A multi layer evidence network model for the design process of space systems under epistemic uncertainty

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Filippi, Gianluca and Vasile, Massimiliano; Gaspar-Cunha, A. and Periaux, J. and Giannakoglou, K.C. and Quagliarella, N.R. and Greiner, D., eds. (2020) A multi layer evidence network model for the design process of space systems under epistemic uncertainty. In: Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences. Computational Methods in Applied Sciences . Springer, Cham, Switzerland, pp. 227-243. ISBN 9783030574222 (https://doi.org/10.1007/978-3-030-57422-2)

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Abstract

The purpose of this paper is to introduce a new method for the design process of complex systems affected by epistemic uncertainty. In particular, a multi-layer network is proposed to model the whole design process and describe the transition between adjacent phases. Each layer represents a design phase with a particular detail definition, each node a subsystem and each link a sharing of information. The network is used to quantify and propagate uncertainty through the different layers (design phases) where, proceeding from phase A to phase F, the detail of the mathematical model is increased. Thus, it can be considered as a multi-fidelity approach for the design of a complex system affected by epistemic uncertainty. The framework of Dempster-Shafer Theory of Evidence (DST) is used to model epistemic uncertainty. The model is then called Multi-Layer Evidence Network Model (ML-ENM).

ORCID iDs

Filippi, Gianluca and Vasile, Massimiliano ORCID logoORCID: https://orcid.org/0000-0001-8302-6465; Gaspar-Cunha, A., Periaux, J., Giannakoglou, K.C., Quagliarella, N.R. and Greiner, D.
CORE (COnnecting REpositories)