R. Montes-Iturrizaga

Reliability Analysis of Marine Platforms Subject to Fatigue Damage for Risk Based Inspection Planning

The probability of failure of steel jacket platforms subjected to fatigue damage is computed by means of Monte Carlo simulations using limit state functions in which wave, wind, and deck loadings are expressed in terms of empirical functions of uncertain maximum wave height. Limit state functions associated with the base shear capacity of the jacket and the shear capacity of the deck legs were used. The sensitivity of the probability of failure to the coefficient of variation of resistance, of wave height, of resistance and loading biases, and to parameters in empirical loading functions, as well as the influence of the reserve strength ratio is analyzed using a simplified limit state function. Results from simulations are compared to those obtained with a formulation that relates the reserve strength ratio to the reliability index. An application to risk based inspection planning for extension of the service life of a platform is given.

Risk Based Structural Integrity Management of Marine Platforms Using Bayesian Probabilistic Nets

The present paper introduces a general framework for integrity management of offshore steel jacket structures allowing for the risk based planning of inspections and maintenance activities with a joint consideration of various relevant deterioration and damage processes. The suggested approach relates the relevant deterioration and damage processes to damage states, which in turn may be related to the overall integrity of the jacket structural system as measured through the reserve strength ratio. Each state of degradation, irrespective of the cause, can then be assessed in terms of their impact on the annual probability of failure for the structure. Based on data and subjective information regarding the annual probabilities of occurrence of the relevant deterioration and damage processes, together with a probabilistic modeling of the quality of condition control, it is possible to assess the structural effect of each type of deterioration and damage phenomenon. This facilitates the development of a general framework for risk based integrity management. In the present work such a framework is formulated using Bayesian probabilistic networks for evaluating the time varying global structural reliability of jackets subject to progressive deterioration of its members due to the combined effect of different sources of damage. In principle, system effects, i.e., the effect of damage in one element of the structural system on the capacity of other elements, can also be accounted for through a Bayesian probabilistic net; however, this is not considered in this work.

FPSO Risk Assessment and Acceptance Criteria with Application to FPSO Mooring Systems

Risk based design code safety format calibration for FPSO installations is addressed based on the results of a recent industrial project performed for IMP by the authors. Generic risk models for general engineering systems are introduced taking basis in recent work by the Joint Committee on Structural Safety (JCSS). Thereafter, the scenarios considered for the risk based calibration of a design code safety format for the design of FPSO facilities in the Gulf of Mexico are outlined in some detail. Furthermore, it is shown how these scenarios may be represented in a generic risk assessment model greatly enhanced by the utilization of hierarchical risk modeling procedures such as Bayesian Probabilistic Nets (BPN’s). A short outline of the Life Quality Index (LQI) principle is then introduced as a practically applicable means to determine how much should be invested into life saving activities. Finally, an example is given where the introduced concepts are used for the purpose of determining the target reliability index for individual mooring lines taking into account the direct and indirect consequences of failure of the mooring system for a considered generic FPSO installation.Copyright

Risk Based Structural Integrity Management Using Bayesian Probabilistic Nets

The present paper presents a general framework for integrity management of offshore steel jacket structures allowing for the risk based planning of inspections and maintenance activities with a joint consideration of all relevant deterioration and damage processes. The basic idea behind the suggested approach is to relate the relevant deterioration and damage processes, i.e. the exposure events, to damage states which in turn may be related to the overall integrity of the jacket structural system as measured through the Reserve Strength Ratio (RSR). This facilitates that any state of degradation, irrespective of the cause, can be assessed in terms of their impact on the annual probability of failure for the structure. Taking basis in data as well as subjective information regarding the annual occurrence probabilities of the relevant deterioration and damage processes, together with a probabilistic modeling of the quality of condition control, it is possible to assess the effect of condition control of each type of deterioration and damage phenomena. This then facilitates the development of a general framework for risk based integrity management. In the present work such a framework is formulated using Bayesian Probabilistic Nets (BPN) for evaluating the time varying global structural reliability of jackets subject to progressive deterioration of its members due to the combined effect of different sources of damage.Copyright

Analytical Models for the Probability Distributions of Fatigue Parameters and Crack Size of Offshore Structures Based on Bayesian Updating

In this paper a bayesian framework is used for updating the probability distributions of the parameters of a fatigue model and of crack size in tubular joints using information from inspection reports of fixed offshore structures. For crack detection, the uncertainties are taken into account by means of probability-of-detection (POD) curves. According to the bayesian procedure, if during an inspection no crack is detected, the updated (posterior) distributions depend on the prior ones at time of such inspection and on the POD. On the other hand, if during an inspection a crack is detected and measured, the corresponding predicted crack depth at that time is estimated given values of parameters of a selected fatigue model and of the initial crack depth. Then, a sample value of the model and sizing error associated with the inspection performed, defined as the logarithmic difference between the measured and the predicted crack size, is calculated. Such error is considered to be a normally distributed random variable with known mean and uncertain variance. The distribution of the error variance is taken as a conjugate one for samples of normally distributed variables with known mean and uncertain variance. Based on these assumptions, an analytical expression is obtained for the updated (posterior) distributions of the parameters of the fatigue model and of crack size. It is shown that the updated distributions depend on POD and on the prior and updated parameters of the error variance distribution. Finally, the bayesian method proposed here is illustrated taking as a fatigue model the Paris-Erdogan relation, which estimates crack growth based on linear elastic fracture mechanics. Joint failure is considered to occur when the crack depth reaches the thickness of the element where the crack propagates. The evolution of reliability with time is assessed.Copyright