Decision making framework for optimal SHM planning of ship structures considering availability and utility. (1st May 2017)

• Record Type: Journal Article
• Authors: Sabatino, Samantha; Frangopol, Dan M.
• Is Part Of: Ocean engineering. Volume 135(2017)
• Page Start: 194
• Page End: 206
• Publication Date: 2017-05-01
• Subjects: Decision making -- Utility -- Availability -- SHM -- Optimization; Ocean engineering -- Periodicals; Ocean engineering; Periodicals; 620.4162
• DOI: 10.1016/j.oceaneng.2017.02.030
• Languages: English
• ISSNs: 0029-8018

Abstract

Abstract: Uncertainties associated with modeling and performance prediction of structures may be addressed and subsequently reduced by including, within the performance assessment, information collected from inspections and structural health monitoring (SHM). Under ideal conditions, continuous monitoring is required to accurately assess and predict the performance of deteriorating systems; however, in general, this is neither practical nor financially efficient. Presented herein is an approach that determines cost-effective SHM plans that consider the probability that the performance prediction model based on monitoring data is suitable throughout the life-cycle of ship structures. This probability is used to compute the expected average availability of monitoring data for prediction during the life-cycle of a system. Utility theory is employed to incorporate the influence of the decision maker's risk attitude on the relative desirability of SHM plans. Optimization techniques are utilized to simultaneously maximize the utilities associated with monitoring cost and expected average availability in order to determine optimal monitoring strategies under uncertainty. The effects of the formulation of the utility function, risk attitude of the decision maker, and number of uniform and non-uniform time monitoring intervals on optimal SHM plans are investigated. The capabilities of the proposed decision support framework are illustrated on a naval ship. Highlights: Uncertainties associated with performance prediction are reduced by considering SHM. Cost-effective SHM plans that consider utility and availability theory are provided. Utility theory is employed to incorporate the influence of risk attitude. Optimization techniques are utilized to maximize cost and availability utilities. The proposed decision support framework is deployed for an existing naval ship.