Random Flow Generation Technique for Large Eddy Simulations and Particle-Dynamics Modeling

Author:

Smirnov A.1,Shi S.1,Celik I.1

Affiliation:

1. Department of Mechanical and Aerospace Engineering, West Virginia University, Morgantown, WV 26506-6106

Abstract

A random flow generation (RFG) technique is presented, which can be used for initial/inlet boundary generation in LES (Large-Eddy-Simulations) or particle tracking in LES/RANS (Reynolds-Averaged Navier-Stokes) computations of turbulent flows. The technique is based on previous methods of synthesizing divergence-free vector fields from a sample of Fourier harmonics and allows to generate non-homogeneous anisotropic flow field representing turbulent velocity fluctuations. It was validated on the cases of boundary layer and flat plate flows. Applications of the technique to LES and particle tracking are considered.

Publisher

ASME International

Subject

Mechanical Engineering

Reference27 articles.

1. Ravikanth, V., and Pletcher, R., 2000, AIAA Paper (2000-0542).

2. Akselvoll, K., and Moin, P., 1995, Technical Report TF-63, Stanford University.

3. Lund, T. , 1998, “Generation of Turbulent Inflow Data for Spatially-Developing Boundary Layer Simulations,” J. Comput. Phys., 140, p. 233233.

4. Lee, S., Lele, S., and Moin, P., 1992, “Simulation of Spatially Evolving Turbulence and the Applicability of Taylor’s Hypothesis in Compressible Flow,” Phys. Fluids A , 4, p. 15211521.

5. Zhou, O., and Leschziner, M., Sept. 1991, “A Time-Correlated Stochastic Model For Particle Dispersion in Anisotropic Turbulence,” 8-th Turbulent Shear Flows Symp., Munich.

Cited by 508 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3