A computational methodology for designing an experimental test matrix is presented based on the concept of potential and repulsive fields. The problem consists in the optimal distribution of test points in a two-dimensional domain, pursuant to hard constraints (permitted boundaries of the domain) and soft constraints (minimization of potential). Each test point is assumed to be the source of different fields which expose all other points to repulsive forces, thus accelerations, acting in different directions. The result of the mutual repulsive forces is a dynamic evolution of the configuration of test points in the domain, which eventually converges to a condition of minimum potential. An iterative process is adopted to find a numerical solution where residual accelerations are below a desired threshold. The method has been extended to the additional task of dynamically relocating the remaining test points, after an initial subset has been performed and a need to change (either increase or reduce) the number of test points has arisen. The proposed technique allows for an easy accomplishment of the task with minor modifications to the algorithm. A large degree of flexibility in the algorithm is allowed to tune the relative weights to attribute to the different requirements. The method proved effective and computationally efficient, exhibiting satisfactory results in both the test matrix design task and the dynamic relocation task.

Design of a flight test matrix and dynamic relocation of test points

D'ARGENIO, ALESSANDRO;DE NICOLA, CARLO;DE PAOLIS, PIERLUIGI;MALLOZZI, LINA
2014

Abstract

A computational methodology for designing an experimental test matrix is presented based on the concept of potential and repulsive fields. The problem consists in the optimal distribution of test points in a two-dimensional domain, pursuant to hard constraints (permitted boundaries of the domain) and soft constraints (minimization of potential). Each test point is assumed to be the source of different fields which expose all other points to repulsive forces, thus accelerations, acting in different directions. The result of the mutual repulsive forces is a dynamic evolution of the configuration of test points in the domain, which eventually converges to a condition of minimum potential. An iterative process is adopted to find a numerical solution where residual accelerations are below a desired threshold. The method has been extended to the additional task of dynamically relocating the remaining test points, after an initial subset has been performed and a need to change (either increase or reduce) the number of test points has arisen. The proposed technique allows for an easy accomplishment of the task with minor modifications to the algorithm. A large degree of flexibility in the algorithm is allowed to tune the relative weights to attribute to the different requirements. The method proved effective and computationally efficient, exhibiting satisfactory results in both the test matrix design task and the dynamic relocation task.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/587612
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