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Titel:

Machine-learn-driven prediction of streamwise vorticity induced by a random distributed roughness path in hypersonic flow

Dokumenttyp:
Konferenzbeitrag
Art des Konferenzbeitrags:
Textbeitrag / Aufsatz
Autor(en):
Friedrich Ulrich, Christian Stemmer
Abstract:
Boundary-layer transition on the surface of a space transportation vehicle highly influences the heat-flux the thermal protection system has to withstand in a re-entry scenario. Distributed surface roughness can cause cross-flow like vortices in the wake of the roughness patch that highly destabilize the flow regime. The variety of roughness parameters which influence the generation of a cross-flow vortex is addressed with the training of a Deep Neural Network. This paper presents a data...     »
Stichworte:
Hypersonic Flow, Machine Learning, Distributed Roughness, Re-entry Capsule
Dewey-Dezimalklassifikation:
620 Ingenieurwissenschaften
Kongress- / Buchtitel:
2nd International Conference on Flight Vehicles, Aerothermodynamics and Re-entry Missions & Engineering (FAR)
Datum der Konferenz:
19 - 23 June 2022
Jahr:
2022
Sprache:
en
TUM Einrichtung:
Lehrstuhl für Aerodynamik und Strömungsmechanik
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