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Fast Data-Driven Noise Prediction for an Aircraft in Unconventional Configuration Using Flight Test Data

New, highly integrated, disruptive aircraft concepts are being devised to reduce aviation’s environmental footprint, but their performance is oftentimes challenging for the aircraft designer to assess. Furthermore, these novel aircraft often introduce new risks, such as noise, that cannot be address...

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Principais autores: Dominik Eisenhut, Andreas Strohmayer
Format: Artigo
Sprog:Inglês
Udgivet: MDPI AG 2026-03-01
Serier:Aerospace
Fag:
machine learning
surrogate model
preliminary aircraft design
flight test
noise estimation
electric aircraft
Online adgang:https://www.mdpi.com/2226-4310/13/3/292
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