Shape Aware Quadratures
Autor: | Vadim Shapiro, Vaidyanathan Thiagarajan |
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Rok vydání: | 2018 |
Předmět: |
Numerical Analysis
Engineering Physics and Astronomy (miscellaneous) Integrable system business.industry Applied Mathematics Divergence theorem 010103 numerical & computational mathematics Bivariate analysis 01 natural sciences Computer Science Applications Quadrature (mathematics) Numerical integration 010101 applied mathematics Computational Mathematics Modeling and Simulation Calculus Applied mathematics 0101 mathematics business Moment equations |
Zdroj: | Journal of Computational Physics. 374:1239-1260 |
ISSN: | 0021-9991 |
DOI: | 10.1016/j.jcp.2018.05.024 |
Popis: | With Shape Aware Quadratures (SAQ), for a given set of quadrature nodes, order, and domain of integration, the quadrature weights are obtained by solving a system of suitable moment fitting equations in least square sense. The moments in the moment equations are approximated over a simplified domain ( Ω 0 ) that is a reasonable approximation of the original domain (Ω) that are then corrected for the deviation of the shape of Ω 0 from Ω via shape correction factors. This idea was already successfully utilized in the Adaptively Weighted Numerical Integration (AW) method [1] , [2] , [3] , where moments were computed over simplified but homeomorphic domain and then corrected using first-order shape sensitivity, allowing efficient and accurate integration of integrable functions over arbitrary domains. With SAQ, more general shape correction factors can be derived based on a variety of sensitivity analysis techniques such as shape sensitivity (SSA) and topological sensitivity (TSA). Using the right kind/order of shape correction factors for moment approximation enables the resulting quadrature (from the moment fitting equations) to efficiently adapt to the shape of the original domain even in the presence of thousands of small features. We derive shape correction factors based on SSA and TSA of moment integrals. We also demonstrate the efficacy of SAQ in integrating bivariate/trivariate polynomials over several 2D/3D domains in the presence of small features. |
Databáze: | OpenAIRE |
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