کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4925580 | 1431406 | 2017 | 15 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Probabilistic risk assessment framework for structural systems under multiple hazards using Bayesian statistics
ترجمه فارسی عنوان
چارچوب ارزیابی ریسک احتمالی برای سیستم های ساختمانی تحت چندین خطر با استفاده از آمار بیزی
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کلمات کلیدی
ارزیابی خطر چند ارزیابی، شبکه های بیزی، استنتاج بیزی، آسیب پذیری فراتر از طراحی،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
مهندسی انرژی و فناوری های برق
چکیده انگلیسی
Conventional probabilistic risk assessment (PRA) methodologies (USNRC, 1983; IAEA, 1992; EPRI, 1994; Ellingwood, 2001) conduct risk assessment for different external hazards by considering each hazard separately and independent of each other. The risk metric for a specific hazard is evaluated by a convolution of the fragility and the hazard curves. The fragility curve for basic event is obtained by using empirical, experimental, and/or numerical simulation data for a particular hazard. Treating each hazard as an independently can be inappropriate in some cases as certain hazards are statistically correlated or dependent. Examples of such correlated events include but are not limited to flooding induced fire, seismically induced internal or external flooding, or even seismically induced fire. In the current practice, system level risk and consequence sequences are typically calculated using logic trees to express the causative relationship between events. In this paper, we present the results from a study on multi-hazard risk assessment that is conducted using a Bayesian network (BN) with Bayesian inference. The framework can consider statistical dependencies among risks from multiple hazards, allows updating by considering the newly available data/information at any level, and provide a novel way to explore alternative failure scenarios that may exist due to vulnerabilities.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Nuclear Engineering and Design - Volume 315, 15 April 2017, Pages 20-34
Journal: Nuclear Engineering and Design - Volume 315, 15 April 2017, Pages 20-34
نویسندگان
Shinyoung Kwag, Abhinav Gupta,