On the Estimation of Failure Rates of Multiple Pipeline Systems

Caleyo, F.; Alfonso, L.; ́ntara, J. A. Alca; Hallen, J.M.; Lagos, F. Ferna ́ndez; Chow, Hugo

doi:10.1115/ipc2006-10526

Cited by 8 publications

(19 citation statements)

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“…Therefore, it is very difficult to model all factors that affect pipeline's performance. To address this problem pipeline systems can be defined as a group of pipelines (network level), which are modeled by the same point stochastic process (Ascher and Feingold, 1984;Caleyo et al, 2008).…”

Section: Background and Motivationmentioning

confidence: 99%

“…Majority pipeline system repairs typically involve a replacement of only a very small component or part of a system rather than replacing the entire system because repairing the pipes is the most practical and economical rehabilitation approach. The natural gas transmission pipeline networks therefore are considered to be repairable systems (Rigdon and Basu, 2000;Røstum, 2000;Caleyo et al, 2008). For example, Røstum (2000) evaluated statistical methods for modeling pipe failures for individual pipe in a water distribution network.…”

Section: Statistical Models To Predict Pipeline Failuresmentioning

confidence: 99%

“…The most popular stochastic point processes, which can be applied to repairable systems, are the homogeneous Poisson process (NPP), the nonhomogeneous Poisson process (NHPP), the renewal process, and superimposed renewal process (SRP) (Ascher and Feingold, 1984). Also, Caleyo et al (2008) emphasized that the pipeline systems refer to a group of natural gas pipelines, which are modeled by the same point stochastic process. In contrast, differential equations are quite different than the point process approaches.…”

Section: Statistical Models To Predict Pipeline Failuresmentioning

confidence: 99%

“…One example was found for natural gas pipeline system. Caleyo et al (2008) conducted a study to estimate the failure rate of a pipeline population from the historical failure data, which are pooled from multiple pipeline system in Southern Mexico. In the study, Caleyo et al (2008) emphasized that the study was conducted on the basis of the statistical methods for reliability of repairable systems (Caleyo et al, 2008).…”

Section: Statistical Models To Predict Pipeline Failuresmentioning

confidence: 99%

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Statistical Modeling of Corrosion Failures in Natural Gas Transmission Pipelines

2016

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Natural gas pipelines are a critical component of the U.S. energy infrastructure.The safety of these pipelines plays a key role for the gas industry. Therefore, the understanding of failure characteristics and their consequences are very important for designing future operations, operating expenditure, and maintenance decisions.The oil and gas industry spends billions of dollars annually for the corrosionrelated cost of the transmission pipelines, the costs which increases due to aging and deterioration processes in pipeline networks. Therefore, pipeline operators need to rethink their corrosion prevention strategies. These results of corrosion failures are forcing the companies to develop accurate maintenance models based on failure frequency. Statistical methods for modeling pipeline failures and proper maintenance decisions play a key role in future safety of lines, to reduce the rate of occurrence of failures, and the cost-effective operation of pipelines.This thesis is focused on two challenges. The first challenge is to estimate the failure rate of natural gas transmission pipeline networks from the previous incidents' data in the United States. A specific objective of this part is to determine the characterization of the failure modes of the transmission pipelines, and to develop the statistical models based on the reliability of a repairable system. The second challenge is to develop the optimal preventive replacement actions by using well-developed optimization models. The objective of the second part is to choose appropriate iii maintenance policies based on the statistical models and to find the optimal maintenance policies.In this thesis, two of the most commonly applied stochastic models, which are the homogeneous Poisson process and the power law process, are used for the estimation of the failure rate. The point and interval estimators of the failure intensity function are provided and the accuracy of the stochastic models is tested for each determined failure mode. Finally, appropriate maintenance models will be presented for planning preventive maintenance and replacement activities for a repairable and maintainable system. It is assumed that pipeline systems could be restored to operation requirements by some minimal repair process instead of replacement after each failure.iv DEDICATION This thesis is dedicated to my parents who supported me throughout my studies.

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Section: Background and Motivationmentioning

confidence: 99%

Section: Statistical Models To Predict Pipeline Failuresmentioning

confidence: 99%

Section: Statistical Models To Predict Pipeline Failuresmentioning

confidence: 99%

Section: Statistical Models To Predict Pipeline Failuresmentioning

confidence: 99%

See 2 more Smart Citations

Statistical Modeling of Corrosion Failures in Natural Gas Transmission Pipelines

2016

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“…This paper in particular adopts the statistical approach to the reliability of repairable systems (Rigdon and Basu 2000;Caleyo et al 2008 The statistical approach is data-driven, and may not be suited for equipment with insufficient failure data. If adequate failure data are lacking, decision models such as analytical hierarchical process (AHP), utility theory or expert judgment can be considered.…”

Section: N O T C O P Y E D I T E Dmentioning

confidence: 99%

Risk-Based Maintenance of a Cross-Country Petroleum Pipeline System

Dawotola

Trafali̇s

Mustaffa

et al. 2013

J. Pipeline Syst. Eng. Pract.

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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.

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