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000867479 041__ $$aEnglish
000867479 1001_ $$0P:(DE-Juel1)165948$$aLintermann, Andreas$$b0$$ufzj
000867479 1112_ $$a13th Teraflop Workshop$$cTohuku$$d2010-10-21 - 2010-10-22$$wJapan
000867479 245__ $$aInvestigations of Nasal Cavity Flows based on a Lattice-Boltzmann Method
000867479 260__ $$aBerlin, Heidelberg$$bSpringer Berlin Heidelberg$$c2012
000867479 29510 $$aHigh Performance Computing on Vector Systems 2011 / Resch, Michael (Editor)   ; Berlin, Heidelberg : Springer Berlin Heidelberg, 2012,  ; ISBN: 978-3-642-22243-6 ; doi:10.1007/978-3-642-22244-3
000867479 300__ $$a143-158
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000867479 520__ $$aAbstract Impaired respiration capabilities or a reduced sense of smell and taste are common for pathologically shaped nasal cavities. To analyze the flow in the human nasal cavity, simulations with a Lattice-Boltzmann Method (LBM) are carried out. This method is particularly suited to simulate flows in intricate geometries, it is efficient compared to solvers based on the Navier-Stokes equations, and straight forward to parallelize. A surface of the nasal cavity is extracted from Computer Tomography (CT) images and is used to automatically generate a hierarchically refined computational grid. Wall-bounded shear layers are highly resolved in contrast to re- gions of lower velocity gradients. In this way the overall number of cells is reduced and the computational efficency is improved. A mean volume flux of 125 ml/sec is prescribed, which results in a REYNOLDS number of Re = 766 based on the averaged velocity and the averaged hydraulic diameter of the nostrils of the nasal cavity. Different nasal cavities are investigated, previously selected from medical analysis. A performance analysis of the algorithm is carried out to show the scalability of the code. The findings verify that the LBM is a valuable tool to predict and analyze the flow in the human nasal cavity for the individual patient and that it is suited for High Performance Computing (HPC) due to its good scalability.
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000867479 7001_ $$0P:(DE-HGF)0$$aMeinke, Matthias$$b1
000867479 7001_ $$0P:(DE-HGF)0$$aSchröder, Wolfgang$$b2
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