Cyber Center

Integrative Computational Studies Seminar Series

May 1 @ 11:00 AM - 12:00 PM -

Integrative Computational Studies Seminar Series

The Lag RST Turbulence Model Applied to Vortical Flows

Matthew J. Churchfield

CS&E Doctoral Student

School of Aeronautics and Astronautics

Purdue University

Friday, May 1 2009

11:00 am - 12:00 pm

ARMS 3326




Turbulent vortical flows are common in nature and engineering applications--the motivating type of flow being wingtip vortices. Computational fluid dynamics (CFD) based on the Reynolds-averaged Navier-Stokes (RANS) equations is an increasingly used analysis tool. Therefore, RANS-based CFD must be able to predict turbulent vortices well. Many popular linear eddy viscosity turbulence models used with RANS-based CFD do not accurately predict the turbulence in vortices, often causing the mean flow to diffuse too quickly. Because such models rely on the Boussinesq approximation, they cannot account for the fact that the Reynolds stresses require time to react to the ever-changing mean strain-rates encountered along a helical vortex streamline. In other words, such models do not allow for misalignment of the principal axes of the Reynolds stress and strain rate tensors. Empirical rotation corrections improve mean predictions but are not a complete solution. More sophisticated models that can account for this “lag” in the Reynolds stresses also have problems in predicting the turbulence correctly. The lag RST model proposed by Olsen and Coakley, which is based on a two-equation k-ω model, shows promise in better predicting turbulent vortices than other current models with little added complexity over a two-equation model. The model has been applied to a q-vortex flow, which is an idealized representation of wingtip vortex flow. These results show that the model is able to control the excessive diffusion of mean momentum seen with linear eddy viscosity models. The lag RST model is also currently being applied to a more complex three dimensional wingtip vortex flow created by a wing in a wind tunnel.


Matthew J. Churchfield is a doctoral candidate in the School of Aeronautics and Astronautics, majoring in aerodynamics and specializing in 'Computational Engineering' through the Computational Science and Engineering (CS&E) program at Purdue University. He is the recipient of the CS&E-Lynn fellowship (2003-2004), the NSF Graduate Research Fellowship (2005-2008), the NSF GK-12 Fellowship (2008-2009), and CS&E Bilsland Dissertation Fellowship (2009). He is a native of Reno, Nevada and completed his bachelor’s degree in mechanical engineering there at the University of Nevada, Reno. Matt will go on to a post-doctoral research position at the National Renewable Energy Laboratory's National Wind Technology Center.

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