Efficient solver for spacetime control of smoke

Zherong Pan, Dinesh Manocha
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引用次数: 3

Abstract

We present a novel algorithm to control the physically-based animation of smoke. Given a set of keyframe smoke shapes, we compute a dense sequence of control force fields that can drive the smoke shape to match several keyframes at certain time instances. Our approach formulates this control problem as a spacetime optimization constrained by partial differential equations. In order to compute the locally optimal control forces, we alternatively optimize the velocity fields and density fields using an alternating direction method of multiplier (ADMM) optimizer. In order to reduce the high complexity of multiple passes of fluid resimulation during velocity field optimization, we utilize the coherence between consecutive fluid simulation passes. We demonstrate the benefits of our approach by computing accurate solutions on 2D and 3D benchmarks. In practice, we observe up to an order of magnitude improvement over prior optimal control methods.
烟雾时空控制的有效求解器
我们提出了一种新的算法来控制基于物理的烟雾动画。给定一组关键帧烟雾形状,我们计算了一个密集的控制力场序列,可以驱动烟雾形状在特定时间实例中匹配几个关键帧。我们的方法将这个控制问题表述为一个由偏微分方程约束的时空优化问题。为了计算出局部最优的控制力,我们使用乘法器的交替方向优化方法交替优化速度场和密度场。为了降低速度场优化过程中流体再模拟多道次的高复杂性,我们利用了连续流体模拟道次之间的相干性。我们通过在2D和3D基准上计算精确的解决方案来展示我们方法的好处。在实践中,我们观察到比先前的最优控制方法有一个数量级的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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