Statistical inverse analysis and stochastic modeling of transition
摘要：
A computational method is introduced to infer statistical information on boundarylayer perturbations upstream of laminar-turbulent transition in a supersonic boundary layer. The method uses the intermittency function as a basis, which specifies the amount of time a flow is turbulent at a given streamwise location. The methods yields a joint probability density function for amplitude and frequency of boundary-layer perturbations upstream of transition. It relies on linear stability theory to link the probability density function with the intermittency. In order to infer parameters governing the function, we perform a statistical inverse analysis using the Markov chain Monte Carlo method. The approach is applied to a synthetic test case and to experimental data. 1.
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关键词：
Animals Animals, Newborn Rats Nervous System Neurons Nerve Growth Factors Drosophila Proteins Proto-Oncogene Proteins Nerve Tissue Proteins Embryonic and Fetal Development
会议名称：
43rd AIAA Fluid Dynamics Conference
会议时间：
2013/06/24
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