrangian Coherent Structure
• A Hybrid Iterative Solver for Robustly Capturing Coulomb Friction in Hair Dynamics
• Sketch-Based Dynamic Illustration of Fluid Systems

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.

Preview-Based Sampling for Controlling Gaseous Simulations

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

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.

A Level-set Method for Skinning Animated Particle Data