Probabilistic Chain Cable Strength and Mooring Reliability

ABCTRACT Based on the strength distribution of individual links, a chain cable strength model which conforms to an asymptotic extreme value distribution is formulated. The subject of probablistic chain breaking strength is investigated and it is found that the variability of link strength is of crucial importance. Based on the formulated chain strength model, the mooring system reliability analysis is subsequently performed. It is concluded that increased variability or reduced mean of link strength will significantly increase the line failure probability and the likelihood of failure occurring in lower sea states. The study also finds that the strength of K4 chains may not necessary be superior to that of ORQ chains if the strength of K4 links has a larger spread. 1. INTRODUCTION Approximately 85\ of the current semisubmersiblesdeployed in the North Sea are equipped with chain mooring systems. A typical chain mooring line consists of a few thousand links and the strength of the chain is only as strong as its weakest link. However; this fact is usually ignored in conventional mooring analysis and design, and the fitness of the mooring system is assessed based on a nominal chain breaking strength specified by manufacturers and classification societies. This alone could significantly undermine the mooring system reliability. To improve the understanding of the subject and stimulate interest in this area, an investigation of probabilistic chain cable strength and its impact on mooring systems is carried out. The paper focuses on the following main issues:Probabilistic prediction of chain strength,Parametric effects of links,Impact on mooring reliability,ORQ vs K4 chains. 2. CHAIR STRENGTH HODEL A typical mooring chain is over 1000m long and has a few thousand links. Assuming that the strength of individual links is independent and follows theGaussian distribution, the probability density function of link strength can be expressed as:(available in full paper) The corresponding cumulative distribution function is given by:(available in full paper) where n and 0 are the mean and the standard deviation of the link strength. The probability distribution function of the strength of the weakest link out of n links is given by:(available in full paper) and the probability density function follows:(available in full paper) where y is the chain strength variable. Though Eq.(3) and Eq.(4) are exact solutions, the above integrations have to be performed numerically, i.e. no closed form solutions are available. However, as n 00, the above distribution converges to the type I asymptotic extreme value distribution. The probability distribution function can be expressed as [1):(available in full paper)