A hybrid adaptive-gridding immersed-boundary lattice Boltzmann method for viscous flow simulations

Xixiong Guo, Jieke Yao, Chengwen Zhong and Jun Cao

Applied Mathematics and Computation, 2015, vol. 267, issue C, 529-553

Abstract: Robust use of adaptive mesh refinement (AMR) techniques in the immersed-boundary (IB) lattice Boltzmann method (LBM) framework is seldom reported, but indeed expected owing to its foreseeable broad applicability and computational efficiency. This study is aimed at developing a highly hybrid computational framework that seamlessly incorporates the AMR algorithm in the IB–LBM approach, so that challenging problems, including the case of an obstacle that moves through a flowing fluid, can be numerically investigated. Owing to the feedback forcing based IB model, the advantages, such as simple mechanics principle, explicit interpolations, and inherent satisfaction of no-slip boundary condition for solid surfaces, are fully exhibited. Additionally, the “bubble” function is employed in the local mesh refinement process so that, for newly generated nodes belonging to a region with overlapping coarse and fine cells, the solution of second-order accuracy can be obtained only through the spatial interpolation but no temporal interpolation. With simulation interests in both steady and unsteady flows around a single cylinder and bi-cylinders, a number of test cases performed in this study have demonstrated the usefulness and effectiveness of the present hybrid AMR–IB–LBM approach.

Keywords: Lattice Boltzmann method; Immersed boundary method; Feedback forcing model; Adaptive mesh refinement; “Bubble” interpolation function (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:267:y:2015:i:c:p:529-553

DOI: 10.1016/j.amc.2015.01.082

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