کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
585977 1453270 2015 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
An extended HAZOP analysis approach with dynamic fault tree
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی بهداشت و امنیت شیمی
پیش نمایش صفحه اول مقاله
An extended HAZOP analysis approach with dynamic fault tree
چکیده انگلیسی


• Based on HAZOP analysis, hazard scenario models are built.
• The quantitative hazard assessment approach is proposed by the introduction of DFT.
• The approach can identify hazards and model the time-dependent behavior in chemical plants.

An extended hazard and operability (HAZOP) analysis approach with dynamic fault tree is proposed to identify potential hazards in chemical plants. First, the conventional HAZOP analysis is used to identify the possible fault causes and consequences of abnormal conditions, which are called deviations. Based on HAZOP analysis results, hazard scenario models are built to explicitly represent the propagation pathway of faults. With the quantitative analysis requirements of HAZOP analysis and the time-dependent behavior of real failure events considered, the dynamic fault tree (DFT) analysis approach is then introduced to extend HAZOP analysis. To simplify the quantitative calculation, the DFT model is solved with modularization approach in which a binary decision diagram (BDD) and Markov chain approach are applied to solve static and dynamic subtrees, respectively. Subsequently, the occurrence probability of the top event and the probability importance of each basic event with respect to the top event are determined. Finally, a case study is performed to verify the effectiveness of the approach. Results indicate that compared with the conventional HAZOP approach, the proposed approach does not only identify effectively possible fault root causes but also quantitatively determines occurrence probability of the top event and the most likely fault causes. The approach can provide a reliable basis to improve process safety.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Loss Prevention in the Process Industries - Volume 38, November 2015, Pages 224–232
نویسندگان
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