Aerodynamic Prediction and Design Optimization Using Multi-Fidelity Deep Neural Network

Aerodynamic Prediction and Design Optimization Using Multi-Fidelity Deep Neural Network

With the rapid development of data-driven methods in recent years, deep neural networks have attracted significant attention for aerodynamic predictions and design optimizations. Among these methods, the multi-fidelity deep neural network (MFDNN), which can combine high-fidelity (HF) and low-fidelit...

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Bibliographic Details
Main Authors: Bingchen Du, Ennan Shen, Jiangpeng Wu, Tongqing Guo, Zhiliang Lu, Di Zhou
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Aerospace
Subjects:
aerodynamic shape optimization
multi-fidelity model
surrogate model
neural networks
computational fluid dynamics
Online Access:https://www.mdpi.com/2226-4310/12/4/292
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