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Skipping steps in deformable simulation with online model reduction

机译:在线模型简化的可变形仿真中的跳过步骤

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Finite element simulations of nonlinear deformable models are computationally costly, routinely taking hours or days to compute the motion of detailed meshes. Dimensional model reduction can make simulations orders of magnitude faster, but is unsuitable for general deformable body simulations because it requires expensive precomputations, and it can suppress motion that lies outside the span of a pre-specified low-rank basis. We present an online model reduction method that does not have these limitations. In lieu of precomputation, we analyze the motion of the full model as the simulation progresses, incrementally building a reduced-order nonlinear model, and detecting when our reduced model is capable of performing the next timestep. For these subspace steps, full-model computation is "skipped" and replaced with a very fast (on the order of milliseconds) reduced order step. We present algorithms for both dynamic and quasistatic simulations, and a "throttle" parameter that allows a user to trade off between faster, approximate previews and slower, more conservative results. For detailed meshes undergoing low-rank motion, we have observed speedups of over an order of magnitude with our method.
机译:非线性可变形模型的有限元模拟在计算上是昂贵的,通常花费数小时或数天来计算详细网格的运动。降维模型可以使仿真速度加快几个数量级,但不适用于一般的可变形体仿真,因为它需要昂贵的预计算,并且可以抑制超出预先指定的低秩范围的运动。我们提出了一种没有这些限制的在线模型简化方法。代替预计算,我们随着仿真的进行分析整个模型的运动,逐步建立降阶非线性模型,并检测何时我们的降阶模型能够执行下一时间步。对于这些子空间步骤,将“跳过”完整模型计算,并用非常快的(约数毫秒)的降阶步骤代替。我们提供了用于动态和准静态仿真的算法,以及一个“节流”参数,该参数允许用户在较快的近似预览与较慢的更保守的结果之间进行权衡。对于经历低秩运动的详细网格,我们已经观察到使用我们的方法可以实现超过一个数量级的加速。

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