An adaptive multilevel wavelet framework for scale-selective WENO reconstruction schemes

作者：Maulik R; San O^*; Behera R

来源：International Journal for Numerical Methods in Fluids, 2018, 87(5): 239-269.

DOI：10.1002/fld.4489

• adaptive mesh refinement
• compact orthogonal wavelets
• finite volume framework
• multiresolution analysis
• scale-selective dissipation
• WENO reconstruction

We put forth a dynamic computing framework for scale-selective adaptation of weighted essential nonoscillatory (WENO) schemes for the simulation of hyperbolic conservation laws exhibiting strong discontinuities. A multilevel wavelet-based multiresolution procedure, embedded in a conservative finite volume formulation, is used for a twofold purpose. (i) a dynamic grid adaptation of the solution field for redistributing grid points optimally (in some sense) according to the underlying flow structures, and (ii) a dynamic minimization of the in built artificial dissipation of WENO schemes. Taking advantage of the structure detection properties of this multiresolution algorithm, the nonlinear weights of the conventional WENO implementation are selectively modified to ensure lower dissipation in smoother areas. This modification is implemented through a linear transition from the fifth-order upwind stencil at the coarsest regions of the adaptive grid to a fully nonlinear fifth-order WENO scheme at areas of high irregularity. Therefore, our computing algorithm consists of a dynamic grid adaptation strategy, a scale-selective state reconstruction, a conservative flux calculation, and a total variation diminishing Runge-Kutta scheme for time advancement. Results are presented for canonical examples drawn from the inviscid Burgers, shallow water, Euler, and magnetohydrodynamic equations. Our findings represent a novel direction for providing a scale-selective dissipation process without a compromise on shock capturing behavior for conservation laws, which would be a strong contender for dynamic implicit large eddy simulation approaches.

• 出版日期2018-6-20