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Machine Learning for Aerodynamic Design by ramanesh is a document available to read on EtoBox.

This document presents a machine learning-based framework for aerodynamic design optimization that enhances data efficiency by replacing traditional adjoint-based solvers with deep neural networks (DNN) and Gaussian processes (GP). The proposed method allows for accurate predictions of aerodynamic quantities while significantly reducing the number of high-fidelity function evaluations needed. The framework demonstrates improved performance in solving multiple optimization problems simultaneously, making it

Author
ramanesh
Language
EN