Assessing Piping Failure Probability subject to Corrosion under Insulation using Markov Model

One of the damage mechanisms experienced by insulated piping systems in refineries and petrochemical plants are corrosion under insulation (CUI). CUI is found to be a major problem for insulated pipes as it becomes even worse as the pipes age. Gradual metal loss may cause the pipe to leak or in the worst scenario, the pipe may rupture. Since the insulated pipes carry hydrocarbons or other process fluids, the presence of leak may lead to a hazardous situation. Therefore, proper inspection and maintenance of these pipes is necessary for sustaining a safe and continuous operation. Risk-based inspection (RBI) strategy has been adopted to establish the inspection strategy for piping systems where the strategy is based on risk calculated. Risk is defined as the product of the probability of failure and its consequences of failure.
Assessing the probability of failure for piping systems subject to CUI in RBI analysis typically follows the guideline by American Petroleum Institute (API 581) where the method is deterministic. Within the literature, it has been found that no probabilistic model has currently been applied to insulated piping systems to estimate the failure probability. Therefore, this study explores one of the probabilistic approaches which is a continuous-time Markov modeling technique. This paper presents a methodology for the estimation of the failure probability of insulated piping systems containing corrosion defects. First-order reliability method (FORM) is employed for estimating the transition rate of the Markov model due to the presence of nonlinearity in the limit-state function and also in the possible presence of non-normal variables. The methodology is applied to a real case study and the remaining useful life of the insulated pipe is assessed.