The need of reducing aircrafts’ fuel consumption and emissions has led the aircraft industry to the design of smart structural elements, which are composite panels with built-in multisensors monitoring systems. The potential economic benefit in terms of maintenance and inspection planning strongly depends on the performances of the built-in monitoring system. The discrimination between damaged and not damaged structural components based on monitoring outcomes is indeed the result of a decision process, in which the state of the structure is assessed based on observations, affected by uncertainties. These might lead to erroneous estimation of the structural damage with consequent strong influence on the maintenance portfolio. In this paper, a reliability-based optimization of the life cycle cost of a smart aircraft component is proposed in the framework of a Bayesian damage update methodology by following a damage-tolerant approach. The methodology is applied to the delamination detection due to impacts on a composite component. The statistical models for the monitoring performance depend on a multilevel defect classification based on the five classes of events in accordance with the FAA AC No: 20 107B. Multiclass ROC analysis and threshold optimization are introduced in the perspective of the maintenance portfolio. A cost model accounting for the calculation of the value at risk (VAR), meant as the potential loss associated with the maintenance portfolio, is implemented.

Value at Risk for a Guided Waves-Based System Devoted to Damage Detection in Composite Aerostructures / De Marchi, Luca; Marzani, Alessandro; Testoni, Nicola; Heckenberger, Ulrike; Apicella, Alfonso. - STAMPA. - (2016), pp. 909-917. (Intervento presentato al convegno Final Project Conference tenutosi a Moscow nel 19-21 May, 2015) [10.1007/978-3-319-22413-8_49].

Value at Risk for a Guided Waves-Based System Devoted to Damage Detection in Composite Aerostructures

DE MARCHI, LUCA;MARZANI, ALESSANDRO;TESTONI, NICOLA;
2016

Abstract

The need of reducing aircrafts’ fuel consumption and emissions has led the aircraft industry to the design of smart structural elements, which are composite panels with built-in multisensors monitoring systems. The potential economic benefit in terms of maintenance and inspection planning strongly depends on the performances of the built-in monitoring system. The discrimination between damaged and not damaged structural components based on monitoring outcomes is indeed the result of a decision process, in which the state of the structure is assessed based on observations, affected by uncertainties. These might lead to erroneous estimation of the structural damage with consequent strong influence on the maintenance portfolio. In this paper, a reliability-based optimization of the life cycle cost of a smart aircraft component is proposed in the framework of a Bayesian damage update methodology by following a damage-tolerant approach. The methodology is applied to the delamination detection due to impacts on a composite component. The statistical models for the monitoring performance depend on a multilevel defect classification based on the five classes of events in accordance with the FAA AC No: 20 107B. Multiclass ROC analysis and threshold optimization are introduced in the perspective of the maintenance portfolio. A cost model accounting for the calculation of the value at risk (VAR), meant as the potential loss associated with the maintenance portfolio, is implemented.
2016
Smart Intelligent Aircraft Structures (SARISTU): Proceedings of the Final Project Conference
909
917
Value at Risk for a Guided Waves-Based System Devoted to Damage Detection in Composite Aerostructures / De Marchi, Luca; Marzani, Alessandro; Testoni, Nicola; Heckenberger, Ulrike; Apicella, Alfonso. - STAMPA. - (2016), pp. 909-917. (Intervento presentato al convegno Final Project Conference tenutosi a Moscow nel 19-21 May, 2015) [10.1007/978-3-319-22413-8_49].
De Marchi, Luca; Marzani, Alessandro; Testoni, Nicola; Heckenberger, Ulrike; Apicella, Alfonso
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/556290
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