基于自适应有限元法的高效布料仿真

Jan Bender, Crispin Deul
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引用次数: 10

摘要

本文提出了一种基于√3细化方案的高效自适应布料仿真方法。我们的自适应布模型可以处理任意的三角形网格,而不局限于其他方法所要求的规则网格。以往的自适应布料仿真工作通常使用离散布料模型,如质量-弹簧系统与特定的细分方案相结合。这种模型的问题是,随着网格的细化,模拟不能收敛到正确的解。我们建议使用基于连续介质力学的布模型,因为连续模型不存在这个问题。为了进行有效的模拟,我们将线性弹性模型与旋转公式相结合。√3-subdivision方案的优点是它可以生成高质量的网格,而三角形的数量在每个细化步骤中只增加3倍。然而,原始方案只定义了网格细化。因此,我们还引入了一个扩展来支持仿真模型的粗化。我们提出的网格自适应可以有效地执行,因此不会造成太多的开销。在本文中,我们将展示通过我们的自适应方法可以获得显着的性能增益。
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Efficient Cloth Simulation Using an Adaptive Finite Element Method
In this paper we present an efficient adaptive cloth simulation based on the √ 3-refinement scheme. Our adaptive cloth model can handle arbitrary triangle meshes and is not restricted to regular grid meshes which are required by other methods. Previous works on adaptive cloth simulation often use discrete cloth models like mass-spring systems in combination with a specific subdivision scheme. The problem of such models is that the simulation does not converge to the correct solution as the mesh is refined. We propose to use a cloth model which is based on continuum mechanics since continuous models do not have this problem. In order to perform an efficient simulation we use a linear elasticity model in combination with a corotational formulation. The √ 3-subdivision scheme has the advantage that it generates high quality meshes while the number of triangles increases only by a factor of 3 in each refinement step. However, the original scheme only defines a mesh refinement. Therefore, we introduce an extension to support the coarsening of our simulation model as well. Our proposed mesh adaption can be performed efficiently and therefore does not cause much overhead. In this paper we will show that a significant performance gain can be achieved by our adaptive method.
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