[HTML][HTML] Improving aircraft performance using machine learning: A review

S Le Clainche, E Ferrer, S Gibson, E Cross… - Aerospace Science and …, 2023 - Elsevier
This review covers the new developments in machine learning (ML) that are impacting the
multi-disciplinary area of aerospace engineering, including fundamental fluid dynamics …

A review of the artificial neural network surrogate modeling in aerodynamic design

G Sun, S Wang - … of the Institution of Mechanical Engineers …, 2019 - journals.sagepub.com
Artificial neural network surrogate modeling with its economic computational consumption
and accurate generalization capabilities offers a feasible approach to aerodynamic design …

Review of multi-fidelity models

MG Fernández-Godino - ar**/links/5efeacf6299bf18816fcdd80/Aerodynamic-Inverse-Design-Using-Multifidelity-Models-and-Manifold-Map**.pdf" data-clk="hl=sr&sa=T&oi=gga&ct=gga&cd=9&d=1708592659388195951&ei=YDTDZ5LvB5eY6rQPjuS70As" data-clk-atid="b2SsoPgjthcJ" target="_blank">[PDF] researchgate.net

Aerodynamic inverse design using multifidelity models and manifold map**

X Du, J Ren, L Leifsson - Aerospace science and technology, 2019 - Elsevier
Aerodynamic inverse design is proposed using multifidelity models and the manifold
map** (MM) technique. Aerodynamic inverse design aims at achieving a target …