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@PHDTHESIS{Lintermann:867476,
      author       = {Lintermann, Andreas},
      title        = {{N}asal {C}avity {F}lows {U}sing {L}attice-{B}oltzmann
                      {M}ethods on {H}igh {P}erformance {C}omputers},
      school       = {RWTH Aachen University},
      type         = {Dissertation},
      address      = {Aachen},
      publisher    = {Apprimus Verlag},
      reportid     = {FZJ-2019-06115},
      isbn         = {978-3-86359-244-8},
      pages        = {147 p.},
      year         = {2014},
      note         = {Dissertation, RWTH Aachen University, 2014},
      abstract     = {Within this work the flow in the human nasal cavity is
                      investigated using Computa-tional Fluid Dynamics (CFD)
                      methods. Different approaches exist to numerically sim-ulate
                      flows, e.g., Finite-Volume Methods (FVM), and Finite-Element
                      Methods (FEM). However, when it comes to handling complex
                      and intricate geometries like the nasal cavity, the
                      Lattice-Boltzmann Method (LBM) excels due to its conductive
                      paralleliza-bility and its straight-forward way to treat
                      arbitrarily shaped boundaries as they ap-pear in biomedical
                      applications. Therefore, such an LBM is used to simulate and
                      analyze the flow in three pathologically distinct nasal
                      cavities in depth to understand the physics of such flows. A
                      new categorization procedure for nasal cavities based on the
                      respiration and heating capability is established. This
                      categorization method is substantiated by the analysis of
                      the inspiratory pressure loss, wall-shear stress, heat flux,
                      and existing vortical structures and their influence on the
                      aforementioned parameters. Such a classification integrates
                      into Virtual Surgery environments, supports an a priori
                      decision process on surgical interventions, and is a
                      potential method to evaluate surgical rhinological
                      procedures by juxtaposing before and after surgery results.
                      To resolve fine-grained flow structures in such simulations
                      and to accurately predict the wall-shear stress and heat
                      flux, computational meshes with a large number of cells are
                      necessary. The construction of such meshes is a challenging
                      task due to the restricted amount of available local memory.
                      Additionally, high grid resolutions require a generation in
                      parallel. The increase of computational power and efficiency
                      of today's CPUs in multi-core distributed-memory systems in
                      High Performance Computing (HPC) offers new chances in CFD.
                      This enables to efficiently generate computational meshes in
                      parallel and to perform unsteady high-fidelity simulations
                      of complex flows in intricate geometries in a reasonable
                      amount of time. In this thesis a new parallel and robust
                      algorithm to automatically generate hierarchical Cartesian
                      meshes, as they are used by the LBM, is presented. The
                      algorithm is analyzed in its parallel performance on HPC
                      systems and scales up to hundreds of thousands of processes.
                      It overcomes the dependence on manual input or an imbalance
                      on the process level which other approaches suffer from.
                      This way, the algorithm enables to generate O(10¹¹) cells
                      in only a few seconds.},
      pnm          = {511 - Computational Science and Mathematical Methods
                      (POF3-511)},
      pid          = {G:(DE-HGF)POF3-511},
      typ          = {PUB:(DE-HGF)3 / PUB:(DE-HGF)11},
      url          = {https://juser.fz-juelich.de/record/867476},
}