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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Vydané v:	Engineering applications of computational fluid mechanics Ročník 15; číslo 1; s. 561 - 583
Hlavní autori:	Zeinalzadeh, A., Pakatchian, M.R.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Hong Kong Taylor & Francis 01.01.2021 Taylor & Francis Ltd Taylor & Francis Group
Predmet:	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
On-line prístup:	Získať plný text
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