Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/31979
Title: Development of an AI-enhanced conceptual aircraft design synergy for the rapid prediction of future drone concepts
Authors: Burke, M
Gatto, A
Issue Date: 30-Jun-2025
Publisher: EUCASS
Citation: Burke, M. and . (2025) 'Development of an AI-enhanced conceptual aircraft design synergy for the rapid prediction of future drone concepts', UAVFUT Symposium: UAV Future Applications/Services and Specific Technologies, 11th European Conference for AeroSpace Sciences (EUCASS), Rome, Italy, 30 June-4 July, pp. 1 - 12.
Abstract: The use of Unmanned Aerial Vehicles(UAVs) has expanded rapidly over the last decade. These systems have an almost limitless scope of application with resupply, surveillance, monitoring, and logistics representing but a few. Having such a wide scope, a means to rapidly, efficiently and accurately develop new designs fit-forpurpose would offer a significant advantage to developers given their inherent need to maximize potential within a competitive marketplace. This work attempts to leverage the capabilities of Artificial Intelligence(AI) for this purpose through the development of a functional AI model aimed primarily at enhancing initial conceptual design metric prediction using limited inputs and/or datasets. Overall, this synergy shows the potential to improve this process significantly through facilitating faster, more cost-effective design cycle iterations allowing ultimately more effective and efficient decision making.
URI: https://bura.brunel.ac.uk/handle/2438/31979
Other Identifiers: ORCiD: Alvin Gatto https://orcid.org/0000-0003-4443-0451
Appears in Collections:Dept of Mechanical and Aerospace Engineering Research Papers

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