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Article
Chebyshev Optimized Approximate Deconvolution Models of Turbulence
Applied Mathematics and Computation
  • Iuliana Stanculescu, Nova Southeastern University
  • William Layton, University of Pittsburgh
Document Type
Article
Publication Date
2-1-2009
Keywords
  • Turbulence model,
  • LES,
  • Deconvolution
Disciplines
Abstract

If the Navier–Stokes equations are averaged with a local, spacial convolution type filter,ϕ¯¯¯=gδ∗ϕ, the resulting system is not closed due to the filtered nonlinear termuu¯¯¯¯. An approximate deconvolution operator DD is a bounded linear operator which satisfies

u=D(u¯¯)+O(δα), Turn MathJaxon

where δδ is the filter width and α⩾2α⩾2. Using a deconvolution operator as an approximate filter inverse, yields the closure

uu¯¯¯¯=D(u¯¯)D(u¯¯)¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯+O(δα). Turn MathJaxon

The residual stress of this model (and related models) depends directly on the deconvolution error,u−D(u¯¯). This report derives deconvolution operators yielding an effective turbulence model, which minimize the deconvolution error for velocity fields with finite kinetic energy. We also give a convergence theory of deconvolution as δ→0δ→0, an ergodic theorem as the deconvolution order N→∞N→∞, and estimate the increase in accuracy obtained by parameter optimization. The report concludes with numerical illustrations.

DOI
10.1016/j.amc.2008.11.022
Citation Information
Iuliana Stanculescu and William Layton. "Chebyshev Optimized Approximate Deconvolution Models of Turbulence" Applied Mathematics and Computation Vol. 208 Iss. 1 (2009) p. 106 - 118 ISSN: 0096-3003
Available at: http://works.bepress.com/iuliana-stanculescu/4/