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Laura Mainini

Chair in Aerospace Computational Design & Associate Director of the Brahmal Institute of Sustainable Aviation at Imperial College London

Imperial College London
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United Kingdom

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Laura Mainini

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Imperial College London

Sustainable Aviation

Imperial College London is offering fully funded PhD studentships through the Brahmal Institute’s Doctoral Programme in Sustainable Aviation (DPSA). Two projects are available: one focuses on infosymbiotics for sustainable aviation, specifically on non-CO2 emissions, and the other on actionable sustainable aviation fuel (SAF) pathways, including multi-criteria assessment of production and impact on aviation. The infosymbiotics project aims to re-imagine aviation sustainability by designing a system that leverages live data from aircraft fleets to reduce environmental impact through real-time operational and design strategies. The SAF pathways project involves analysing various fuel alternatives, their effects on aircraft design, operations, and airport logistics, and deploying computational search and multisource learning to improve large-scale assessments. Supervisors include Laura Mainini (Chair in Aerospace Computational Design & Associate Director of the Brahmal Institute), Dr Sebastian Eastham, and Prof Niall Mac Dowell, all affiliated with Imperial College London. Applicants should have a strong background in engineering, physical sciences, or related fields, and be interested in multidisciplinary research. The studentships are fully funded, covering tuition and providing a stipend. The application deadline is 11 July 2025. For more information and to apply, visit the Brahmal Institute for Sustainable Aviation DPSA page.

3 months ago

Articles (15)

FREEDOM: Validated Method for Rapid Assessment of Incipient Faults of Aerospace Systems

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 evaluations of numerical models of the equipment. This results in an intensive computational procedure that can be addressed only grounding the aircraft. We introduce an original methodology to sensitively accelerate FDI by reducing the computational demand to identify the health status of the aircraft. Our scheme FREEDOM (Fast Reliability Estimate and Incipient Fault Detection of Multiphysics Aerospace Systems) proposes an original combination of a novel two-step compression strategy to compute offline a synthesized representation of the dynamical response of the system and uses an inverse Bayesian optimization approach to infer online the level of damage determined by multiple fault modes affecting the equipment. We demonstrate and validate FREEDOM against numerical and physical experiments for the case of an electromechanical actuator employed for secondary flight controls. Particular attention is dedicated to simultaneous incipient mechanical and electrical faults considering different experimental settings. The outcomes validate our FDI strategy, which permits to achieve the accurate identification of complex damages outperforming the computational time of state-of-the-art algorithms by two orders of magnitude.

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2024

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Matteo Davide Lorenzo Dalla Vedova

Assistant Professor

Politecnico di Torino

ITALY
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