Application of Bayesian network to safety assessment of chemical plants during fire-induced domino effects

Author(s):  
N Khakzad ◽  
G Reniers ◽  
G Landucci
2021 ◽  
Author(s):  
Zhiyuan Han ◽  
Guoshan Xie ◽  
Haiyi Jiang ◽  
Xiaowei Li

Abstract The safety and risk of the long term serviced pressure vessels, especially which serviced more than 20 years, has become one of the most concerned issues in refining and chemical industry and government safety supervision in China. According to the Chinese pressure vessel safety specification TSG 21-2016 “Supervision Regulation on Safety Technology for Stationary Pressure Vessel”, if necessary, safety assessment should be performed for the pressure vessel which reaches the design service life or exceeds 20 years without a definite design life. However, the safety and risk conditions of most pressure vessels have little changes after long term serviced because their failure modes are time-independent. Thus the key problem is to identify the devices with the time-dependent failure modes and assess them based on the failure modes. This study provided a case study on 16 typical refining and chemical plants including 1870 pressure vessels serviced more than 20 years. The quantitative risk and damage mechanisms were calculated based on API 581, the time-dependent and time-independent failure modes were identified, and the typical pressure vessels were assessed based on API 579. Taking the high pressure hydrogenation plant as an example, this study gave the detailed assessment results and conclusions. The results and suggestions in this study are essential for the safety supervision and extending life of long term serviced pressure vessels in China.


Author(s):  
D Matellini ◽  
A Wall ◽  
I Jenkinson ◽  
J Wang ◽  
R Pritchard

2019 ◽  
Vol 73 (3) ◽  
pp. 559-580 ◽  
Author(s):  
Bing Wu ◽  
Tsz Leung Yip ◽  
Xinping Yan ◽  
Zhe Mao

Navigational accidents (collisions and groundings) account for approximately 85% of mari-time accidents, and consequence estimation for such accidents is essential for both emergency resource allocation when such accidents occur and for risk management in the framework of a formal safety assessment. As the traditional Bayesian network requires expert judgement to develop the graphical structure, this paper proposes a mutual information-based Bayesian network method to reduce the requirement for expert judgements. The central premise of the proposed Bayesian network method involves calculating mutual information to obtain the quantitative element among multiple influencing factors. Seven-hundred and ninety-seven historical navigational accident records from 2006 to 2013 were used to validate the methodology. It is anticipated the model will provide a practical and reasonable method for consequence estimation of navigational accidents.


2017 ◽  
Vol 321 ◽  
pp. 830-840 ◽  
Author(s):  
Esmaeil Zarei ◽  
Ali Azadeh ◽  
Nima Khakzad ◽  
Mostafa Mirzaei Aliabadi ◽  
Iraj Mohammadfam

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