Granular materials exhibit a large number of diverse physical phenomena which makes their numerical simulation challenging. When set in motion they flow almost like a fluid, while they can present high shear strength when at rest. Those macroscopic effects result from the material’s microstructure: a particle skeleton with interlocking particles which stick to and slide across each other, producing soil cohesion and friction. For the purpose of Earthmoving equipment operator training, we developed Parallel Particles (P2), a fast and stable position based granular material simulator which models inter-particle friction and adhesion and captures the physical nature of soil to an extend sufficient for training. Our parallel solver makes the approach scalable and applicable to modern multi-core architectures yielding the simulation speed required in this application. Using a regularization procedure, we successfully model visco-elastic particle interactions on the position level which provides real, physical parameters allowing for intuitive tuning. We employ the proposed technique in an Excavator training simulator and demonstrate that it yields physically plausible results at interactive to real-time simulation rates.
Parallel Particles (P^2): A Parallel Position Based Approach for Fast and Stable Simulation of Granular Materials
Mark Browning, Connelly Barnes, Samantha Ritter, Adam Finkelstein
We present a method that combines hand-drawn artwork with fluid simulations to produce animated fluids in the visual style of the artwork. Given a fluid simulation and a set of keyframes rendered by the artist in any medium, our system produces a set of in-betweens that visually matches the style of the keyframes and roughly follows the motion from the underlying simulation. Our method leverages recent advances in patch-based regenerative morphing and image melding to produce temporally coherent sequences with visual fidelity to the target medium. Because direct application of these methods results in motion that is generally not fluid-like, we adapt them to produce motion closely matching that of the underlying simulation. The resulting animation is visually and temporally coherent, stylistically consistent with the given keyframes, and approximately matches the motion from the simulation. We demonstrate the method with animations in a variety of visual styles.
Stylized Keyframe Animation of Fluid Simulations
The SIGGRAPH Asia 2014 collection includes:
Transactions on Graphics, to be presented at SIG Asia:
Xinxin Zhang, Robert Bridson
Solving the N-body problem, i.e. the Poisson problem with point sources, is a common task in graphics and simulation. The naive direct summation of the kernel function over all particles scales quadratically, rendering it too slow for large problems, while the optimal Fast Multipole Method has drastic implementation complexity and can sometimes carry too high an overhead to be practical. We present a new Particle-Particle Particle-Mesh (PPPM) algorithm which is fast, accurate, and easy to implement even in parallel on a GPU. We capture long-range interactions with a fast multigrid solver on a background grid with a novel boundary condition, while short-range interactions are calculated directly with a new error compensation to avoid error from the background grid. We demonstrate the power of PPPM with a new vortex particle smoke solver, which features a vortex segment-approach to the stretching term, potential flow to enforce no-stick solid boundaries on arbitrary moving solid boundaries, and a new mechanism for vortex shedding from boundary layers. Comparison against a simpler Vortex-in-Cell approach shows PPPM can produce significantly more detailed results with less computation. In addition, we use our PPPM solver for a Poisson surface reconstruction problem to show its potential as a general-purpose Poisson solver.
Particle-particle Particle-mesh (PPPM) Fast Summation for Fluids and Beyond
Adam W. Bargteil, Elaine Cohen
In this paper, we investigate the use of quadratic finite elements for graphical animation of deformable bodies. We consider both integrating quadratic elements with conventional linear elements to achieve a computationally efficient adaptive-degree simulation framework as well as wholly quadratic elements for the simulation of non-linear rest shapes. In both cases, we adopt the Bézier basis functions and employ a co-rotational linear strain formulation. As with linear elements, the co-rotational formulation allows us to precompute per-element stiffness matrices, resulting in substantial computational savings. We present several examples that demonstrate the advantages of quadratic elements in general and our adaptive-degree system in particular. Furthermore, we demonstrate, for the first time in computer graphics, animations of volumetric deformable bodies with non-linear rest shapes.
