In this paper we present a computational methodology to solve the problem of the proper design of the test matrix for an envelope expansion test campaign, where both flutter and systems testing are required (i.e. a new store integration). There are two different stakeholders involved: Structural Engineers (StE), who want to verify their predictions about the flutter free area, and the Systems Engineers (SyE), who want to investigate environmental aspects in the entire operational flight envelope. The test matrix, representing the test points distribution in the flight envelope, can be found solving an optimization problem with hard constraints (flight envelope boundaries) and different objective functions for the two stakeholders: the aim of the StE is to optimize distribution in Mach (M) range; the aim of SyE is to optimize distribution in Pressure Altitude (Hc) range; both of them want to maximize test points density near maximum equivalent airspeed (VE) area. Given the goals of the two stakeholders, the problem was formulated as a potential game, where StE control M distribution and SyE control Hc distribution, according to their respective strategies. The two players make their decision about test points location simultaneously, playing a spatial competition game. A simple Newton-Raphson method is sufficient to numerically solve the single test point location problem; a genetic algorithm is adopted to estimate the Nash equilibrium solutions to the multiple test points location problem. Results for the single, double and multiple test points location problems are shown.

Computational Results for Flight Test Points Distribution in the Flight Envelope

MALLOZZI, LINA;DE PAOLIS, PIERLUIGI;D'ARGENIO, ALESSANDRO
2013

Abstract

In this paper we present a computational methodology to solve the problem of the proper design of the test matrix for an envelope expansion test campaign, where both flutter and systems testing are required (i.e. a new store integration). There are two different stakeholders involved: Structural Engineers (StE), who want to verify their predictions about the flutter free area, and the Systems Engineers (SyE), who want to investigate environmental aspects in the entire operational flight envelope. The test matrix, representing the test points distribution in the flight envelope, can be found solving an optimization problem with hard constraints (flight envelope boundaries) and different objective functions for the two stakeholders: the aim of the StE is to optimize distribution in Mach (M) range; the aim of SyE is to optimize distribution in Pressure Altitude (Hc) range; both of them want to maximize test points density near maximum equivalent airspeed (VE) area. Given the goals of the two stakeholders, the problem was formulated as a potential game, where StE control M distribution and SyE control Hc distribution, according to their respective strategies. The two players make their decision about test points location simultaneously, playing a spatial competition game. A simple Newton-Raphson method is sufficient to numerically solve the single test point location problem; a genetic algorithm is adopted to estimate the Nash equilibrium solutions to the multiple test points location problem. Results for the single, double and multiple test points location problems are shown.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/598914
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact