4.7 Article

A Chebyshev-based rectangular-polar integral solver for scattering by geometries described by non-overlapping patches

期刊

JOURNAL OF COMPUTATIONAL PHYSICS
卷 421, 期 -, 页码 -

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jcp.2020.109740

关键词

Integral equations; Scattering problem; High-order accuracy; CAD representation; Rectangular-polar method; General geometries

资金

  1. NSF
  2. AFOSR
  3. DARPA [DMS-1714169, FA9550-15-1-0043, HR00111720035]
  4. NSSEFF Vannevar Bush Fellowship [N00014-16-1-2808]

向作者/读者索取更多资源

This paper introduces a high-order-accurate strategy for integration of singular kernels and edge-singular integral densities that appear in the context of boundary integral equation formulations for the problem of acoustic scattering. In particular, the proposed method is designed for use in conjunction with geometry descriptions given by a set of arbitrary non-overlapping logically-quadrilateral patches-which makes the algorithm particularly well suited for computer-aided design (CAD) geometries. Fejer's first quadrature rule is incorporated in the algorithm, to provide a spectrally accurate method for evaluation of contributions from far integration regions, while highly-accurate precomputations of singular and near-singular integrals over certain surface patches together with two-dimensional Chebyshev transforms and suitable surface-varying rectangular-polar changes of variables, are used to obtain the contributions for singular and near-singular interactions. The overall integration method is then used in conjunction with the linear- algebra solver GMRES to produce solutions for sound-soft open- and closed-surface scattering obstacles, including an application to an aircraft described by means of a CAD representation. The approach is robust, fast, and highly accurate: use of a few points per wavelength suffices for the algorithm to produce far-field accuracies of a fraction of a percent, and slight increases in the discretization densities give rise to significant accuracy improvements. (C) 2020 Elsevier Inc. All rights reserved.

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