Open Access
Subscription Access

### Computation of Lifetime Value of Information for Monitoring Systems

#### Abstract

Structural Health Monitoring (SHM) systems are useful instruments for limiting the risk related to seismic events. Aside from the cost of the devices and the convenience of their operation, the selection of these systems should be guided by the quality 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 expected loss of managing a structure without and with the SHM system. Indeed, while a monitoring system can provide improved information as to damage suffered by the structure, it is only by considering the savings resulting from subsequent decisions (e.g., inspection, repair, continued operation or closure of the structure) that the value of such a system can be determined. An accurate estimation of the VoI generally requires running a large number of simulations, making use of complex numerical models, and its computational cost is high. Therefore, a procedure for obtaining an approximate estimate by a relatively small number of simulations is needed. In this paper we investigate a numerical approach based on Monte Carlo simulation and non-parametric regression to estimate the VoI. Application of the proposed technique is presented on a bridge model subject to seismic excitation and instrumented with accelerometers.