دانلود مقاله ISI انگلیسی شماره 113794
ترجمه فارسی عنوان مقاله

تجزیه و تحلیل احتمالی خط لوله شبکه گاز طبیعی بر اساس شبکه بیزی

عنوان انگلیسی
Probabilistic analysis of natural gas pipeline network accident based on Bayesian network
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
113794 2017 11 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Journal of Loss Prevention in the Process Industries, Volume 46, March 2017, Pages 126-136

ترجمه کلمات کلیدی
تصادف شبکه خط لوله گاز طبیعی، تجزیه و تحلیل احتمالی، تصادف آبشار شبکه بیزی، تصمیم گیری اضطراری،
کلمات کلیدی انگلیسی
Natural gas pipeline network accident; Probabilistic analysis; Cascading accident; Bayesian network; Emergency decision-making;
پیش نمایش مقاله
پیش نمایش مقاله  تجزیه و تحلیل احتمالی خط لوله شبکه گاز طبیعی بر اساس شبکه بیزی

چکیده انگلیسی

Natural gas pipeline network (NGPN) accident is a kind of catastrophic disaster as the hazard of natural gas may present a large-scale extension in NGPN that can easily result in cascading accidents. In this paper, the Bayesian network (BN) was employed to probabilistically analyze natural gas pipeline network accidents. On the basis of case-studies of typical NGPN accidents, eleven BN nodes were proposed to represent the evolution process of natural gas pipeline network accidents from failure causes to consequences. The conditional probabilities of every BN node were determined by expert knowledge with weighted treatments by the Dempster-Shafer evidence theory. Through giving evidences of some BN nodes with certain state values, the probabilities of evolution stages and consequences of the natural gas pipeline network accident can be estimated. The results indicate that the combination of Bayesian network and Dempster-Shafer evidence theory is an alternative method for evaluating NGPN accident, and the proposed framework can provide a more realistic consequence analysis since it could consider the conditional dependency in the evolution process of the NGPN accident. This study could be helpful for emergency response decision-making and loss prevention.