Constrained least-squares based adaptive-order finite-volume WENO scheme for the simulation of viscous compressible flows on unstructured grids

Dasika, S and Vaghani, D and Shukla, RK (2022) Constrained least-squares based adaptive-order finite-volume WENO scheme for the simulation of viscous compressible flows on unstructured grids. In: Journal of Computational Physics, 470 .

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Abstract

We develop a novel constrained least-squares technique for fourth-order weighted essentially non-oscillatory (WENO) polynomial reconstruction on general unstructured grids composed of curved-edged quadrilateral elements. Our technique relies on a segregation of the conditions that match the spatial averages of the candidate WENO polynomial and the reconstructed state variable over stencil-forming cells into two sets. The first set consists of exactly enforced linearly independent constraints that are applied only over the central cell and its edge-sharing neighbors. The second set consists of the remaining conditions and are enforced only approximately in a least-squares sense. We develop a specialized technique that reduces the computational burden associated with the numerical solution of the constrained least-squares system for the WENO interpolation coefficients. For a comparable computational expense, our constrained reconstruction approach yields pointwise estimates that are consistently more accurate than the conventional least-squares based estimates over a wide spectrum of spatial wavenumbers. This enhanced spectral resolution yields a significant, over two-fold increase in the accuracy with which unsteady smooth flow features, such as an advecting isentropic vortex, are captured over highly distorted curvilinear unstructured grids. Our constraint based reconstruction framework is generic, facilitates implementation of high-order boundary closures, and is amenable to large scale parallelization over several thousand CPU cores. Numerical tests over a range of inviscid and viscous flow configurations are presented to demonstrate the accuracy and robustness of our technique. Our constrained least-squares based adaptive WENO discretization faithfully captures intricate features that arise in strongly shocked, and highly unsteady and separated complex geometry flows. Our results suggest exact preservation of the match between the cell averages of the interpolant and the reconstructed state variable over the nearest neighbors to be quite an effective strategy that dramatically enhances the accuracy and spectral resolution of the high-order finite-volume reconstruction operation. © 2022 Elsevier Inc.

Item Type:	Journal Article
Publication:	Journal of Computational Physics
Publisher:	Academic Press Inc.
Additional Information:	The copyright for this article belongs to Academic Press Inc.
Keywords:	Interpolation; Polynomials, Adaptive orders; Condition; Constrained least squares; Essentially non-oscillatory; Finite-volume; High resolution; State-variables; Unstructured grid; Unstructured meshes; Weighted essentially non-oscillatory, Spectral resolution
Department/Centre:	Division of Mechanical Sciences > Mechanical Engineering
Date Deposited:	06 Oct 2022 06:20
Last Modified:	06 Oct 2022 06:20
URI:	https://eprints.iisc.ac.in/id/eprint/77133

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