Optimization of a turbulence model by using data assimilation

Hiroshi Kato, Shigeru Obayashi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This research investigates the effectiveness of optimization of the parameter values in the Spalart-Allmaras (SA) turbulence model applied to transonic flows. In the optimization, the ensemble Kalman filter which is one of data assimilation methods was employed. The optimization result showed the followings. The parameter values were estimated to weaken the production term and to enhance the collapse and diffusion terms compared to those of the original values. The simulation with the optimized values predicted the smaller turbulent eddy viscosity, and thus the friction drag was smaller than that with the original values. The computed pressure coefficients with the optimized values were agreed with experiment better than those with the original values.

Original languageEnglish
Title of host publicationECCOMAS 2012 - European Congress on Computational Methods in Applied Sciences and Engineering, e-Book Full Papers
Pages1542-1555
Number of pages14
Publication statusPublished - 2012 Dec 1
Event6th European Congress on Computational Methods in Applied Sciences and Engineering, ECCOMAS 2012 - Vienna, Austria
Duration: 2012 Sep 102012 Sep 14

Other

Other6th European Congress on Computational Methods in Applied Sciences and Engineering, ECCOMAS 2012
CountryAustria
CityVienna
Period12/9/1012/9/14

Keywords

  • Data assimilation
  • Ensemble Kalman filter
  • Optimization
  • Turbulence model

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Applied Mathematics

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  • Cite this

    Kato, H., & Obayashi, S. (2012). Optimization of a turbulence model by using data assimilation. In ECCOMAS 2012 - European Congress on Computational Methods in Applied Sciences and Engineering, e-Book Full Papers (pp. 1542-1555)