Abstract Machine learning (ML) has been increasingly used to aid aerodynamic shape
optimization (ASO), thanks to the availability of aerodynamic data and continued …

Abstract Machine Learning (ML) techniques have been used in an extensive range of
applications in the field of structural and multidisciplinary optimization over the last few …

This study offers a complete analysis of the use of deep learning or machine learning, as
well as precise recommendations on how these methods could be used in the creation of …

Multi-fidelity surrogate (MFS) modeling aims to fuse data from different fidelity levels to
accurately approximate the responses of a physical system with an acceptable cost. High …

The multidisciplinary design optimization (MDO) of re-entry vehicles presents many
challenges associated with the plurality of the domains that characterize the design problem …

Surrogate models from machine learning regression have been increasingly used in
engineering analysis and design. Since surrogate models are usually built using data from …

To reduce the environmental impact of aviation, aircraft manufacturers develop novel aircraft
configurations and investigate advanced systems technologies. These new technologies are …

Installing photovoltaic (PV) systems in buildings is one of the most effective strategies for
achieving sustainable energy goals and reducing carbon emissions. However, the …

The aerospace industry strives toward innovative aircraft concepts that feature increasing
electrification to meet environmental and business targets. Advanced Multi-Disciplinary …

Model-based fault detection and isolation (FDI) methods allow to infer the health status of
complex aerospace systems through a large quantity of data acquired in flight and …