Keywords | Bypass Transition, Flow Instability, Laminar Flow, Turbulence Modeling, Turbulent Flow |
Background | The use of simulations, particularly computational fluid dynamics (CFD), is having an increasing role in design decisions for marine vehicles and aircraft. The typical high level simulation, for example at the level of the Reynolds Averaged Navier-Stokes (RANS) equations, assumes the flow is fully turbulent. This assumption of the flow being fully turbulent is appropriate for full scale ships, submarines and aircraft and RANS codes can provide good predictions of full scale performance. However, the assumption of fully turbulent flow is not appropriate for smaller vehicles, such as unmanned vehicles, where large transitional regions can exist.
The prediction of transitional flows has been difficult. As mentioned RANS level predictions typically assume the flow is fully turbulent. Models do exist for the prediction of transitional flows with RANS codes. In addition, large eddy simulation (LES) is becoming applicable to practical flows at higher Reynolds numbers and LES codes have an ability to predict transitional flows. However, the capability of these tools to predict transitional flows of relevance to the NATO community needs to be assessed as this directly relates to the ability to predict the performance of unmanned vehicles.
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Objectives | In this effort, an assessment will be made of existing capabilities of CFD codes to predict transitional flows of interest as well as an assessment of relevant data for validation of transition prediction. This will include the use of RANS as well as LES codes for transition prediction. The effort will also include the evaluation of transition specific turbulence models. Finally, transitional experimental data of relevance for validation of the methods will be identified. The goal is to be able to provide information on what the state of the art is for the prediction of transitional flows and guidance for the NATO community on predicting these flows for configurations relevant to unmanned vehicle design and evaluation. |
