Implementing Genetic Algorithms to Assist Oil and Gas Pipeline Integrity Assessment and Intelligent Risk Optimization

Calzada-Orihuela, Gustavo; Urquiza-Beltrán, Gustavo; Ascencio, J.A.; Reyes-Salgado, Gerardo

doi:10.4018/ijoci.2017100104

Cited by 1 publication

(1 citation statement)

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“…Individual risk [ 21 ] and social risk [ 22 , 23 , 24 , 25 , 26 ] can be obtained by integrating physical simulation methods with the vulnerability of hazard-affected carriers in specific cases. Furthermore, the risk level [ 27 , 28 ] can be obtained using a risk matrix, and the subsequent risk management strategy can be obtained with genetic algorithms [ 29 ] or optimization methods. However, obtaining the risk treatment strategy for an oil pipeline accident requires illustrating the incident evolution process to comprehensively identify risk factors; quantitatively analyzing the corresponding effects, benefits, and costs; and comparing the risk treatment options.…”

Section: Introductionmentioning

confidence: 99%

A Risk Treatment Strategy Model for Oil Pipeline Accidents Based on a Bayesian Decision Network Model

Zhang

Wang

et al. 2022

IJERPH

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Risk treatment is an effective way to reduce the risk of oil pipeline accidents. Many risk analysis and treatment strategies and models have been established based on the event tree method, bow-tie method, Bayesian network method, and other methods. Considering the characteristics of the current models, a risk treatment strategy model for oil pipeline accidents based on Bayesian decision network (BDNs) is proposed in this paper. First, the quantitative analysis method used in the Event-Evolution-Bayesian model (EEB model) is used for risk analysis. Second, the consequence weights and initial event likelihoods are added to the risk analysis model, and the integrated risk is obtained. Third, the risk treatment strategy model is established to achieve acceptable risk with optimal resources. The risk treatment options are added to the Bayesian network (BN) risk analysis model as the decision nodes and utility nodes. In this approach, the BN risk analysis model can be transformed into a risk treatment model based on BDNs. Compared to other models, this model can not only identify the risk factors comprehensively and illustrate the incident evolution process clearly, but also can support diverse risk treatment strategies for specific cases, such as to reduce the integrated risk to meet acceptable criterion or to balance the benefit and cost of an initiative. Furthermore, the risk treatment strategy can be updated as the risk context changes.

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