Physics-Based Animation

Rene Winchenbach, Hendrik Hochstetter, Andreas Kolb

In this paper we present a new approach to create neighbor lists with strict memory bounds for incompressible Smoothed Particle Hydrodynamics (SPH) simulations. Our proposed approach is based on a novel efficient predictive-corrective algorithm that locally adjusts particle support radii in order to yield neighborhoods of a user-defined maximum size. Due to the improved estimation of the initial support radius, our algorithm is able to efficiently calculate neighborhoods in a single iteration in almost any situation. We compare our neighbor list algorithm to previous approaches and show that our proposed approach can handle larger particle numbers on a single GPU due to its strict guarantees and is able to simulate more particles in real time due to its benefits in regard to performance. Additionally we demonstrate the versatility and stability of our approach in several different scenarios, for example multi-scale simulations and with different kernel functions.

Constrained Neighbor Lists for SPH-based Fluid Simulations

Florian Canezin, Gael Guennebaud, Loïc Barthe

Particle based simulations are widely used in computer graphics. In this field, several recent results have improved the simulation itself or improved the tension of the final fluid surface. In current particle based implementations, the particle neighborhood is computed by considering the Euclidean distance between fluid particles only. Thus particles from different fluid components interact, which generates both local incorrect behavior in the simulation and blending artifacts in the reconstructed fluid surface. Our method introduces a better neighborhood computation for both the physical simulation and surface reconstruction steps. We track and store the local fluid topology around each particle using a graph structure. In this graph, only particles within the same local fluid component are neighbors and other disconnected fluid particles are inserted only if they come into contact. The graph connectivity also takes into account the asymmetric behavior of particles when they merge and split, and the fluid surface is reconstructed accordingly, thus avoiding their blending at distance before a merge. In the simulation, this neighborhood information is exploited for better controlling the fluid density and the force interactions at the vicinity of its boundaries. For instance, it prevents the introduction of collision events when two distinct fluid components are crossing without contact, and it avoids fluid interactions through thin waterproof walls. This leads to an overall more consistent fluid simulation and reconstruction.

Topology-Aware Neighborhoods for Point-Based Simulation and Reconstruction

Aaron Demby Jones, Pradeep Sen, Theodore Kim

Subspace fluid simulations, also known as reduced-order simulations, can be extremely fast, but also require basis matrices that consume an enormous amount of memory. Motivated by the extreme sparsity of Laplacian eigenfunctions in the frequency domain, we design a frequency-space codec that is capable of compressing basis matrices by up to an order of magnitude. However, if computed naively, decompression can be highly inefficient and dominate the running time, effectively negating the advantage of the subspace approach. We show how to significantly accelerate the decompressor by performing the key matrix-vector product in the sparse frequency domain. Subsequently, our codec only adds a factor of three or four to the overall runtime. The compression preserves the overall quality of the simulation, which we show in a variety of examples.

Compressing Fluid Subspaces

Sheng Yang Xiaowei He Huamin Wang Sheng Li Guoping Wang Enhua Wu Kun Zhou

Capillary waves are difficult to simulate due to their fast traveling speed and high frequency. In this paper, we propose to approximate capillary wave effects by surface compression waves under the SPH framework. To achieve this goal, we present a method to convert surface tension energy changes measured from SPH simulation into high-frequency density variations. Based on the compression wave propagation model, we present an approximate technique to simulate capillary wave propagation in a high-frequency particle density field. To address noise issues in wave simulation, we develop a simple way to apply the zero pressure condition on free surfaces in projection-based incompressible SPH. Our experiment shows that the developed algorithm can produce realistic capillary wave effects on both thin liquid features and large liquid bodies. Its computational overhead is also small.

Enriching SPH Simulation by Approximate Capillary Waves