کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
586244 878202 2012 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Accident modeling approach for safety assessment in an LNG processing facility
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی بهداشت و امنیت شیمی
پیش نمایش صفحه اول مقاله
Accident modeling approach for safety assessment in an LNG processing facility
چکیده انگلیسی

The rapid growth in global demand for natural gas as a fuel has led to expansion of the production capacity of existing gas processing trains and the design of new process trains. The increasing complexity of high performance processing systems leads to more complex failure modes and new safety issues. To physical properties of liquefied natural gas (LNG) such as its cryogenic temperature and flammability and vapor dispersion characteristics, add additional concerns of potential safety issues. Therefore, continuous monitoring and implementation of appropriate actions are essential to prevent, control and mitigate unfavorable consequences of LNG production and use. The newly developed accident modeling approach, SHIPP (System Hazard Identification, Prediction and Prevention), is an important part of a comprehensive safety management system that helps to maintain and manage these safety issues. This approach is used to model accidents in gas processing facilities using safety barriers. It identifies possible causal factors and potential consequences and provides quantitative results by combining fault and event tree analyses. The predictive model employed in this approach helps to forecast the number of abnormal events in ensuing time intervals. In the current work, SHIPP has been validated using data from an LNG processing facility.


► The SHIPP method explains the logic of the accident process in an LNG processing facility.
► The logical relationship of the accident sequence is modeled using safety barriers.
► The results (prior estimation) obtained through FT and ET analyses are directly supported by plant specific data.
► The predictive model forecasts the number of abnormal events happening in the next time intervals.
► The short term prediction has better adequacy and accuracy.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Loss Prevention in the Process Industries - Volume 25, Issue 2, March 2012, Pages 414–423
نویسندگان
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