Structural Health Monitoring (SHM) systems are useful instruments for limitingthe risk related to seismic events. Aside from the cost of the devices and theconvenience of their operation, the selection of these systems should be guided by thequality of the information gained and by their effect on reduction of overall losses.This selection can be guided quantitatively by the Value of Information (VoI)principle of decision theory. VoI is essentially the difference between the expectedloss of managing a structure without and with the SHM system. Indeed, while amonitoring system can provide improved information as to damage suffered by thestructure, it is only by considering the savings resulting from subsequent decisions(e.g., inspection, repair, continued operation or closure of the structure) that the valueof such a system can be determined.An accurate estimation of the VoI generally requires running a large number ofsimulations, making use of complex numerical models, and its computational cost ishigh. Therefore, a procedure for obtaining an approximate estimate by a relativelysmall number of simulations is needed.In this paper we investigate a numerical approach based on Monte Carlosimulation and non-parametric regression to estimate the VoI. Application of theproposed technique is presented on a bridge model subject to seismic excitation andinstrumented with accelerometers.
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