Sensor-integrating, gentelligent components "inherit" data on operational loads from one generation to the next for design optimisations and require an optimal sensor placement (OSP) to make accurate decisions based on this data. The OSP can be very time-consuming, and most studies focus only on one load case. To address this issue, a methodology for OSP for several load cases, based on the region-growing algorithm for FEM simulation data (RGA4FEM) for solution space reduction, is presented. For validation of the methodology’s applicability, a case study is carried out for a boom of a satellite antenna. The results show that region-based approaches are slower to converge but need smaller populations to find global optima with a genetic algorithm. Furthermore, high robustness is achieved for the most demanding parameters on all load cases in a single optimisation.
Methodology for consideration of different load cases in the design of a sensor-integrating, gentelligent antenna / Galfione, Alessio; Meyer Zu Westerhausen, Sören; Stauß, Timo; Wawer, Max Leo; Ameduri, Salvatore; Totaro, Giovanni; Esposito, Marco; Lachmayer, Roland; Gherlone, Marco. - ELETTRONICO. - 5:(2025), pp. 2401-2410. ( XXV International Conference on Engineering Design Dallas, Texas (USA) August 11 - 14, 2025) [10.1017/pds.2025.10254].
Methodology for consideration of different load cases in the design of a sensor-integrating, gentelligent antenna
Galfione, Alessio;Ameduri, Salvatore;Esposito, Marco;Gherlone, Marco
2025
Abstract
Sensor-integrating, gentelligent components "inherit" data on operational loads from one generation to the next for design optimisations and require an optimal sensor placement (OSP) to make accurate decisions based on this data. The OSP can be very time-consuming, and most studies focus only on one load case. To address this issue, a methodology for OSP for several load cases, based on the region-growing algorithm for FEM simulation data (RGA4FEM) for solution space reduction, is presented. For validation of the methodology’s applicability, a case study is carried out for a boom of a satellite antenna. The results show that region-based approaches are slower to converge but need smaller populations to find global optima with a genetic algorithm. Furthermore, high robustness is achieved for the most demanding parameters on all load cases in a single optimisation.| File | Dimensione | Formato | |
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Methodology-for-consideration-of-different-load-cases-in-the-design-of-a-sensor-integrating-gentelligent-antenna.pdf
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https://hdl.handle.net/11583/3002828
