Machine learning in aerodynamic shape optimization
Abstract Machine learning (ML) has been increasingly used to aid aerodynamic shape
optimization (ASO), thanks to the availability of aerodynamic data and continued …
optimization (ASO), thanks to the availability of aerodynamic data and continued …
Complex nonlinear dynamics and vibration suppression of conceptual airfoil models: A state-of-the-art overview
During the past few decades, several significant progresses have been made in exploring
complex nonlinear dynamics and vibration suppression of conceptual aeroelastic airfoil …
complex nonlinear dynamics and vibration suppression of conceptual aeroelastic airfoil …
Deep neural operators as accurate surrogates for shape optimization
Deep neural operators, such as DeepONet, have changed the paradigm in high-
dimensional nonlinear regression, paving the way for significant generalization and speed …
dimensional nonlinear regression, paving the way for significant generalization and speed …
Airfoil design and surrogate modeling for performance prediction based on deep learning method
Q Du, T Liu, L Yang, L Li, D Zhang, Y **e - Physics of Fluids, 2022 - pubs.aip.org
Airfoil design and surrogate modeling for performance prediction based on deep learning
method | Physics of Fluids | AIP Publishing Skip to Main Content Umbrella Alt Text Umbrella Alt …
method | Physics of Fluids | AIP Publishing Skip to Main Content Umbrella Alt Text Umbrella Alt …
Design subspace learning: Structural design space exploration using performance-conditioned generative modeling
R Danhaive, CT Mueller - Automation in Construction, 2021 - Elsevier
Designers increasingly rely on parametric design studies to explore and improve structural
concepts based on quantifiable metrics, generally either by generating design variations …
concepts based on quantifiable metrics, generally either by generating design variations …
Data-based approach for wing shape design optimization
Aircraft design is a trade-off among different objectives and constraints, so multiple design
rounds are usually required. Aerodynamic shape optimization based on high-fidelity …
rounds are usually required. Aerodynamic shape optimization based on high-fidelity …
Performance prediction and design optimization of turbine blade profile with deep learning method
Q Du, Y Li, L Yang, T Liu, D Zhang, Y **e - Energy, 2022 - Elsevier
Aerodynamic design optimization of the blade profile is a critical approach to improve
performance of turbomachinery. This paper aims to achieve the performance prediction with …
performance of turbomachinery. This paper aims to achieve the performance prediction with …
Inverse design optimization framework via a two-step deep learning approach: application to a wind turbine airfoil
The inverse approach is computationally efficient in aerodynamic design as the desired
target performance distribution is prespecified. However, it has some significant limitations …
target performance distribution is prespecified. However, it has some significant limitations …
Unsteady aerodynamic reduced-order modeling based on machine learning across multiple airfoils
Computational-fluid-dynamics-based prediction of unsteady aerodynamics is an essential
research topic in the design of aircraft, which usually requires very high computational cost …
research topic in the design of aircraft, which usually requires very high computational cost …
A deep learning‒genetic algorithm approach for aerodynamic inverse design via optimization of pressure distribution
Conventional aerodynamic inverse design (AID) methods have major limitations in terms of
optimality and actuality of target parameter distribution. In this research, the target pressure …
optimality and actuality of target parameter distribution. In this research, the target pressure …