Conceptual Aircraft Design and AI: Developing a functional relationship for the rapid realisation of future drone concepts

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-for-purpose would offer a significant advantage to developers given their inherent need to maximise potential within a competitive marketplace. This paper attempts to leverage the capabilities of Artificial Intelligence(AI) for this purpose through the development of functional synergies to predict maximum rated engine power from limited inputs and datasets. Overall, the use of AI techniques was found to offer the potential to substantial improve and enhance the design process with also the possibility for the creation of more cost-effective and efficient software tools that could significantly streamline the process.

Publication Details

Journal
Brunel University Research Archive (BURA) (Brunel University London)
Published
2025-01-28
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00

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article

Conceptual Aircraft Design and AI: Developing a functional relationship for the rapid realisation of future drone concepts

Brunel University Research Archive (BURA) (Brunel University London)
Geochemistry and Geologic Mapping
article

Conceptual Aircraft Design and AI: Developing a functional relationship for the rapid realisation of future drone concepts

article en

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-for-purpose would offer a significant advantage to developers given their inherent need to maximise potential within a competitive marketplace. This paper attempts to leverage the capabilities of Artificial Intelligence(AI) for this purpose through the development of functional synergies to predict maximum rated engine power from limited inputs and datasets. Overall, the use of AI techniques was found to offer the potential to substantial improve and enhance the design process with also the possibility for the creation of more cost-effective and efficient software tools that could significantly streamline the process.

Brunel University Research Archive (BURA) (Brunel University London)
UK Research and Innovation
Openalex Percentile: Top 41%
Geochemistry and Geologic Mapping
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