In the realization of novel aircraft, comfort plays a more and more important role in the design, by different reasons. For instance, the demand of people for higher quality standards; the related growth of laws and regulations conditioning the issue of new products; the need of using lighter materials and the consequent fall of sound absorption characteristics. Subjective comfort should be addressed in the design process, instead of the physical variables that can affect the personal judgement. Then, the definition of a numerical model of a standard passenger, dealing with the environmental response of a generic person in an aircraft, is necessary. Associated with a classical representation of the vehicle, this may provide a tool that links the external solicitation to the human response through the structural environment. Dealing with people, artificial neural network-based tools seem the most advisable to develop a proper model. The necessary experimental data (both input and output) to test and assess the software come from a large experimental campaign, carried out at the manufacturers' sites of Alenia and Dornier. The necessary psychological informations were get through a proper tool developed by the University of Oldenburg. In this paper, a three-layer net, with back-propagation learning algorithm, was considered. The acoustic field inside the aircraft was considered as input, while the output consisted of suitable phsycho-acoustic descriptors. Different tests, with different input/output typologies, were performed and the results compared.
Model of a generic aircraft passenger using artificial neural networks
Modell eines Standardfluggastes mit Hilfe künstlicher neuronaler Netze
International Congress on Sound and Vibration, 7 ; 3369-3376
2000
8 Seiten, 5 Bilder, 2 Tabellen, 7 Quellen
Aufsatz (Konferenz)
Englisch
Aircraft System Identification Using Artificial Neural Networks
British Library Conference Proceedings | 2013
|