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A direct-forcing embedded-boundary method with adaptive mesh refinement for fluid-structure interaction problems

delete2010-09-01
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PRE
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M
Marcos Vanella
P
Patrick Rabenold
E
Elias Balaras *
DOI:10.1016/j.jcp.2010.05.003delete
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摘要

摘要

En 中文
In the present work we developed a structured adaptive mesh refinement (S-AMR) strategy for fluid-structure interaction problems in laminar and turbulent incompressible flows. The computational grid consists of a number of nested grid blocks at different refinement levels. The coarsest grid blocks always cover the entire computational domain, and local refinement is achieved by the bisection of selected blocks in every coordinate direction. The grid topology and data-structure is managed using the Paramesh toolkit. The filtered Navier-Stokes equations for incompressible flow are advanced in time using an explicit second-order projection scheme, where all spatial derivatives are approximated using second-order central differences on a staggered grid. For transitional and turbulent flow regimes the large-eddy simulation (LES) approach is used, where special attention is paid on the discontinuities introduced by the local refinement. For all the fluid-structure interaction problems reported in this study the complete set of equations governing the dynamics of the flow and the structure are simultaneously advanced in time using a predictor-corrector strategy. An embedded-boundary method is utilized to enforce the boundary conditions on a complex moving body which is not aligned with the grid lines. Several examples of increasing complexity are given to demonstrate the robustness and accuracy of the proposed formulation. (C) 2010 Elsevier Inc. All rights reserved.
Keyword:
Cartesian grids
Finite-difference method
Adaptive mesh refinement
Immersed-boundary method
Fluid-structure interaction
Large-eddy simulation
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期刊

Journal of Computational Physics 封面图
Journal of Computational Physics
IF:
3.8
论文数:
1.6W
被引数:
7.4W

机构

University System of Maryland 封面图
University System of Maryland
学者数:
6.5W
论文数: 5.6W
被引数: 113
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