Category: Fluids

Jan Bender, Dan Koschier

In this paper we present a novel Smoothed Particle Hydrodynamics (SPH) method for the efficient and stable simulation of incompressible fluids. The most efficient SPH-based approaches enforce incompressibility either on position or velocity level. However, the continuity equation for incompressible flow demands to maintain a constant density and a divergence-free velocity field. We propose a combination of two novel implicit pressure solvers enforcing both a low volume compression as well as a divergence-free velocity field. While a compression-free fluid is essential for realistic physical behavior, a divergence-free velocity field drastically reduces the number of required solver iterations and increases the stability of the simulation significantly. Thanks to the improved stability, our method can handle larger time steps than previous approaches. This results in a substantial performance gain since the computationally expensive neighborhood search has to be performed less frequently. Moreover, we introduce a third optional implicit solver to simulate highly viscous fluids which seamlessly integrates into our solver framework. Our implicit viscosity solver produces realistic results while introducing almost no numerical damping. We demonstrate the efficiency, robustness and scalability of our method in a variety of complex simulations including scenarios with millions of turbulent particles or highly viscous materials.

Divergence-Free SPH for Incompressible and Viscous Fluids

Haixiang Liu, Nathan Mitchell, Mridul Aanjaneya, Eftychios Sifakis

We present a scalable parallel solver for the pressure Poisson equation in fluids simulation which can accommodate complex irregular domains in the order of a billion degrees of freedom, using a single server or workstation fitted with GPU or Many-Core accelerators. The design of our numerical technique is attuned to the subtleties of heterogeneous computing, and allows us to benefit from the high memory and compute bandwidth of GPU accelerators even for problems that are too large to fit entirely on GPU memory. This is achieved via algebraic formulations that adequately increase the density of the GPU-hosted computation as to hide the overhead of offloading from the CPU, in exchange for accelerated convergence. Our solver follows the principles of Domain Decomposition techniques, and is based on the Schur complement method for elliptic partial differential equations. A large uniform grid is partitioned in non-overlapping subdomains, and bandwidth-optimized (GPU or Many-Core) accelerator cards are used to efficiently and concurrently solve independent Poisson problems on each resulting subdomain. Our novel contributions are centered on the careful steps necessary to assemble an accurate global solver from these constituent blocks, while avoiding excessive communication or dense linear algebra. We ultimately produce a highly effective Conjugate Gradients preconditioner, and demonstrate scalable and accurate performance on high-resolution simulations of water and smoke flow.

A scalable Schur-complement fluids solver for heterogeneous compute platforms

José A. Canabal, David Miraut, Nils Thürey, Theodore Kim, Javier Portilla, Miguel A. Otaduy

We propose a method to simulate the rich, scale-dependent dynamics of water waves. Our method preserves the dispersion properties of real waves, yet it supports interactions with obstacles and is computationally efficient. Fundamentally, it computes wave accelerations by way of applying a dispersion kernel as a spatially variant filter, which we are able to compute efficiently using two core technical contributions. First, we design novel, accurate, and compact pyramid kernels which compensate for low-frequency truncation errors. Second, we design a shadowed convolution operation that efficiently accounts for obstacle interactions by modulating the application of the dispersion kernel. We demonstrate a wide range of behaviors, which include capillary waves, gravity waves, and interactions with static and dynamic obstacles, all from within a single simulation.

Dispersion Kernels for Water Wave Simulation

Tetsuya Takahashi, Yoshinori Dobashi, Tomoyuki Nishita, Ming Lin

We propose a hybrid Smoothed Particle Hydrodynamics solver for efficiently simulating incompressible fluids using an interface handling method for boundary conditions in the pressure Poisson equation. We blend particle density computed with one smooth and one spiky kernel to improve the robustness against both fluid-fluid and fluid-solid collisions. To further improve the robustness and efficiency, we present a new interface handling method consisting of two components: free surface handling for Dirichlet boundary conditions and solid boundary handling for Neumann boundary conditions. Our free surface handling appropriately determines particles for Dirichlet boundary conditions using Jacobi-based pressure prediction while our solid boundary handling introduces a new term to ensure the solvability of the linear system. We demonstrate that our method outperforms the state-of-the-art particle-based fluid solvers.

