Robust Node Generation for Meshfree Discretizations on Irregular Domains and Surfaces
June 08, 2018 Β· Declared Dead Β· π SIAM Journal on Scientific Computing
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Authors
Varun Shankar, Robert M. Kirby, Aaron L. Fogelson
arXiv ID
1806.02972
Category
cs.DS: Data Structures & Algorithms
Cross-listed
math.NA
Citations
49
Venue
SIAM Journal on Scientific Computing
Last Checked
3 months ago
Abstract
We present a new algorithm for the automatic one-shot generation of scattered node sets on irregular 2D and 3D domains using Poisson disk sampling coupled to novel parameter-free, high-order parametric Spherical Radial Basis Function (SBF)-based geometric modeling of irregular domain boundaries. Our algorithm also automatically modifies the scattered node sets locally for time-varying embedded boundaries in the domain interior. We derive complexity estimates for our node generator in 2D and 3D that establish its scalability, and verify these estimates with timing experiments. We explore the influence of Poisson disk sampling parameters on both quasi-uniformity in the node sets and errors in an RBF-FD discretization of the heat equation. In all cases, our framework requires only a small number of "seed" nodes on domain boundaries. The entire framework exhibits O(N) complexity in both 2D and 3D.
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