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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Kaman, T., Kaufman, R., Glimm, J., Sharp, D.H. (2012). Uncertainty Quantification for Turbulent Mixing Flows: Rayleigh-Taylor Instability. In: Dienstfrey, A.M., Boisvert, R.F. (eds) Uncertainty Quantification in Scientific Computing. WoCoUQ 2011. IFIP Advances in Information and Communication Technology, vol 377. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32677-6_14
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DOI: https://doi.org/10.1007/978-3-642-32677-6_14
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