A Deep Learning Approach to an Airfoil Inverse Design Problem
Author:
Affiliation:
1. Georgia Institute of Technology
Publisher
American Institute of Aeronautics and Astronautics
Link
https://arc.aiaa.org/doi/pdf/10.2514/6.2018-3420
Reference20 articles.
1. A Convolutional Neural Network Approach to Training Predictors for Airfoil Performance
2. Visual closed-loop control for pouring liquids
3. Human-level control through deep reinforcement learning
4. Airfoil Shape Design and Optimization Using Multifidelity Analysis and Embedded Inverse Design
5. Inverse Airfoil Design Utilizing CST Parameterization
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2. Mission-Driven Inverse Design of Blended Wing Body Aircraft with Machine Learning;Aerospace;2024-02-05
3. Airfoil Inverse Design Using a Deep Neural Net with an Explainable Attention Mechanism;International Journal of Aeronautical and Space Sciences;2023-12-21
4. A novel deep-learning-based pressure distribution prediction approach of airfoils;Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering;2023-10-19
5. A reinforcement learning approach to airfoil shape optimization;Scientific Reports;2023-06-16
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