Browsing by Author "Bhattacharya, Haimasree"
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ItemFluid Simulation on Unstructured Quadrilateral Surface MeshesBhattacharya, Haimasree; Levine, Joshua A.; Bargteil, Adam W.In this paper, we present a method for fluid simulation on unstructured quadrilateral surface meshes. We solve the Navier-Stokes equations by performing the traditional steps of fluid simulation, semi-Lagrangian advection and pressure projection, directly on the surface. We include level-set based front-tracking for visualizing “liquids,” while we use densities to visualize “smoke.” We demonstrate our method on a variety of meshes and create an assortment of visual effects ItemA Level-set Method for Skinning Animated Particle Data(IEEE, 2014-10-09) Bhattacharya, Haimasree; Gao, Yue; Bargteil, Adam W.In this paper, we present a straightforward, easy to implement method for particle skinning—generating surfaces from animated particle data. We cast the problem in terms of constrained optimization and solve the optimization using a level-set approach. The optimization seeks to minimize the thin-plate energy of the surface, while staying between surfaces defined by the union of spheres centered at the particles. Our approach skins each frame independently while preserving the temporal coherence of the underlying particle animation. Thus, it is well-suited for environments where particle skinning is treated as a post-process, with each frame generated in parallel. We demonstrate our method on data generated by a variety of fluid simulation techniques and simple particle systems. ItemA Point-based Method for Animating Elastoplastic Solids(ACM, 2009-08-01) Gerszewski, Dan; Bhattacharya, Haimasree; Bargteil, Adam W.In this paper we describe a point-based approach for animating elastoplastic materials. Our primary contribution is a simple method for computing the deformation gradient for each particle in the simulation. The deformation gradient is computed for each particle by finding the affine transformation that best approximates the motion of neighboring particles over a single timestep. These transformations are then composed to compute the total deformation gradient that describes the deformation around a particle over the course of the simulation. Given the deformation gradient we can apply arbitrary constitutive models and compute the resulting elastic forces. Our method has two primary advantages: we do not store or compare to an initial rest configuration and we work directly with the deformation gradient. The first advantage avoids poor numerical conditioning and the second naturally leads to a multiplicative model of deformation appropriate for finite deformations. We demonstrate our approach on a number of examples that exhibit a wide range of material behaviors.