Deterministic point inclusion methods for computational applications with complex geometry

A. Khamayseh, A. Kuprat
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引用次数: 8

Abstract

A fundamental problem in computation is finding practical and efficient algorithms for determining if a query point is contained within a model of a three-dimensional solid. The solid is modeled using a general boundary representation that can contain polygonal elements and/or parametric patches. We have developed two such algorithms: the first is based on a global closest feature query, and the second is based on a local intersection query. Both algorithms work for two- and three-dimensional objects. This paper presents both algorithms, as well as the spatial data structures and queries required for efficient implementation of the algorithms. Applications for these algorithms include computational geometry, mesh generation, particle simulation, multiphysics coupling, and computer graphics. These methods are deterministic in that they do not involve random perturbations of diagnostic rays cast from the query point in order to avoid 'unclean' or 'singular' intersections of the rays with the geometry. Avoiding the necessity of such random perturbations will become increasingly important as geometries become more convoluted and complex.
复杂几何计算应用的确定性点包含方法
计算中的一个基本问题是找到实用而有效的算法来确定查询点是否包含在三维实体的模型中。该实体使用一般的边界表示进行建模,该边界表示可以包含多边形元素和/或参数块。我们已经开发了两种这样的算法:第一种是基于全局最接近特征查询,第二种是基于局部交集查询。这两种算法都适用于二维和三维物体。本文介绍了这两种算法,以及有效实现算法所需的空间数据结构和查询。这些算法的应用包括计算几何、网格生成、粒子模拟、多物理场耦合和计算机图形学。这些方法是确定性的,因为它们不涉及从查询点投射的诊断射线的随机扰动,以避免射线与几何形状的“不洁”或“奇异”相交。随着几何图形变得越来越复杂,避免这种随机扰动的必要性将变得越来越重要。
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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