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Prof. Antonio José Torija Martínez

University of Salford, RefMap, ImAFUSA

This presentation will overview the current state-of-the-art methods to model and assess aircraft noise, with a particular focus on conventional practices used in regulatory and operational contexts. It will highlight key research gaps in extending these approaches to assess noise from emerging innovative air mobility (IAM) technologies, such as electric vertical take-off and landing (eVTOL) aircraft. These gaps include challenges related to novel vehicle configurations, complex noise signatures, and particular operational conditions with IAM aircraft operating closer to communities. The presentation will also showcase recent work at the University of Salford aimed at advancing modelling tools and assessment methods for IAM noise, including integrated efforts within an innovative framework of perception-driven engineering. Progress in auralisation and psychoacoustic methods for IAM noise will be presented and discussed.

Panel Discussion

Sustainability challenges in Aviation

Progress in psychoacoustic modelling of drone noise

Short Bio

Prof. Antonio J. Torija Martinez is a leading expert in perception-driven research on aircraft noise, with core interests in noise measurement, modelling, psychoacoustics, and metrics. His current work focuses on psychoacoustic modelling for drones and ducted fan systems. He has authored 48 peer-reviewed articles (including in *Nature*), over 70 conference papers, and leads major projects such as EPSRC DroneNoise and Horizon Europe REFMAP and ImAFUSA. A Marie Curie Fellow, he has collaborated with MIT, UCL, Airbus, and NASA. He serves on NATO and ISO working groups, and in 2023 gave expert evidence to the House of Lords on noise and human health. He currently chairs QuietDrones 2024.

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Osquars backe 8114 28 Stockholm, Sweden

Dissemination e-mail:

refmap@futureneeds.eu

Coordination e-mail: gzampino@kth.se

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This Project has received funding from the European Union’s HORIZON Research and Innovation Programme under Grant Agreement number 101096698

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