The state of engineering systems changes in time due to the effect of gradual (e.g. corrosion, fatigue) and shock deterioration (e.g. earthquakes, floods, and tornados). At specified moments, for example, after a shock, decision-makers might wish to know the state of the system to take the optimal management action. Different data acquisition strategies such as inspections and continuous structural health monitoring (SHM) can help in the definition and prediction of the system state over time. The acquisition of information comes at a cost that must be balanced by the benefit it brings in terms of risk reduction. The value of information from Bayesian decision analysis quantifies the benefit provided by such information. This article proposes a formulation to compute the value of information of inspection and continuous SHM for degrading engineering systems. In the proposed formulation, the information collected before a given time is used to improve the prediction of the effects of gradual and shock deterioration processes and the future probability of failure. This article investigates the case study of a two-span reinforced concrete bridge degrading under the effect of chemical reactions and seismic actions.

Quantifying the value of information from inspecting and monitoring engineering systems subject to gradual and shock deterioration

Pier Francesco Giordano;Maria Pina Limongelli
2022-01-01

Abstract

The state of engineering systems changes in time due to the effect of gradual (e.g. corrosion, fatigue) and shock deterioration (e.g. earthquakes, floods, and tornados). At specified moments, for example, after a shock, decision-makers might wish to know the state of the system to take the optimal management action. Different data acquisition strategies such as inspections and continuous structural health monitoring (SHM) can help in the definition and prediction of the system state over time. The acquisition of information comes at a cost that must be balanced by the benefit it brings in terms of risk reduction. The value of information from Bayesian decision analysis quantifies the benefit provided by such information. This article proposes a formulation to compute the value of information of inspection and continuous SHM for degrading engineering systems. In the proposed formulation, the information collected before a given time is used to improve the prediction of the effects of gradual and shock deterioration processes and the future probability of failure. This article investigates the case study of a two-span reinforced concrete bridge degrading under the effect of chemical reactions and seismic actions.
2022
Reliability, value of information, decision-making, structural health modeling, statistical modeling
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1156591
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