Animation of Deformable Bodies with Quadratic Bezier Finite Elements
I’ve been slow in getting this list together, so without further ado:
- Continuous Collision Detection Between Points and Signed Distance Fields
- Massively Parallel Batch Neural Gas for Bounding Volume Hierarchy Construction
- Massively-Parallel Proximity Queries for Point Clouds
- Efficient Transfer of Contact-Point Local Deformations in Data-Driven Simulations Using Hermitian Moments
- A unified topological-physical model for adaptive refinement
- A p-Multigrid Algorithm using Cubic Finite Elements for Efficient Deformation Simulation
- Mechanical modelling of three-dimensional plant tissue indented by a probe
- Controlling the Shape and Motion of Plumes in Explosion Simulations
- SutureHap: a Suture Simulator with Haptic Feedback
- Information Fusion for Real-time Motion Estimation in Image-guided Breast Biopsy Navigation
- Virtual Fitting Pipeline: Body Dimension Recognition, Cloth Modelling, and On-Body Simulation
- Coupling Hair with Smoothed Particle Hydrodynamics Fluids
- A Parallel Architecture for IISPH Fluids
- An Improved Jacobi Solver for Particle Simulation
- Parallel Particles: A Parallel Position Based Approach for Fast and Stable Simulation of Granular Materials
- Laplacian Cut-Maps for Real-Time Deformables
- Variable stiffness haptic interface controlled through Inverse simulation
If anyone has links to the associated papers for the (many) missing ones, please let me know!
Hongyi Xu, Jernej Barbic
We present an algorithm for fast continuous collision detection between points and signed distance fields. Such robust queries are often needed in computer animation, haptics and virtual reality applications, but have so far only been investigated for polygon (triangular) geometry representations. We demonstrate how to use an octree subdivision of the distance field for fast traversal of distance field cells. We also give a method to combine octree subdivision with points organized into a tree hierarchy, for efficient culling of continuous collision detection tests. We apply our method to multibody rigid simulations, and demonstrate that our method accelerates continuous collision detection between points and distance fields by an order of magnitude.
Continuous Collision Detection Between Points and Signed Distance Fields
Min Tang, Ruofeng Tong, Zhendong Wang, Dinesh Manocha
We present fast algorithms to perform accurate CCD queries between triangulated models. Our formulation uses properties of the Bernstein basis and Bezier curves and reduces the problem to evaluating signs of polynomials. We present a geometrically exact CCD algorithm based on the exact geometric computation paradigm to perform reliable Boolean collision queries. This algorithm is more than an order of magnitude faster than prior exact algorithms. We evaluate its performance for cloth and FEM simulations on CPUs and GPUs, and highlight the benefits.
Fast and Exact Continuous Collision Detection with Bernstein Sign Classification
Fabian Hahn, Bernhard Thomaszewski, Stelian Coros, Robert W. Sumner, Forrester Cole, Mark Meyer, Tony DeRose, and Markus Gross
We present a new approach to clothing simulation using low-dimensional linear subspaces with temporally adaptive bases. Our method exploits full-space simulation training data in order to construct a pool of low-dimensional bases distributed across pose space. For this purpose, we interpret the simulation data as offsets from a kinematic deformation model that captures the global shape of clothing due to body pose. During subspace simulation, we select low-dimensional sets of basis vectors according to the current pose of the character and the state of its clothing. Thanks to this adaptive basis selection scheme, our method is able to reproduce diverse and detailed folding patterns with only a few basis vectors. Our experiments demonstrate the feasibility of subspace clothing simulation and indicate its potential in terms of quality and computational efficiency.
Subspace Clothing Simulation Using Adaptive Bases
Nuttapong Chentanez, Matthias Mueller, Tae-Yong Kim
We propose a new method to simulate large scale water phenomena by combining particle, 3D grid and height field methods. In contrast to most hybrid approaches that use particles to simulate foam and spray only, we also represent the bulk of water near the surface with both particles and a grid depending on the regions of interest and switch between those two representations during the course of the simulation. For the coupling we leverage the recent idea of tracking the water surface with a density field in grid based methods. Combining particles and a grid simulation then amounts to adding the density field of the particles and the one stored on the grid. For open scenes, we simulate the water outside of the 3D grid domain by solving the Shallow Water Equations on a height field. We propose new methods to couple these two domains such that waves travel naturally across the border. We demonstrate the effectiveness of our approach in various scenarios including a whale breaching simulation, all running in real-time or at interactive rates.
Coupling 3D Eulerian, Height Field and Particle Methods for the Simulation of Large Scale Liquid Phenomena