Correspondence should be addressed to Alex W. Dawotola, a.w.dawotola@tudelft.nl A model is constructed for risk management of crude pipeline subject to rupture on the basis of a methodology that incorporates structured expert judgment and analytic hierarchy process AHP . The risk model calculates frequency of failure and their probable consequences for different segments of crude pipeline, considering various failure mechanisms. Specifically, structured expert judgment is used to provide frequency of failure assessments for identified failure mechanisms of the pipeline. In addition, AHP approach is utilized to obtain relative failure likelihood for attributes of failure mechanisms with very low probability of occurrence. Finally, the expected cost of failure for a given pipeline segment is estimated by combining its frequency of failure and the consequences of failure, estimated in terms of historical costs of failure from the pipeline operator's database. A real-world case study of a crude pipeline is used to demonstrate the application of the proposed methodology.
This paper proposes a data-driven approach in determining an optimal inspection interval for a petroleum pipeline system. The approach accounts for the determination of both the probability of failure and its associated consequences. The probability of failure is estimated by fitting the historical data of failure of the pipeline into either a homogenous Poisson process or non-homogenous Poisson process (power law). The analysis of historical data reveals the Poisoneous form that gives better description of the failure process. The consequences of failure are calculated in terms of economic loss, environmental damage and loss of human life. Both the failure probability and consequences are utilized to estimate the total loss of an operating pipeline system. A risk based integrity maintenance optimization of the pipeline is achieved by minimizing the economic loss, while taking the human risk and maintenance budget as constraints. The proposed framework is utilized in the maintenance planning of a very long cross country petroleum pipeline system. The outcomes are robust and well validated. The framework can be applied to any engineering system that requires inspection and maintenance planning.
In this paper, a data-driven model is applied to derive optimum maintenance strategy for a petroleum pipeline. The model incorporates structured expert judgment (classical model) to calculate the frequency of failure, considering various failure mechanisms. Optimization models are applied to derive optimum maintenance intervals for petroleum pipelines on the basis of the frequency of failure estimated. Two separate maintenance-optimization models are proposed. The first is a use-based optimization model that minimizes the expected total cost from a petroleum pipeline. The second is a benefit/cost (B/C) -ratio model that seeks to maximize the benefit derived from the pipeline, while minimizing operation and failure costs. The B/C-ratio model is less data intensive, and it has been used to optimize failure data obtained in the classical model. In this approach, the maintenance optimization is a further attempt at reducing the influence of subjectivity in maintenance decisions.
In this work, the probabilistic methods have been used to produce a methodology capable to estimate the acceptable level of risk in a cost-benefit framework. The benefits and the costs are weighed against associated risks to aid the decision making process on risk acceptance, from both the individual and societal perspective. Thereafter, acceptable individual and societal risk levels are defined based on historical trend of non-voluntary deaths and overall national fatalities. An example is used to explore the practical application of the method to critical infrastructures such as petroleum pipelines. The results show that the cost-benefit risk framework provides a safety standard that is acceptable from both individual and societal perspectives. and MBA (Energy) from University of Oklahoma, USA. He presently works for SBM Offshore in Houston, Texas as a Package Manager. P.H.A.J.M. van Gelder is a full-time Associate Professor of probabilistic methods in Civil Engineering at Delft University of Technology. He has been involved in research and education on safety and reliability for over 15 years. His research interest is in risk-based hydraulic structural design and extreme value statistics for hydraulic loads determination.
This paper presents a method for assessing the reliability of a corroded pipeline placed in series, with special consideration given to the effect of the length scale imposed by each segment of the pipe. The features of corrosion in different pipe segments are statistically correlated; thus, a failure in one section may impact the adjacent sections. Herein, using a correlation distance parameter, such statistical correlation is described considering the length-scale effects. The reliability of the corroded pipeline is presented in the form of a failure probability. The results show that analysing a corroded pipeline by considering length-scale effects produces a higher failure probability compared with the case where such effects are excluded, even when the parameters that govern corrosion in a pipeline are included in the analysis.
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