Non-oscillatory forward-in-time integrators for viscous incompressible flows past a sphere

JOURNAL OF COMPUTATIONAL PHYSICS

卷:386

Article

Szmelter, Joanna¹  Smolarkiewicz, Piotr K.²  Zhang, Zhao³  Cao, Zhixin¹ 

[1] Loughborough Univ, Loughborough LE11 3TU, Leics, England

[2] European Ctr Medium Range Weather Forecasts, Reading RG2 9AX, Berks, England

[3] Heriot Watt Univ, Edinburgh EH14 4AS, Midlothian, Scotland

关键词: Multidimensional high resolution schemes;    Incompressible viscous flows;    Stably stratified flows;    MPDATA;    Anelastic flows;    Upwind approximations;   

DOI  :  10.1016/j.jcp.2019.02.010

来源: Elsevier

【 摘 要 】

A non-oscillatory forward-in-time (NFT) integrator is developed to provide solutions of the Navier-Stokes equations for incompressible flows. Simulations of flows past a sphere are chosen as a benchmark representative of a class of engineering flows past obstacles. The methodology is further extended to moderate Reynolds number, stably stratified flows under gravity, for Froude numbers that typify the characteristic regimes of natural flows past distinct isolated features of topography in weather and climate models. The key elements of the proposed method consist of the Multidimensional Positive Definite Advection Transport Algorithm (MPDATA) and a robust non-symmetric Krylov-subspace elliptic solver. The solutions employ a finite volume spatial discretisation on unstructured and hybrid meshes and benefit from a collocated arrangement of all flow variables while being inherently stable. The development includes the implementation of viscous terms with the detached-eddy simulation (DES) approach employed for turbulent flows. Results demonstrate that the proposed methodology enables direct comparisons of the numerical solutions with corresponding laboratory studies of viscous and stratified flows while illustrating accuracy, robustness and flexibility of the NFT schemes. The presented simulations also offer a better insight into stably stratified flows past a sphere. (C) 2019 Elsevier Inc. All rights reserved.

【 授权许可】

Free