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Regressing the Size and Cost of Turbulent Cavity Flow Simulations

By Aldo Rona and Manuele Monti


This paper was published as Journal of Algorithms and Computational Technology, 2011, 5 (3), pp. 383-412. It is available from only entryA successful model of high Reynolds number cavity flows involves\ud reproducing the flow physics with adequate accuracy, given the available\ud computational resources. The process of planning high Reynolds number\ud cavity flow simulations is systematically reviewed to extract the dependence\ud of different programmer’s choices on the CFD mesh size and on the cost of\ud the computation.\ud This process has been broken down into five phases: i) description of the\ud problem in the continuous domain, ii) problem order reduction by turbulence\ud modelling, iii) discretization in space and time, iv) integration of the\ud governing equations, v) costing the numerical operations of the flow solver.\ud This paper examines the influence of each phase on the spectral width and\ud the grid density, which are the key CFD indicators that determine the cost\ud of the computation.\ud A dimensional analysis was conducted to separate the effects of the\ud geometry of the enclosure, the boundary layer resolution, the turbulence\ud model, and the numerical scheme order of accuracy. Regression analysis on\ud the non-dimensional groups of published cavity CFD simulations\ud determined the range of practical values used by current state-of-the-art\ud computations. This analysis is a useful tool for obtaining design trade-offs\ud by a multivariate optimization in cavity flow CFD and for estimating the order\ud of magnitude of the computational resources required by the simulations

Topics: Computational fluid dynamics, cavity flow, turbulence modelling, computational cost
Publisher: Multi-science Publishing Co Ltd
Year: 2011
DOI identifier: 10.1260/1748-3018.5.3.383
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