We propose MiNNIE, a simple yet comprehensive framework for real-time simulation of nonlinear near-incompressible elastics. To avoid the common volumetric locking issues at high Poisson's ratios of linear finite element methods (FEM), we build MiNNIE upon a mixed FEM framework and further incorporate a pressure stabilization term to ensure excellent convergence of multigrid solvers. Our pressure stabilization strategy injects bounded influence on nodal displacement which can be eliminated using a quasiNewton method. MiNNIE has a specially tailored GPU multigrid solver including a modified skinning-space interpolation scheme, a novel vertex Vanka smoother, and an efficient dense solver using Schur complement. MiNNIE supports various elastic material models and simulates them in real-time, supporting a full range of Poisson's ratios up to 0.5 while handling large deformations, element inversions, and self-collisions at the same time.

中文翻译：

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MiNNIE：一种用于实时模拟非线性近不可压缩弹性的混合多重网格方法


我们提出了 MiNNIE，这是一个简单而全面的框架，用于实时模拟非线性近不可压缩弹性。为了避免线性有限元法 （FEM） 的高泊松比下常见的体积锁定问题，我们在混合 FEM 框架上构建了 MiNNIE，并进一步加入了压力稳定项，以确保多网格求解器的出色收敛。我们的压力稳定策略对节点位移施加有限影响，这可以使用准牛顿方法消除。MiNNIE 具有专门定制的 GPU 多重网格求解器，包括改进的蒙皮空间插值方案、新颖的顶点 Vanka 平滑器以及使用 Schur 补码的高效密集求解器。MiNNIE 支持各种弹性材料模型并对其进行实时仿真，支持高达 0.5 的全范围泊松比，同时处理大变形、单元反转和自碰撞。