e-space
Manchester Metropolitan University's Research Repository

    A parallel meshless dynamic cloud method on graphic processing units for unsteady compressible flows past moving boundaries

    Ma, ZH, Wang, H and Pu, SH (2015) A parallel meshless dynamic cloud method on graphic processing units for unsteady compressible flows past moving boundaries. Computer Methods in Applied Mechanics and Engineering, 285. ISSN 0045-7825

    [img]
    Preview

    Available under License In Copyright.

    Download (2MB) | Preview

    Abstract

    This paper presents an effort to implement a recently proposed meshless dynamic cloud method (Hong Wang et al., 2010) on modern high-performance graphic processing units (GPUs) with the compute unified device architecture (CUDA) programming model. Within the framework of the meshless method, clouds of points used as basic computational stencils are distributed in the whole flow domain. The spatial derivatives of the governing equations are discretised by the moving-least square scheme on every cloud of points. Roe’s approximate Riemann solver is adopted to compute the convective flux. A dual-time stepping approach, which iterates in physical and pseudo temporal spaces, is employed to obtain the time-accurate solution. Simulation of steady compressible flows over a fixed aerofoil is firstly carried out to verify the GPU implementation of the method. Then it is extended to compute unsteady flows past oscillatory aerofoils. Numerical outcomes are compared with experimental and/or other reference results to validate the method. Significant performance speedup of more than an order of magnitude is verified by the numerical results. Systematic analysis shows that GPU is more energy efficient than CPU for solving aerodynamic problems. This demonstrates the potential of the proposed method to solve fluid–structure interaction problems.

    Impact and Reach

    Statistics

    Activity Overview
    6 month trend
    374Downloads
    6 month trend
    348Hits

    Additional statistics for this dataset are available via IRStats2.

    Altmetric

    Repository staff only

    Edit record Edit record