Physics-Based Animation

We present a new hybrid CPU/GPU collision detection technique for rigid and deformable objects based on spatial subdivision. Our approach efficiently exploits the massive computational capabilities of modern CPUs and GPUs commonly found in off-the-shelf computer systems. The algorithm is specifically tailored to be highly scalable on both the CPU and the GPU sides. We can compute discrete and continuous external and self-collisions of non-penetrating rigid and deformable objects consisting of many tens of thousands of triangles in few milliseconds on a modern PC. Our approach is orders of magnitude faster than earlier CPU-based approaches and up to twice as fast as the most recent GPU-based techniques.

Fast and Scalable CPU/GPU Collision Detection for Rigid and Deformable Surfaces

Chris Wojtan,  Georgia Tech: Animating Physical Phenomena with Embedded Surface Meshes

Andreas Söderström, Linköping University: Memory Efficient Methods for Eulerian Free Surface Fluid Animation

By modeling mass transfer phenomena, we simulate solids and liquids dissolving or changing to other substances.We also deal with the very small-scale phenomena that occur when a fluid spreads out at the interface of another fluid. We model the pressure at the interfaces between fluids with Darcy’s Law and represent the viscous fingering phenomenon in which a fluid interface spreads out with a fractal-like shape. We use hybrid grid-based simulation and smoothed particle hydrodynamics (SPH) to simulate intermolecular diffusion and attraction using particles at a computable scale. We have produced animations showing fluids mixing and objects dissolving.

Hybrid Simulation of Miscible Mixing with Viscous Fingering

The visual simulation of natural phenomena has been widely studied. Although several methods have been proposed to simulate melting, the flows of meltwater drops on the surfaces of objects are not taken into account. In this paper, we propose a particle-based method for the simulation of the melting and freezing of ice objects and the interactions between ice and fluids. To simulate the flow of meltwater on ice and the formation of water droplets, a simple interfacial tension is proposed, which can be easily incorporated into common particle-based simulation methods such as Smoothed Particle Hydrodynamics. The computations of heat transfer, the phase transition between ice and water, the interactions between ice and fluids, and the separation of ice due to melting are further accelerated by implementing our method using CUDA. We demonstrate our simulation and rendering method for depicting melting ice at interactive frame-rates.

Fast Particle-Based Visual Simulation of Melting Ice

In this paper we introduce a novel parallel and interactive SPH simulation and rendering method on the GPU using CUDA which allows for high quality visualization. The crucial particle neighborhood search is based onZ-indexing and parallel sorting which eliminates GPU memory overhead due to grid or hierarchical data structures. Furthermore, it overcomes limitations imposed by shading languages allowing it to be very flexible and approaching the practical limits of modern graphics hardware. For visualizing the SPH simulation we introduce a new rendering pipeline. In the first step, all surface particles are efficiently extracted from the SPH particle cloud exploiting the simulation data. Subsequently, a partial and therefore fast distance field volume is rasterized from the surface particles. In the last step, the distance field volume is directly rendered using state-of-the-art GPU raycasting. This rendering pipeline allows for high quality visualization at very high frame rates.

Interactive SPH Simulation and Rendering on the GPU

The papers program for VRIPHYS 2010 (VRIPHYS = Virtual Reality Interaction and Physical Simulation) has recently been posted here.

We present a simple technique for creating fluid silhouettes described with vector graphics, which we call “Vector Fluid.” In our system, a solid region in the fluid is represented as a closed contour and advected by fluid flow to form a curly and clear shape similar to marbling or sumi-nagashi. The fundamental principle behind our method is that contours of solid regions should not collide. This means that if the initial shape of the region is a concave polygon, that shape should maintain its topology so that it can be rendered as a regular concave polygon, no matter how irregularly the contour is distorted by advection. In contrast to other techniques, our approach explicitly neglects topology changes to track surfaces in a trade off of computational cost and complexity. We also introduce an adaptive contour sampling technique to reduce this extra cost. We explore specific examples in 2D for art oriented usage and show applications and robustness of our method to exhibit organic fluid components. We also demonstrate how to port our entire algorithm onto a GPU to boost interactive performance for complex scenes.

Vector Fluid: A Vector Graphics Depiction of Free Surface Flow

We present a method for directly modeling piles of objects in multibody simulations. Piles of objects represent some of the more interesting, but also most time-consuming portion of simulation. We propose a method for reducing computation in many of these situations by explicitly modeling the piles that the objects may form into. By modeling pile behavior rather than the behavior of all individual objects, we can achieve realistic results in less time, and without directly modeling the frictional component that leads to desired pile shapes. Our method is simple to implement and can be easily integrated with existing rigid body simulations. We observe notable speedups in several rigid body examples, and generate a wider variety of piled structures than possible with strict impulse-based simulation.

Piles of Objects

This paper introduces a fully-Eulerian interface tracking framework that preserves the fine details of liquids. Unlike existing Eulerian methods, the proposed framework shows good mass conservation even though it does not employ conventional Lagrangian elements. In addition, it handles complex merging and splitting of interfaces robustly due to the implicit representation. To model the interface more accurately, a high order polynomial reconstruction of the signed distance function is utilized based on a number of sub-grid quadrature points. By combining this accurate polynomial representation with a high-order re-initialization method, the proposed framework preserves the detailed structures of the interface. Moreover, the method is simple to implement, unconditionally stable, and is suitable for parallel computing environments.

Detail-Preserving Fully Eulerian Interface Tracking Framework

Catching up on some recent theses:

• Robust, efficient, and accurate contact algorithms – David Harmon, Columbia University
• Unified particle simulation and interactions in computer animation – Toon Lenaerts, Katholicke Universiteit Leuven
• Simulating viscous incompressible fluids with embedded boundary finite difference methods – Christopher Batty, University of British Columbia
• Geometric interpretation of physical systems for improved elasticity simulations – Liliya Kharevych, Caltech

If there are other recent ones I’ve missed, post them in the comments and I’ll add them to the list!