Nested reliability analysis of mooring lines for floating systems

Montes-Iturrizaga, R.; Heredia‐Zavoni, Ernesto; Silva-González, F.; Straub, Daniel

doi:10.1016/j.apor.2011.09.005

Cited by 18 publications

(14 citation statements)

References 9 publications

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“…For the mooring line resistance, as defined by its breaking strength, the probability distribution is based on the type I extreme value distribution model developed by Montes-Iturrizaga et al [8,10]. It considers that a mooring line is a series system composed of M segments which commonly are a combination of chain, wire rope or polyester.…”

Section: Limit State Functionmentioning

confidence: 99%

“…The proposed reliability formulation was applied to models of catenary and taut-leg moorings of an FPSO used in a previous study [10]. Both mooring system models consist of four clusters of three lines each, symmetrically distributed around the hull turret, and were designed according to DNV-OS-E301 [14].…”

Section: Application To Case Studiesmentioning

confidence: 99%

“…None of these works have studied however the effect of parameter uncertainties on the uncertain reliability index. MontesIturrizaga et al [10] carried an analysis of the predictive reliability of mooring lines for offshore floating structures. They considered the parameters of the distribution of the maximum dynamic tension of the mooring line to be functions of the random environmental variables describing the extreme sea states.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Reliability assessment of mooring lines for floating structures considering statistical parameter uncertainties

Rendón-Conde

Heredia‐Zavoni

2015

Applied Ocean Research

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Section: Limit State Functionmentioning

confidence: 99%

Section: Application To Case Studiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Reliability assessment of mooring lines for floating structures considering statistical parameter uncertainties

Rendón-Conde

Heredia‐Zavoni

2015

Applied Ocean Research

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“…Eq. (6) implies that if we know the probability density function (PDF) of j c and calculate j d given i X and E d , we can calculate the fragility of this component [6,7,8]. In Eq.…”

Section: Calculating the Conditional Probability Of Each Configurationmentioning

confidence: 99%

“…The probability of failure of suction caissons in mooring systems was discussed by Najjar and Gilbert [7]. Montes-Iturrizaga et al [8] also analyzed individual mooring lines for their reliability and used a new equation to calculate the probability of failure of the individual lines in the 3 intact system. Mousavi and Gardoni [9] calculated the probability of failure of mooring systems using Monte Carlo simulation and a new definition for the failure based on system functionality by making the assumption that one mooring component fails at a time.…”

Section: Introductionmentioning

confidence: 99%

Progressive reliability method and its application to offshore mooring systems

Mousavi

Gardoni

Maadooliat

2013

Engineering Structures

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Assessing the reliability of complex systems (e.g. structures) is essential for a reliability-based optimal design that balances safety and costs of such systems. This paper proposes the Progressive Reliability Method (PRM) for the quantification of the reliability of complex systems. The proposed method is a closed-form solution for calculating the probability of failure. The new method is flexible to the definition of "failure" (i.e., can consider serviceability and ultimate-strength failures) and uses the rules of probability theory to estimate the failure probability of the system or its components. The method is first discussed in general and then illustrated in two examples, including a case study to find the safest configuration and orientation of a 12-line offshore mooring system. The PRM results are compared with results of a similar assessment based on the Monte Carlo simulations. It is shown in the example of twocomponent that using PRM, the importance of system components to system safety can be quantified and compared as input information for maintenance planning.

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