Month: August 2017

Pairwise Force SPH Model for Real-Time Multi-Interaction Applications

Tao Yang, Ralph R. Martin, Ming C. Lin, Jian Chang, and Shi-Min Hu

In this paper, we present a novel pairwise-force smoothed particle hydrodynamics (PF-SPH) model to enable simulation of various interactions at interfaces in real time. Realistic capture of interactions at interfaces is a challenging problem for SPH-based simulations, especially for scenarios involving multiple interactions at different interfaces. Our PF-SPH model can readily handle multiple types of interactions simultaneously in a single simulation; its basis is to use a larger support radius than that used in standard SPH. We adopt a novel anisotropic filtering term to further improve the performance of interaction forces. The proposed model is stable; furthermore, it avoids the particle clustering problem which commonly occurs at the free surface. We show how our model can be used to capture various interactions. We also consider the close connection between droplets and bubbles, and show how to animate bubbles rising in liquid as well as bubbles in air. Our method is versatile, physically plausible and easy-to-implement. Examples are provided to demonstrate the capabilities and effectiveness of our approach.

Pairwise Force SPH Model for Real-Time Multi-Interaction Applications

 

 

Modeling and Data-Driven Parameter Estimation for Woven Fabrics

David Clyde, Joseph Teran, Rasmus Tamstorf

Accurate estimation of mechanical parameters for simulation of woven fabrics is essential in many fields. To facilitate this we first present a new orthotropic hyperelastic constitutive model for woven fabrics. Next, we design an experimental protocol for characterizing real fabrics based on commercially available tests. Finally, we create a method for accurately fitting the material parameters to the experimental data. The last step is accomplished by solving inverse problems based on a Catmull-Clark subdivision finite element discretization of the Kirchhoff-Love equations for thin shells. Using this approach we are able to reproduce the fully nonlinear behavior corresponding to the captured data with a small number of parameters while maintaining all fundamental invariants from continuum mechanics. The resulting constitutive model can be used with any discretization (e.g., simple triangle meshes) and not just subdivision finite elements. We illustrate the entire process with results for five types of fabric and compare photo reference of the real fabrics to the simulated equivalents.

Modeling and Data-Driven Parameter Estimation for Woven Fabrics

Inequality Cloth

Ning Jin, Wenlong Lu, Zhenglin Geng, Ronald Fedkiw

As has been noted and discussed by various authors, numerical simulations of deformable bodies often adversely suffer from so-called “locking” artifacts. We illustrate that the “locking” of out-of-plane bending motion that results from even an edge-spring-only cloth simulation can be quite severe, noting that the typical remedy of softening the elastic model leads to an unwanted rubbery look. We demonstrate that this “locking” is due to the well-accepted notion that edge springs in the cloth mesh should preserve their lengths, and instead propose an inequality constraint that stops edges from stretching while allowing for edge compression as a surrogate for bending. Notably, this also allows for the capturing of bending modes at scales smaller than those which could typically be represented by the mesh. Various authors have recently begun to explore optimization frameworks for deformable body simulation, which is particularly germane to our inequality cloth framework. After exploring such approaches, we choose a particular approach and illustrate its feasibility in a number of scenarios including contact, collision, and self-collision. Our results demonstrate the efficacy of the inequality approach when it comes to folding, bending, and wrinkling, especially on coarser meshes, thus opening up a plethora of interesting possibilities.

Inequality Cloth

Hierarchical Vorticity Skeletons

Sebastian Eberhardt, Steffen Weissmann, Ulrich Pinkall, Nils Thuerey

We propose a novel method to extract hierarchies of vortex filaments from given three-dimensional flow velocity fields. We call these collections of filaments Hierarchical Vorticity Skeletons (HVS). They extract multi-scale information from the input velocity field, which is not possible with any previous filament extraction approach. Once computed, these HVSs provide a powerful mechanism for data compression and a very natural way for modifying flows. The data compression rates for all presented examples are above 99%. Employing our skeletons for flow modification has several advantages over traditional approaches. Most importantly, they reduce the complexity of three-dimensional fields to one-dimensional lines and, make complex fluid data more accessible for changing defining features of a flow. The strongly reduced HVS dataset still carries the main characteristics of the flow. Through the hierarchy we can capture the main features of different scales in the flow and by that provide a level of detail control. In contrast to previous work, we present a fully automated pipeline to robustly decompose dense velocities into filaments.

Hierarchical Vorticity Skeletons