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 StE and SyE. Given the goals of the two stakeholders, the problem is formulated as a noncooperative game, where StE control M distribution and SyE control H distribution, according to their respective strategies. The two players make their decision about test points location simultaneously, playing a spatial competition game and a genetic algorithm is adopted to estimate the Nash equilibrium solutions to the multiple test points location problem. Results for a multiple test points location problem are shown.

Computational results for flight test points distribution in the flight envelope

MALLOZZI, LINA;DE PAOLIS, PIERLUIGI;D'ARGENIO, ALESSANDRO
2015

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 StE and SyE. Given the goals of the two stakeholders, the problem is formulated as a noncooperative game, where StE control M distribution and SyE control H distribution, according to their respective strategies. The two players make their decision about test points location simultaneously, playing a spatial competition game and a genetic algorithm is adopted to estimate the Nash equilibrium solutions to the multiple test points location problem. Results for a multiple test points location problem are shown.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/599664
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