ABSTRACT
Structural health monitoring (SHM) integrated within the performance assessment of ships is an effective method to reduce uncertainties in the analysis and derive crucial information regarding the real-time structural response. In an ideal situation, continuous monitoring is required to accurately assess and predict the performance of deteriorating naval vessels; however, this is neither practical nor financially efficient. Presented in this paper is a computational framework that has the ability to determine cost-effective SHM plans considering the probability that the performance prediction model based on monitoring data is suitable throughout the life-cycle of a naval vessel. Utility functions are employed to express the relative desirability of lifetime intervention schedules. Optimization procedures are utilized to simultaneously maximize the utilities associated with monitoring cost and expected average availability in order to determine optimum SHM strategies under uncertainty. The capabilities of the proposed decision support framework are illustrated on an aluminum wave piercing catamaran.
