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Published in: Journal of Scientific Computing 1/2018

30-04-2018

Shock Regularization with Smoothness-Increasing Accuracy-Conserving Dirac-Delta Polynomial Kernels

Authors: B. W. Wissink, G. B. Jacobs, J. K. Ryan, W. S. Don, E. T. A. van der Weide

Published in: Journal of Scientific Computing | Issue 1/2018

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Abstract

A smoothness-increasing accuracy conserving filtering approach to the regularization of discontinuities is presented for single domain spectral collocation approximations of hyperbolic conservation laws. The filter is based on convolution of a polynomial kernel that approximates a delta-sequence. The kernel combines a kth order smoothness with an arbitrary number of m zero moments. The zero moments ensure a mth order accurate approximation of the delta-sequence to the delta function. Through exact quadrature the projection error of the polynomial kernel on the spectral basis is ensured to be less than the moment error. A number of test cases on the advection equation, Burger’s equation and Euler equations in 1D and 2D show that the filter regularizes discontinuities while preserving high-order resolution away from a discontinuity.

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Metadata
Title
Shock Regularization with Smoothness-Increasing Accuracy-Conserving Dirac-Delta Polynomial Kernels
Authors
B. W. Wissink
G. B. Jacobs
J. K. Ryan
W. S. Don
E. T. A. van der Weide
Publication date
30-04-2018
Publisher
Springer US
Published in
Journal of Scientific Computing / Issue 1/2018
Print ISSN: 0885-7474
Electronic ISSN: 1573-7691
DOI
https://doi.org/10.1007/s10915-018-0719-5

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