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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 |
Files in This Item:
File | Description | Size | Format | |
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FullText.pdf | 758.34 kB | Adobe PDF | View/Open |
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