Steady-state transonic flowfield prediction via deep-learning framework

G Immordino, A Da Ronch, M Righi - AIAA Journal, 2024 - arc.aiaa.org
This paper focuses on the development of a deep-learning framework for predicting
distributed quantities around aircraft flying in the transonic regime. These quantities play a …

Uncertainties quantification in the prediction of the aeroelastic response of the pazy wing tunnel model

M Righi - AIAA Scitech 2023 Forum, 2023 - arc.aiaa.org
View Video Presentation: https://doi. org/10.2514/6.2023-0761. vid The present paper
extends our previous analysis of the effects of uncertainties to large displacements and to a …

Uncertainties quantification in flutter prediction of a wind tunnel model exhibiting large displacements

M Righi, L Carnevali, M Ravasi - AIAA SCITECH 2022 Forum, 2022 - arc.aiaa.org
View Video Presentation: https://doi. org/10.2514/6.2022-0178. vid This study is a follow up
on our contribution to {AIAA SciTech 2021}; the most relevant additions is the account of the …

Steady-state flowfield prediction in transonic regime via deep-learning framework

G Immordino, A Da Ronch, M Righi - AIAA Journal, 2023 - eprints.soton.ac.uk
This article focuses on the development of a deep–learning framework for predicting
distributed quantities around aircraft flying in the transonic regime. These quantities play a …

Uncertainties Quantification of CFD-Based Flutter Prediction

M Righi, P Greco, A Da Ronch - AIAA Scitech 2021 Forum, 2021 - arc.aiaa.org
View Video Presentation: https://doi. org/10.2514/6.2021-1038. vid This study uses Non-
Intrusive Polynomial Chaos Expansion (NIPCE) to propagate uncertainties related to flow …

Multi-Disciplinary Optimization of HAPS in Formation Flight

M Righi, D Anderegg, M Sondergger… - AIAA AVIATION 2021 …, 2021 - arc.aiaa.org
View Video Presentation: https://doi. org/10.2514/6.2021-2569. vid This paper presents a
multi-disciplinary optimisation of a High-Altitude Pseudo Satellite (HAPS) system exploiting …