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<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ufj23cmftbe47kik7exdpigzsi" style="color: black;">Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation - SCA '09</a>
Figure 1 : An armadillo demonstrates non-Newtonian behavior similar to a cornstarch solution-resisting large stresses, it initially bounces on the ground, but when the stress is reduced it flows readily. Abstract 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<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/1599470.1599488">doi:10.1145/1599470.1599488</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/sca/GerszewskiBB09.html">dblp:conf/sca/GerszewskiBB09</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rh3vqwnz5jgsnpg5wpog2wfisu">fatcat:rh3vqwnz5jgsnpg5wpog2wfisu</a> </span>
more »... ansformation 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.
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