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51312-01123-A BAYESIAN NETWORK BASED PIPELINE RISK MANAGEMENT

Picture for A BAYESIAN NETWORK BASED PIPELINE RISK MANAGEMENT
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Product Number: 51312-01123-SG
ISBN: 01123 2012 CP
Author: Francois Ayello
Publication Date: 2012
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$20.00
$20.00
Risk is defined as a product of the probability of a hazard causing an adverse event combined with the severity or consequences of that adverse event. Accordingly pipeline risk management should integrate both the concepts of failure frequency and the potential consequences for each hazard scenario. Pipelines pose a particular challenge to risk assessment because they cover an extended geographic region and there many threats to pipeline integrity as well as different consequences depending on the product being transported. Furthermore models and statistical data cannot completely capture the complex time-based phenomena leading to failures. To solve this problem a pipeline risk assessment model has been created using a probabilistic graphical model called a Bayesian Network. The model calculates separately internal and external corrosion risks manufacturing and construction risks natural hazard risks third party damage risks and maintenance/operation error risks. Moreover these risks might lead to a “loss of containment” which has four different consequences: financial impact environmental impact effects on health and safety and public outrage. The Bayesian network model is illustrated through a specific example involving combination of third party damage and corrosion. The geographically-based risk assessment allows the user to prioritize effectively pipeline inspections and repairs.
Risk is defined as a product of the probability of a hazard causing an adverse event combined with the severity or consequences of that adverse event. Accordingly pipeline risk management should integrate both the concepts of failure frequency and the potential consequences for each hazard scenario. Pipelines pose a particular challenge to risk assessment because they cover an extended geographic region and there many threats to pipeline integrity as well as different consequences depending on the product being transported. Furthermore models and statistical data cannot completely capture the complex time-based phenomena leading to failures. To solve this problem a pipeline risk assessment model has been created using a probabilistic graphical model called a Bayesian Network. The model calculates separately internal and external corrosion risks manufacturing and construction risks natural hazard risks third party damage risks and maintenance/operation error risks. Moreover these risks might lead to a “loss of containment” which has four different consequences: financial impact environmental impact effects on health and safety and public outrage. The Bayesian network model is illustrated through a specific example involving combination of third party damage and corrosion. The geographically-based risk assessment allows the user to prioritize effectively pipeline inspections and repairs.
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51314-3851-Corrosion Threat Assessment Using Bayesian Networks

Product Number: 51314-3851-SG
ISBN: 3851 2014 CP
Author: Francois Ayello
Publication Date: 2014
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Picture for Internal Corrosion Direct Assessment Using Bayesian Networks Modeling With Limited Data-A Case Study
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51316-7078-Internal Corrosion Direct Assessment Using Bayesian Networks Modeling With Limited Data-A Case Study

Product Number: 51316-7078-SG
ISBN: 7078 2016 CP
Author: Shan Guan
Publication Date: 2016
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Bayesian networks (BN) are useful tools for corrosion modeling. This paper is a case study demonstrating how to perform Internal Corrosion Direct Assessment (ICDA) using BN modeling with limited data.  A BN model was developed for ICDA of a 50 km refined oil pipeline.  Internal corrosion probability of failure along the pipeline was assessed.
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01008 OFFSHORE RISK BASED CORROSION INTEGRITY MANAGEMENT A NEW METHODOLOGY

Product Number: 51300-01008-SG
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