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Machine Learning In Aerodynamic Shape Optimization, Jichao Li, Xiaosong Du, Joaquim R.R.A. Martins
Machine Learning In Aerodynamic Shape Optimization, Jichao Li, Xiaosong Du, Joaquim R.R.A. Martins
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Machine learning (ML) has been increasingly used to aid aerodynamic shape optimization (ASO), thanks to the availability of aerodynamic data and continued developments in deep learning. We review the applications of ML in ASO to date and provide a perspective on the state-of-the-art and future directions. We first introduce conventional ASO and current challenges. Next, we introduce ML fundamentals and detail ML algorithms that have been successful in ASO. Then, we review ML applications to ASO addressing three aspects: compact geometric design space, fast aerodynamic analysis, and efficient optimization architecture. In addition to providing a comprehensive summary of the research, …