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  • 1990-1994  (3)
  • 1
    Electronic Resource
    Electronic Resource
    New York, NY : American Institute of Physics (AIP)
    Physics of Fluids 4 (1992), S. 1759-1766 
    ISSN: 1089-7666
    Source: AIP Digital Archive
    Topics: Physics
    Notes: The pressure-gradient–velocity correlation and return to isotropy term in the Reynolds stress transport equation are analyzed using the Yakhot–Orszag renormalization group. The perturbation series for the relevant correlations, evaluated to lowest order in the ε expansion of the Yakhot–Orszag theory, are infinite series in tensor product powers of the mean velocity gradient and its transpose. Formal lowest-order Padé approximations to the sums of these series produce a rapid pressure strain model of the form proposed by Launder et al. [J. Fluid Mech. 68, 537 (1975)], and a return to isotropy model of the form proposed by Rotta [Z. Phys. 129, 547 (1951)]. In both cases, the model constants are computed theoretically. The predicted Reynolds stress ratios in simple shear flows are evaluated and compared with experimental data. The possibility is discussed of deriving higher-order nonlinear models by approximating the sums more accurately.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Oxford, UK : Blackwell Publishing Ltd
    Annals of the New York Academy of Sciences 693 (1993), S. 0 
    ISSN: 1749-6632
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Natural Sciences in General
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    Springer
    Annals of operations research 27 (1990), S. 175-212 
    ISSN: 1572-9338
    Keywords: Monte Carlo optimization ; optimization in simulation ; sample path analysis
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Notes: Abstract We present a method for deriving theoptimal solution of a class of mathematical programming problems, associated with discrete-event systems and in particular with queueing models, while using asingle sample path (single simulation experiment) from the underlying process. Our method, called thescore function method, is based on probability measure transformation derived from the efficient score process and generating statistical counterparts to the conventional deterministic optimization procedures (e.g. Lagrange multipliers, penalty functions, etc.). Applications of our method to optimization of various discrete-event systems are presented, and numerical results are given.
    Type of Medium: Electronic Resource
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