Transition prediction in hypersonic regime on complex geometries with RANS-based models

L. Cutrone, A. Schettino, José I. Cardesa, Grégory Delattre, James G. Coder, Steven Qiang, E. Vogel, M. Choudhari

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In the near future, RANS computations will continue to play a significant role in the design of hypersonic vehicles with complex geometries. Therefore, it is imperative to continue testing, benchmarking, and refining the RANS models. In the present study, we evaluate RANS-like, transport equations-based models for predicting laminar-turbulent transition over a full-scale scale model of the BOLT flight configuration that was tested in the CUBRC LENS-II wind tunnel test facility. Based on the availability of the experimental results, comparisons are made between computations from several pre-existing transition models and Computational Fluid Dynamics (CFD) codes, with an emphasis on using the same computational meshes and flow conditions for all computations. The analysis covers the sensitivity of the transition predictions to the input parameters for five different transition models (four mainstream models designed for low-speed flows and a uniquely high-speed model), grid resolution, and the details of model implementation across three different flow solvers. The results show that the phenomenological models can describe significant aspects of the measured transition front. However, a number of additional improvements are required before these models can offer more reliable estimates of transition in high-speed flows.

Original languageEnglish (US)
Title of host publicationAIAA SciTech Forum and Exposition, 2024
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624107115
StatePublished - 2024
EventAIAA SciTech Forum and Exposition, 2024 - Orlando, United States
Duration: Jan 8 2024Jan 12 2024

Publication series

NameAIAA SciTech Forum and Exposition, 2024


ConferenceAIAA SciTech Forum and Exposition, 2024
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering

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