Uncertainty Quantification for Turbulent Mixing Flows: Rayleigh-Taylor Instability

Abstract : Uncertainty Quantification (UQ) for fluid mixing depends on the length scales for observation: macro, meso and micro, each with its own UQ requirements. New results are presented here for macro and micro observables. For the micro observables, recent theories argue that convergence of numerical simulations in Large Eddy Simulations (LES) should be governed by space-time dependent probability distribution functions (PDFs, in the present context, Young measures) which satisfy the Euler equation. From a single deterministic simulation in the LES, or inertial regime, we extract a PDF by binning results from a space time neighborhood of the convergence point. The binned state values constitute a discrete set of solution values which define an approximate PDF. The convergence of the associated cumulative distribution functions (CDFs) are assessed by standard function space metrics.
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Andrew M. Dienstfrey; Ronald F. Boisvert. 10th Working Conference on Uncertainty Quantification in Scientific Computing (WoCoUQ), Aug 2011, Boulder, CO, United States. Springer, IFIP Advances in Information and Communication Technology, AICT-377, pp.212-225, 2012, Uncertainty Quantification in Scientific Computing. 〈10.1007/978-3-642-32677-6_14〉
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T. Kaman, R. Kaufman, J. Glimm, D. Sharp. Uncertainty Quantification for Turbulent Mixing Flows: Rayleigh-Taylor Instability. Andrew M. Dienstfrey; Ronald F. Boisvert. 10th Working Conference on Uncertainty Quantification in Scientific Computing (WoCoUQ), Aug 2011, Boulder, CO, United States. Springer, IFIP Advances in Information and Communication Technology, AICT-377, pp.212-225, 2012, Uncertainty Quantification in Scientific Computing. 〈10.1007/978-3-642-32677-6_14〉. 〈hal-01518667〉

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