An Efficient Hybrid Incompressible SPH Solver with Interface Handling for Boundary Conditions

Tetsuya Takahashi, Ming Lin

We propose a geometric multilevel solver for efficiently solving linear systems arising from particle-based methods. To apply this method to particle systems, we construct the hierarchy, establish the correspondence between solutions at the particle and grid levels, and coarsen simulation elements taking boundary conditions into account. In addition, we propose a new solid boundary handling method to solve a pressure Poisson equation in a unified manner. We demonstrate that our method can handle general fluid simulation scenarios including two-way fluid-solid coupling, and the computational cost of this new solver scales nearly linearly with respect to the number of unknowns, unlike previous solvers for particle-based methods.

A Multilevel SPH Solver with Unified Solid Boundary Handling

Tuur Stuyck, Fang Da, Sunil Hadap, Philip Dutré

This paper presents a realistic digital oil painting system, specifically targeted at the real-time performance on highly resource constrained portable hardware such as tablets and iPads. To effectively use the limited computing power, we develop an efficient adaptation of the Shallow Water Equations that models all the characteristic properties of oil paint. The pigments are stored in a multi-layered structure to model the peculiar nature of pigment mixing in oil paint. The user experience ranges from thick shape-retaining strokes to runny diluted paint that reacts naturally to the gravity set by tablet orientation. Finally, the paint is rendered in real-time using a combination of carefully chosen efficient rendering techniques. The virtual lighting adapts to the tablet orientation, or alternatively, the front-facing camera captures the lighting environment, which leads to a truly immersive user experience. Our proposed features are evaluated via a user study. In our experience, our system enables artists to quickly try out ideas and compositions anywhere when inspiration strikes, in a truly ubiquitous way. They don’t need to carry expensive and messy oil paint supplies.

Real-Time Oil Painting on Mobile Hardware

Pierre-Luc Manteaux, Ulysse Vimont, Chris Wojtan, Damien Rohmer, Marie-Paule Cani

We propose an interactive sculpting system for seamlessly editing pre-computed animations of liquid, without the need for any re-simulation. The input is a sequence of meshes without correspondences representing the liquid surface over time. Our method enables the efficient selection of consistent space-time parts of this animation, such as moving waves or droplets, which we call space-time features. Once selected, a feature can be copied, edited, or duplicated and then pasted back anywhere in space and time in the same or in another liquid animation sequence. Our method circumvents tedious user interactions by automatically computing the spatial and temporal ranges of the selected feature. We also provide space-time shape editing tools for non-uniform scaling, rotation, trajectory changes, and temporal editing to locally speed up or slow down motion. Using our tools, the user can edit and progressively refine any input simulation result, possibly using a library of pre-computed space-time features extracted from other animations. In contrast to the trial-and-error loop usually required to edit animation results through the tuning of indirect simulation parameters, our method gives the user full control over the edited space-time behaviors.

Space-time sculpting of liquid animation

Marcel Weiler, Dan Koschier, Jan Bender

We present a new method for particle based fluid simulation, using a combination of Projective Dynamics and Smoothed Particle Hydrodynamics (SPH). The Projective Dynamics framework allows the fast simulation of a wide range of constraints. It offers great stability through its implicit time integration scheme and is parallelizable in large parts, so that it can make use of modern multi core CPUs. Yet existing work only uses Projective Dynamics to simulate various kinds of soft bodies and cloth. We are the first ones to incorporate fluid simulation into the Projective Dynamics framework. Our proposed fluid constraints are derived from SPH and seamlessly integrate into the existing method. Furthermore, we adapt the solver to handle the constantly changing constraints that appear in fluid simulation. We employ a highly parallel matrix-free conjugate gradient solver, and thus do not require expensive matrix factorizations.

Projective Fluids