适应性模拟的简单框架

E. Grinspun, P. Krysl, P. Schröder
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引用次数: 383

摘要

有限元求解器是仿真应用的基本组成部分;它们在计算机图形学、工程学和医学模拟中很常见。尽管自适应解算器在降低通常较高的模拟计算成本方面具有很大的价值,但它们并没有得到广泛的应用。事实上,构建自适应求解器可能是一项艰巨的任务,特别是对于3D有限元素。在本文中,我们介绍了一种新的方法来产生一致的、分层的、自适应的细化方法(CHARMS)。我们方法的基本原则是精炼基函数,而不是元素。这消除了许多与其他方法相关的实现难题,并且是一种独立于域维度(这里是2D和3D)、元素类型(例如三角形、四面体、四面体)和基函数顺序(分段线性、高阶b样条、循环细分等)的通用技术。(非)精化算法很简单,在数据结构支持方面要求很少。我们通过2D和3D示例展示了我们新方法的多功能性,包括医疗应用和薄壳动画。
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CHARMS: a simple framework for adaptive simulation
Finite element solvers are a basic component of simulation applications; they are common in computer graphics, engineering, and medical simulations. Although adaptive solvers can be of great value in reducing the often high computational cost of simulations they are not employed broadly. Indeed, building adaptive solvers can be a daunting task especially for 3D finite elements. In this paper we are introducing a new approach to produce conforming, hierarchical, adaptive refinement methods (CHARMS). The basic principle of our approach is to refine basis functions, not elements. This removes a number of implementation headaches associated with other approaches and is a general technique independent of domain dimension (here 2D and 3D), element type (e.g., triangle, quad, tetrahedron, hexahedron), and basis function order (piece-wise linear, higher order B-splines, Loop subdivision, etc.). The (un-)refinement algorithms are simple and require little in terms of data structure support. We demonstrate the versatility of our new approach through 2D and 3D examples, including medical applications and thin-shell animations.
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Session details: 3D acquisition and image based rendering Session details: Geometry Session details: Soft things Session details: Lighting and appearance Session details: Images and video
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