Rapid design of aircraft fuel quantity indication systems via multi-objective evolutionary algorithms

Judt, D., Lawson, C. and van Heerden, A. S.J. (2021) Rapid design of aircraft fuel quantity indication systems via multi-objective evolutionary algorithms. Integrated Computer-Aided Engineering, 28(2), pp. 141-158. (doi: 10.3233/ICA-200646)

Abstract

The design of electrical, mechanical and fluid systems on aircraft is becoming increasingly integrated with the aircraft structure definition process. An example is the aircraft fuel quantity indication (FQI) system, of which the design is strongly dependent on the tank geometry definition. Flexible FQI design methods are therefore desirable to swiftly assess system-level impact due to aircraft level changes. For this purpose, a genetic algorithm with a two-stage fitness assignment and FQI specific crossover procedure is proposed (FQI-GA). It can handle multiple measurement accuracy constraints, is coupled to a parametric definition of the wing tank geometry and is tested with two performance objectives. A range of crossover procedures of comparable node placement problems were tested for FQI-GA. Results show that the combinatorial nature of the probe architecture and accuracy constraints require a probe set selection mechanism before any crossover process. A case study, using approximated Airbus A320 requirements and tank geometry, is conducted and shows good agreement with the probe position results obtained with the FQI-GA. For the objectives of accessibility and probe mass, the Pareto front is linear, with little variation in mass. The case study confirms that the FQI-GA method can incorporate complex requirements and that designers can employ it to swiftly investigate FQI probe layouts and trade-offs.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: van Heerden, Dr Stevan
• Authors: Judt, D., Lawson, C., and van Heerden, A. S.J.
• College/School: College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
• Journal Name: Integrated Computer-Aided Engineering
• Publisher: IOS Press
• ISSN: 1069-2509
• ISSN (Online): 1875-8835
• Published Online: 05 March 2021