Abstract
The selection of optimal maintenance solutions under uncertainty is affected by the risk perception of decision-makers. The solution predicted by the minimum expected cost criterion may not conform to the preferences of decision-makers. The aim of this paper is to develop a risk-informed maintenance decision-making framework for corroding ship structures considering risk perceptions. Cumulative prospect theory is employed to model the choice preferences under uncertainty. The optimal ship maintenance strategy is developed as a single goal to maximize the expected prospect value. The uniform inspection interval is assumed to be the only design variable and a condition-based repair policy is considered. Monte Carlo simulations are employed to obtain the distribution of the maintenance and failure costs within the considered service life. The application of the developed framework is demonstrated on a ship hull girder structure.
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Acknowledgments
The support by grants from (a) the U.S. Office of Naval Research (ONR) Awards N00014-08-1-0188, N00014-12-1-0023, and N00014-16-1-2299, (b) the National Science Foundation (NSF) Award CMMI-1537926, and (c) the Commonwealth of Pennsylvania, Department of Community and Economic Development, through the Pennsylvania Infrastructure Technology Alliance (PITA) Awards, is gratefully acknowledged. Opinions presented in this paper are those of the authors and do not necessarily reflect the views of the sponsoring organizations.
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Gong, C., Frangopol, D.M., Cheng, M. (2020). Application of Cumulative Prospect Theory to Optimal Inspection Decision-Making for Ship Structures. In: Barthorpe, R. (eds) Model Validation and Uncertainty Quantification, Volume 3. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-030-12075-7_7
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DOI: https://doi.org/10.1007/978-3-030-12075-7_7
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