无散度SPH边界处理的MLS压力外推

Stefan Band, Christoph Gissler, A. Peer, M. Teschner
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引用次数: 7

摘要

我们提出了一种新的方法来预测不可压缩无发散SPH模拟(DFSPH)中边界粒子的压力值。我们的方法采用移动最小二乘(MLS)来预测边界粒子的压力。因此,MLS计算的超平面近似于流体和边界粒子界面处的压力场。我们将这种方法与之前的两种技术进行比较。先前的一项技术反映了流体到边界粒子的压力。另一种是从流体到边界粒子的压力外推,但使用平滑粒子流体动力学(SPH)计算的梯度。我们鼓励基于梯度的外推比镜像更准确。我们进一步证明,我们提出的MLS梯度比边界处的SPH梯度更不容易出错。在我们的实验中,我们指出了先前方法中的工件。我们表明,与以前的方法相比,我们的方法可以显著减少这些伪影,从而使模拟步骤减少两倍。我们进一步提出具有挑战性和复杂的场景来说明所建议的边界处理的能力。•计算方法→物理模拟;大规模并行和高性能仿真;
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MLS Pressure Extrapolation for the Boundary Handling in Divergence-Free SPH
We propose a novel method to predict pressure values at boundary particles in incompressible divergence-free SPH simulations (DFSPH). Our approach employs Moving Least Squares (MLS) to predict the pressure at boundary particles. Therefore, MLS computes hyperplanes that approximate the pressure field at the interface between fluid and boundary particles. We compare this approach with two previous techniques. One previous technique mirrors the pressure from fluid to boundary particles. The other one extrapolates the pressure from fluid to boundary particles, but uses a gradient that is computed with Smoothed Particle Hydrodynamics (SPH). We motivate that gradient-based extrapolation is more accurate than mirroring. We further motivate that our proposed MLS gradient is less error prone than the SPH gradient at the boundary. In our experiments, we indicate artifacts in previous approaches. We show that these artifacts are significantly reduced with our approach resulting in simulation steps that can be twice as large compared to previous methods. We further present challenging and complex scenarios to illustrate the capabilities of the proposed boundary handling. CCS Concepts •Computing methodologies → Physical simulation; Massively parallel and high-performance simulations;
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