Research on Surrogate Model of Variable Geometry Turbine Performance Based on Backpropagation Neural Network

Research on Surrogate Model of Variable Geometry Turbine Performance Based on Backpropagation Neural Network

To meet the increasingly stringent performance indicators of gas turbines, the turbine inlet temperature has increased, and variable geometry turbine technology is widely applied. Therefore, this study developed a quasi-two-dimensional (quasi-2D) method for variable geometry turbine performance cons...

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Bibliographic Details
Main Authors: Liping Deng, Hu Wu, Yuhang Liu, Qi’an Xie
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Aerospace
Subjects:
axial flow turbine
quasi-2D
variable geometry
BP neural network
surrogate model
Online Access:https://www.mdpi.com/2226-4310/12/5/410
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