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Gómez-Rodríguez AAutor (correspondència)Sánchez-Carmona AAutor o coautorCuerno-Rejado CAutor o coautor

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Remotely Piloted Aircraft Systems conceptual design methodology based on factor analysis

Publicat a:Aerospace Science And Technology. 90 368-387 - 2019-07-01 90(), DOI: 10.1016/j.ast.2019.04.041

Autors: Gómez-Rodríguez Á; Sanchez-Carmona A; García-Hernández L; Cuerno-Rejado C

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© 2019 Elsevier Masson SAS The rapid expansion of Remotely Piloted Aircraft Systems (RPAS)within the aeronautical industry demands the development of new design methodologies focused on these aircraft. In this paper, a novel rapid-sizing procedure for the initial design phases of H-tail Remotely Piloted Aircraft (RPA)based on the factor analysis technique is proposed. The main concept of this methodology consists in finding the latent design tendencies within the sample of study, that are represented by unobservable factors, which can be employed as specifications in a novel design procedure based on the most prominent design trends of the sample of study. The classical factor analysis procedure has been adapted to the characteristics of the aircraft conceptual design discipline, including a new criterion for the extraction of factors taking into account the desirable accuracy in this phase of design. From the findings of this analysis, a novel conceptual rapid-sizing methodology based on the main design tendencies of H-tail RPA is proposed. This methodology is then tested with a design example case and compared with the results obtained from a conventional approach based purely on regression analysis for the same aircraft in order to validate the procedure. This analysis shows that the results fall within the expected accuracy of the conceptual design phase, with the added novelty of considering the extracted design tendencies as specifications for the initial sizing of the RPA, and constituting a methodology with higher robustness than the contrasting traditional procedure due to the capacity to account simultaneously for the interrelations amongst all the variables and the ability to control a wide range of statistical indicators to augment the confidence in the results.

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