Direct numerical simulation of particulate flows with an overset grid method
Journal of Computational Physics
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Koblitz, A., Lovett, S., Nikiforakis, N., & Henshaw, W. (2017). Direct numerical simulation of particulate flows with an overset grid method. Journal of Computational Physics, 343 414-431. https://doi.org/10.1016/j.jcp.2017.04.058
We evaluate an efficient overset grid method for two-dimensional and three-dimensional particulate flows for small numbers of particles at finite Reynolds number. The rigid particles are discretised using moving overset grids overlaid on a Cartesian background grid. This allows for strongly-enforced boundary conditions and local grid refinement at particle surfaces, thereby accurately capturing the viscous boundary layer at modest computational cost. The incompressible Navier–Stokes equations are solved with a fractional-step scheme which is second-order-accurate in space and time, while the fluid–solid coupling is achieved with a partitioned approach including multiple sub-iterations to increase stability for light, rigid bodies. Through a series of benchmark studies we demonstrate the accuracy and efficiency of this approach compared to other boundary conformal and static grid methods in the literature. In particular, we find that fully resolving boundary layers at particle surfaces is crucial to obtain accurate solutions to many common test cases. With our approach we are able to compute accurate solutions using as little as one third the number of grid points as uniform grid computations in the literature. A detailed convergence study shows a 13-fold decrease in CPU time over a uniform grid test case whilst maintaining comparable solution accuracy.
particulate flow, overset grids, direct numerical simulation, incompressible flow
This work was supported by contracts from the U.S. Department of Energy ASCR Applied Math Program under grant AC52-07NA27344; the National Science Foundation under grant DMS-1519934; the Schlumberger Gould Research Centre under grant RG78221; the EPSRC Centre for Doctoral Training in Computational Methods for Materials Science under grant EP/L015552/1.
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External DOI: https://doi.org/10.1016/j.jcp.2017.04.058
This record's URL: https://www.repository.cam.ac.uk/handle/1810/266273
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