Parameter optimization design of an aero-engine bearing chamber based on active learning Kriging

The air-oil two-phase flow in the aero-engine bearing chamber is highly complex and unsteady. To obtain the mapping relationship between the oil volume fraction in the chamber and the oil inlet flow rate and rotational speed for further design optimization, the air-oil two-phase flows are simulated...

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Veröffentlicht in:	Journal of physics. Conference series 2024-01, Vol.2691 (1), p.12047
Hauptverfasser:	Qian, Yuming, Li, Jingkui, Qu, Binjie, Liu, Zhibin
Format:	Artikel
Sprache:	eng
Schlagworte:	Active learning Aerospace engines Chambers Computational fluid dynamics Computing costs Design optimization Design parameters Fluid flow Inlet flow Learning Particle swarm optimization Simulation models Two phase flow
Online-Zugang:	Volltext
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