Evaluation of novel-objective functions in the design optimization of a transonic rotor by using deep learning

Design optimization of transonic airfoils for rotary blades is a challenging subject that remarkably affects the stage and overall performance of axial-flow compressors. This paper describes a surrogate-based multi-objective optimization process over a transonic rotary blade. This blade works in the...

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Veröffentlicht in:	Engineering applications of computational fluid mechanics Jg. 15; H. 1; S. 561 - 583
Hauptverfasser:	Zeinalzadeh, A., Pakatchian, M.R.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Hong Kong Taylor & Francis 01.01.2021 Taylor & Francis Ltd Taylor & Francis Group
Schlagworte:	Airfoil design optimization axial compressor Boundary layers Deep learning Design factors Design optimization Flat roofs MISES Multilayer perceptrons Multilayers Multiple objective analysis Pressure distribution Rotor blades Rotor blades (turbomachinery) Suction Supercritical airfoils supercritical pressure distribution Supercritical pressures transonic rotor Turbocompressors
ISSN:	1994-2060, 1997-003X
Online-Zugang:	Volltext
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