Simulating the behavior of soap films and foams is a challenging task. A direct numerical simulation of films and foams via the Navier-Stokes equations is still computationally too expensive. We propose an alternative formulation inspired by geometric flow. Our model exploits the fact, according to Plateau’s laws, that the steady state of a film is a union of constant mean curvature surfaces and minimal surfaces. Such surfaces are also well known as the steady state solutions of certain curvature flows. We show a link between the Navier-Stokes equations and a recent variant of mean curvature flow, called *hyperbolic mean curvature flow*, under the assumption of constant air pressure per enclosed region. We thus introduce hyperbolic mean curvature flow to describe film dynamics. Instead of using hyperbolic mean curvature flow as is, we propose to replace curvature by the gradient of the surface area functional. This formulation enables us to robustly handle non-manifold configurations; such junctions connecting multiple films are intractable with the traditional formulation using curvature. We also add explicit volume preservation to hyperbolic mean curvature flow, which in fact corresponds to the pressure term of the Navier-Stokes equations. Our method is simple, fast, robust, and consistent with Plateau’s laws, which are all due to our reformulation of film dynamics as a geometric flow.

We present an adaptive Generalized Interpolation Material Point (GIMP) method for simulating elastoplastic materials. Our approach allows adaptive refining and coarsening of different regions of the material, leading to an efficient MPM solver that concentrates most of the computation resources in specific regions of interest. We propose a C1 continuous adaptive basis function that satisfies the partition of unity property and remains nonnegative throughout the computational domain. We develop a practical strategy for particle-grid transfers that leverages the recently introduced SPGrid data structure for storing sparse multi-layered grids. We demonstrate the robustness and efficiency of our method on the simulation of various elastic and plastic materials. We also compare key kernel components to uniform grid MPM solvers to highlight performance benefits of our method.

An Adaptive Generalized Interpolation Material Point Method for Simulating Elastoplastic Materials

]]>In this paper we present a physically-based model for simulating realistic interactions between liquid droplets in an efficient manner. Our particle-based system recreates the coalescence, separation and fragmentation interactions that occur between colliding liquid droplets and allows systems of droplets to be meaningfully repre- sented by an equivalent number of simulated particles. By consid- ering the interactions specific to liquid droplet phenomena directly, we display novel levels of detail that cannot be captured using other interaction models at a similar scale. Our work combines experi- mentally validated components, originating in engineering, with a collection of novel modifications to create a particle-based interac- tion model for use in the development of mid-to-large scale droplet- based liquid spray effects. We demonstrate this model, alongside a size-dependent drag force, as an extension to a commonly-used ballistic particle system and show how the introduction of these interactions improves the quality and variety of results possible in recreating liquid droplets and sprays, even using these otherwise simple systems.

]]>We present a novel method for the combustion of botanical tree models. Tree models are represented as connected particles for the branching structure and a polygonal surface mesh for the combustion. Each particle stores biological and physical attributes that drive the kinetic behavior of a plant and the exothermic reaction of the combustion. Coupled with realistic physics for rods, the particles enable dynamic branch motions. We model material properties, such as moisture and charring behavior, and associate them with individual particles. The combustion is efficiently processed in the surface domain of the tree model on a polygonal mesh. A user can dynamically interact with the model by initiating fires and by inducing stress on branches. The flames realistically propagate through the tree model by consuming the available resources. Our method runs at interactive rates and supports multiple tree instances in parallel. We demonstrate the effectiveness of our approach through numerous examples and evaluate its plausibility against the combustion of real wood samples.

]]>The simulation of high viscoelasticity poses important computational challenges. One is the difficulty to robustly measure strain and its derivatives in a medium without permanent structure. Another is the high stiffness of the governing differential equations. Solutions that tackle these challenges exist, but they are computationally slow. We propose a constraint-based model of viscoelasticity that enables efficient simulation of highly viscous and viscoelastic phenomena. Our model reformulates, in a constraint-based fashion, a constitutive model of viscoelasticity for polymeric fluids, which defines simple governing equations for a conformation tensor. The model can represent a diverse palette of materials, spanning elastoplastic, highly viscous, and inviscid liquid behaviors. In addition, we have designed a constrained dynamics solver that extends the position-based dynamics method to handle efficiently both position-based and velocity-based constraints. We show results that range from interactive simulation of viscoelastic effects to large-scale simulation of high viscosity with competitive performance

Conformation Constraints for Efficient Viscoelastic Fluid Simulation

]]>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

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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*

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.

]]>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.

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