TY - CHAP
T1 - Overview of the AFT Model for Transition Prediction in Complex Aerodynamic Flows
AU - Coder, James G.
N1 - Funding Information:
Acknowledgements The development and maturation of the amplification factor transport model framework has been financially supported through a variety of sources, including the United States Department of Defense NDSEG program, the Office of Naval Research, the US Army Vertical Lift Research Centers of Excellence, and NASA. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the funding agencies.
Funding Information:
The development and maturation of the amplification factor transport model framework has been financially supported through a variety of sources, including the United States Department of Defense NDSEG program, the Office of Naval Research, the US Army Vertical Lift Research Centers of Excellence, and NASA. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the funding agencies. Special thanks is extended to Dr. Mark D. Maughmer of the Pennsylvania State University for encouraging and advising the original development of the AFT model.
Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - For many aerodynamic flows of practical interest, prediction of laminar-turbulent transition from first principles is a difficult, if not impossible, undertaking. These flows are often characterized by high Reynolds numbers, geometric complexities, and inherent unsteadiness, which limits the ability to perform direct numerical simulation of the transition processes or to perform detailed stability calculations against a base flow. In response to this and other flow simulation needs, there has been increased interest by the aerodynamics community in PDE-based transition models. Such models are generally phenomenological in nature and designed to estimate the path to transition using single-point correlations. The practical benefits of such models are that they can be fully integrated within a flow solver without an excessive increase in grid resolution requirements or sacrificing parallelization, and they can be applied to general three-dimensional configurations with minimal user intervention. An overview of these PDE-based models is provided, and, in particular, the amplification factor transport (AFT) model developed by the author. The AFT model is rooted in linear stability theory and it has been successfully applied to a wide range of engineering applications. The model formulation is discussed, and key results are included highlighting the model’s predictive capabilities.
AB - For many aerodynamic flows of practical interest, prediction of laminar-turbulent transition from first principles is a difficult, if not impossible, undertaking. These flows are often characterized by high Reynolds numbers, geometric complexities, and inherent unsteadiness, which limits the ability to perform direct numerical simulation of the transition processes or to perform detailed stability calculations against a base flow. In response to this and other flow simulation needs, there has been increased interest by the aerodynamics community in PDE-based transition models. Such models are generally phenomenological in nature and designed to estimate the path to transition using single-point correlations. The practical benefits of such models are that they can be fully integrated within a flow solver without an excessive increase in grid resolution requirements or sacrificing parallelization, and they can be applied to general three-dimensional configurations with minimal user intervention. An overview of these PDE-based models is provided, and, in particular, the amplification factor transport (AFT) model developed by the author. The AFT model is rooted in linear stability theory and it has been successfully applied to a wide range of engineering applications. The model formulation is discussed, and key results are included highlighting the model’s predictive capabilities.
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U2 - 10.1007/978-3-030-67902-6_29
DO - 10.1007/978-3-030-67902-6_29
M3 - Chapter
AN - SCOPUS:85112659212
T3 - IUTAM Bookseries
SP - 337
EP - 346
BT - IUTAM Bookseries
PB - Springer Science and Business Media B.V.
ER -