A simplified method for reliability- and integrity-based design of engineering systems and its application to offshore mooring systems

• Published in: Marine structures Vol. 36; pp. 88 - 104
• Main Authors: Mousavi, Mir Emad, Gardoni, Paolo
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01-04-2014
• Subjects: Design; Integrity; Mooring; Offshore; Optimization; Probability; Reliability; Structure; System; Design; Offshore; Mooring; Probability; Reliability; Structure; System; Optimization; Integrity
• ISSN: 0951-8339; 1873-4170
• DOI: 10.1016/j.marstruc.2014.02.001

This paper presents a simplified method for the reliability- and the integrity-based optimal design of engineering systems and its application to offshore mooring systems. The design of structural systems is transitioning from the conventional methods, which are based on factors of safety, to more advanced methods, which require calculation of the failure probability of the designed system for each project. Using factors of safety to account for the uncertainties in the capacity (strength) or demands can lead to systems with different reliabilities. This is because the number and arrangement of components in each system and the correlation of their responses could be different, which could affect the system reliability. The generic factors of safety that are specified at the component level do not account for such differences. Still, using factors of safety, as a measure of system safety, is preferred by many engineers because of the simplicity in their application. The aim of this paper is to provide a simplified method for design of engineering systems that directly involves the system annual failure probability as a measure of system safety, concerning system strength limit state. In this method, using results of conventional deterministic analysis, the optimality factors for an integrity-based optimal design are used instead of generic safety factors to assure the system safety. The optimality factors, which estimate the necessary change in average component capacities, are computed especially for each component and a target system annual probability of system failure using regression models that estimate the effect of short and long term extreme events on structural response. Because in practice, it is convenient to use the return period as a measure to quantify the likelihood of extreme events, the regression model in this paper is a relationship between the component demands and the annual probability density function corresponding to every return period. This method accounts for the uncertainties in the environmental loads and structural capacities, and identifies the target mean capacity of each component for maximizing its integrity and meeting the reliability requirement. In addition, because various failure modes in a structural system can lead to different consequences (including damage costs), a method is introduced to compute optimality factors for designated failure modes. By calculating the probability of system failure, this method can be used for risk-based decision-making that considers the failure costs and consequences. The proposed method can also be used on existing structures to identify the riskiest components as part of inspection and improvement planning. The proposed method is discussed and illustrated considering offshore mooring systems. However, the method is general and applicable also to other engineering systems. In the case study of this paper, the method is first used to quantify the reliability of a mooring system, then this design is revised to meet the DNV recommended annual probability of failure and for maximizing system integrity as well as for a designated failure mode in which the anchor chains are the first components to fail in the system.
•We proposed a simplified method for reliability- and integrity-based optimal design.•The new method uses conventional deterministic results for reliability assessment.•This reliability and integrity analysis is based on ultimate limit state of a series system.•Closed form solutions are proposed for the probability of failure and optimality factors.•The method is illustrated in a case study about mooring systems based on DNV guidelines.