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    A dynamic mesh refinement technique for Lattice Boltzmann simulations on octree-like grids

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    Type
    Article
    Authors
    Neumann, Philipp
    Neckel, Tobias
    KAUST Grant Number
    UK-c0020
    Date
    2012-04-27
    Online Publication Date
    2012-04-27
    Print Publication Date
    2013-02
    Permanent link to this record
    http://hdl.handle.net/10754/597259
    
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    Abstract
    In this contribution, we present our new adaptive Lattice Boltzmann implementation within the Peano framework, with special focus on nanoscale particle transport problems. With the continuum hypothesis not holding anymore on these small scales, new physical effects - such as Brownian fluctuations - need to be incorporated. We explain the overall layout of the application, including memory layout and access, and shortly review the adaptive algorithm. The scheme is validated by different benchmark computations in two and three dimensions. An extension to dynamically changing grids and a spatially adaptive approach to fluctuating hydrodynamics, allowing for the thermalisation of the fluid in particular regions of interest, is proposed. Both dynamic adaptivity and adaptive fluctuating hydrodynamics are validated separately in simulations of particle transport problems. The application of this scheme to an oscillating particle in a nanopore illustrates the importance of Brownian fluctuations in such setups. © 2012 Springer-Verlag.
    Citation
    Neumann P, Neckel T (2012) A dynamic mesh refinement technique for Lattice Boltzmann simulations on octree-like grids. Comput Mech 51: 237–253. Available: http://dx.doi.org/10.1007/s00466-012-0721-y.
    Sponsors
    The work presented in this contribution was supported by the Munich Centre of Advanced Computing (MAC)<SUP>2</SUP> and the Faculty Graduate Centre CeDoSIA<SUP>3</SUP> at Technische Universitat Munchen. This support is gratefully acknowledged. Besides, parts of this paper are based on work supported by Award No. UK-c0020 by the King Abdullah University of Science and Technology (KAUST).
    Publisher
    Springer Nature
    Journal
    Computational Mechanics
    DOI
    10.1007/s00466-012-0721-y
    ae974a485f413a2113503eed53cd6c53
    10.1007/s00466-012-0721-y
    Scopus Count
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