TY - JOUR

T1 - A new efficient algorithm for computational aeroacoustics on parallel processors

AU - Özyörük, Yusuf

AU - Long, Lyle N.

N1 - Funding Information:
The authors gratefully acknowledge support from NASA Langley Research Center Grant Number NAG-1-1367. Gratitude is also extended to K. Uenishi of General Electric Aircraft Engines, Cincinnati, OH, for providing the C1A engine inlet surface geometry. The use of the computational resources of the Numerical Aerodynamics Simulation Program at the NASA Ames Research Center and the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign is also acknowledged.

PY - 1996/4

Y1 - 1996/4

N2 - One of the great challenges in computational physics is the prediction of flow associated noise, where the quantities of interest, namely the sound waves can be at high frequencies and are usually orders of magnitude smaller in magnitude than the mean quantities. In order to numerically resolve such small scales governed by the fluid dynamics equations, high resolution schemes are required. Thus solutions of flow noise problems are computationally intensive. An efficient, hybrid, data parallel computational aeroacoustics algorithm has been developed for the prediction of noise radiation and scattering from three-dimensional geometries. The algorithm solves the Euler/Navier-Stokes equations in the interior and nonreflecting boundary conditions on the outer boundaries. A moving surface Kirchhoff method is coupled to the flow solver for far-field predictions. The algorithm uses standard time and spatial discretization techniques but utilizes several new optimization strategies that are highly suitable for single zone solutions on data parallel processors. One strategy, for example, enables simultaneous residual evaluations of the interior and far-field nonreflecting boundary conditions equations, reducing the computational effort spent on them by approximately 60% CPU time savings. The algorithms for the flow solver and the Kirchhoff method and their coupling are described in this paper, and results for some example radiation and scattering problems are presented.

AB - One of the great challenges in computational physics is the prediction of flow associated noise, where the quantities of interest, namely the sound waves can be at high frequencies and are usually orders of magnitude smaller in magnitude than the mean quantities. In order to numerically resolve such small scales governed by the fluid dynamics equations, high resolution schemes are required. Thus solutions of flow noise problems are computationally intensive. An efficient, hybrid, data parallel computational aeroacoustics algorithm has been developed for the prediction of noise radiation and scattering from three-dimensional geometries. The algorithm solves the Euler/Navier-Stokes equations in the interior and nonreflecting boundary conditions on the outer boundaries. A moving surface Kirchhoff method is coupled to the flow solver for far-field predictions. The algorithm uses standard time and spatial discretization techniques but utilizes several new optimization strategies that are highly suitable for single zone solutions on data parallel processors. One strategy, for example, enables simultaneous residual evaluations of the interior and far-field nonreflecting boundary conditions equations, reducing the computational effort spent on them by approximately 60% CPU time savings. The algorithms for the flow solver and the Kirchhoff method and their coupling are described in this paper, and results for some example radiation and scattering problems are presented.

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U2 - 10.1006/jcph.1996.0084

DO - 10.1006/jcph.1996.0084

M3 - Article

AN - SCOPUS:0030117065

VL - 125

SP - 135

EP - 149

JO - Journal of Computational Physics

JF - Journal of Computational Physics

SN - 0021-9991

IS - 1

ER -