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5.4.16 Xiao

Topic: 75th NIA CFD Seminar: A Data-Driven, Physics-Informed Approach towards Predictive Turbulence Modeling

Date: Wednesday, May 4, 2016

Time: 11:00am-noon (EST)

Room: NIA, Rm137

Speaker: Heng Xiao

Abstract: Despite their well-known limitations, Reynolds-Averaged Navier-Stokes (RANS) models are still the workhorse tools for engineering turbulent flow simulations. In this talk we present a data-driven, physics-informed approach for quantifying and reducing model-form uncertainties in RANS simulations. The framework utilizes an ensemble-based Bayesian inference method to incorporate all sources of available information, including empirical prior knowledge, physical constraints (e.g., realizability, smoothness, and symmetric), and available observation data. When there are no available data on the flow to be predicted, we showed that the Reynolds stress discrepancy can be calibrated on related flows where data are available. This finding has profound physical and modeling implications, i.e., the errors in RANS modeled Reynolds stresses are not random, but can be well explained by the mean flow features. This work demonstrates the potential of the data-driven predictive turbulence modeling approach based on standard RANS models, which is an alternative to advanced RANS models.

Bio: Dr. Heng Xiao is an Assistant Professor in the Department of Aerospace and Ocean Engineering at Virginia Tech. He holds a bachelor’s degree in Civil Engineering from Zhejiang University, China, a master’s degree in Mathematics from the Royal Institute of Technology (KTH), Sweden, and a Ph.D. degree in Civil Engineering from Princeton University, USA. Before joining Virginia Tech in 2013, he worked as a postdoctoral researcher at the Institute of Fluid Dynamics in ETH Zurich, Switzerland, from 2009 to 2012. His current research interests lie in model uncertainty quantification in turbulent flow simulations. He is also interested in developing novel algorithms for high-fidelity simulations of particle-laden flows with application to sediment transport problems. More information can be found in the manuscripts below or from the presenter’s website:
https://sites.google.com/a/vt.edu/hengxiao/papers

Additional information, including the webcast link, can be found at the NIA CFD Seminar website: http://www.hiroakinishikawa.com/niacfds/index.html

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