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

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

A Multilevel SPH Solver with Unified Solid Boundary Handling

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

SIGGRAPH Asia 2016

Real-Time Oil Painting on Mobile Hardware

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

Space-time sculpting of liquid animation

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

Projective Fluids

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

Simulating Visual Geometry

Matthias Müller, Nuttapong Chentanez, Miles Macklin

In computer graphics, simulated objects typically have two or three different representations, a visual mesh, a simulation mesh and a collection of convex shapes for collision handling. Using multiple representations requires skilled authoring and complicates object handing at run time. It can also produce visual artifacts such as a mismatch of collision behavior and visual appearance. The reason for using multiple representation has been performance restrictions in real time environments. However, for virtual worlds, we believe that the ultimate goal must be WYSIWYS – what you see is what you simulate, what you can manipulate, what you can touch. In this paper we present a new method that uses the same representation for simulation and collision handling and an almost identical visualization mesh. This representation is very close and directly derived from a visual input mesh which does not have to be prepared for simulation but can be non-manifold, non-conforming and self-intersecting.

Simulating Visual Geometry

XPBD: Position-Based Simulation of Compliant Constrained Dynamics

Miles Macklin, Matthias Muller, Nuttapong Chentanez

We address the long-standing problem of iteration count and time step dependent constraint stiffness in position-based dynamics (PBD). We introduce a simple extension to PBD that allows it to accurately and efficiently simulate arbitrary elastic and dissipative energy potentials in an implicit manner. In addition, our method provides constraint force estimates, making it applicable to a wider range of applications, such those requiring haptic user-feedback. We compare our algorithm to more expensive non-linear solvers and find it produces visually similar results while maintaining the simplicity and robustness of the PBD method.

XPBD: Position-Based Simulation of Compliant Constrained Dynamics

A Robust Method to Extract the Rotational Part of Deformations

Matthias Muller, Jan Bender, Nuttapong Chentanez, Miles Macklin

We present a novel algorithm to extract the rotational part of an arbitrary 3×3 matrix. This problem lies at the core of two popular simulation methods in computer graphics, the co-rotational Finite Element Method and Shape Matching techniques. In contrast to the traditional method based on polar decomposition, degenerate configurations and inversions are handled robustly and do not have to be treated in a special way. In addition, our method can be implemented with only a few lines of code without branches which makes it particularly well suited for GPU-based applications. We demonstrate the robustness, coherence and efficiency of our method by comparing it to stabilized polar decomposition in several simulation scenarios.

A Robust Method to Extract the Rotational Part of Deformations

A Macroblock Optimization for Grid-Based Nonlinear Elasticity

Nathan Mitchell, Michael Doescher, Eftychios Sifakis

We introduce a new numerical approach for the solution of grid-based discretizations of nonlinear elastic models. Our method targets the linearized system of equations within each iteration of the Newton method, and combines elements of a direct factorization scheme with an iterative Conjugate Gradient method. The goal of our hybrid scheme is to inherit as many of the advantages of its constituent approaches, while curtailing several of their respective drawbacks. In particular, our algorithm converges in far fewer iterations than Conjugate Gradients, especially for systems with less-than-ideal conditioning. On the other hand, our approach largely avoids the storage footprint and memory-bound nature of direct methods, such as sparse Cholesky factorization, while offering very direct opportunities for both SIMD and thread-based parallelism. Conceptually, our method aggregates a rectangular neighborhood of grid cells (typically a 16x8x8 subgrid) into a composite element that we refer to as a “macroblock”. Similar to conventional tetrahedral or hexahedral elements, macroblocks receive nodal inputs (e.g., displacements) and compute nodal outputs (e.g., forces). However, this input/output interface now only includes nodes on the boundary of the 16x8x8 macroblock; interior nodes are always solved exactly, by means of a direct, highly optimized solver. Models built from macroblocks are solved using Conjugate Gradients, which is accelerated due to the reduced number of degrees of freedom and improved robustness against poor conditioning thanks to the direct solver within each macroblock. We explain how we attain these benefits with just a small increase of the per-iteration cost over the simplest traditional solvers.

A Macroblock Optimization for Grid-Based Nonlinear Elasticity