کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6972924 | 1453257 | 2018 | 15 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A global stochastic programming approach for the optimal placement of gas detectors with nonuniform unavailabilities
ترجمه فارسی عنوان
یک رویکرد برنامه ریزی تصادفی جهانی برای جای گذاری مطلوب آشکارسازهای گاز با عدم دسترسی غیرمستقیم
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی شیمی
بهداشت و امنیت شیمی
چکیده انگلیسی
Optimal design of a gas detection systems is challenging because of the numerous sources of uncertainty, including weather and environmental conditions, leak location and characteristics, and process conditions. Rigorous CFD simulations of dispersion scenarios combined with stochastic programming techniques have been successfully applied to the problem of optimal gas detector placement; however, rigorous treatment of sensor failure and nonuniform unavailability has received less attention. To improve reliability of the design, this paper proposes a problem formulation that explicitly considers nonuniform unavailabilities and all backup detection levels. The resulting sensor placement problem is a large-scale mixed-integer nonlinear programming (MINLP) problem that requires a tailored solution approach for efficient solution. We have developed a multitree method which depends on iteratively solving a sequence of upper-bounding master problems and lower-bounding subproblems. The tailored global solution strategy is tested on a real data problem and the encouraging numerical results indicate that our solution framework is promising in solving sensor placement problems. This paper was selected for the special issue in JLPPI from the 2016 International Symposium of the MKO Process Safety Center.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Loss Prevention in the Process Industries - Volume 51, January 2018, Pages 29-35
Journal: Journal of Loss Prevention in the Process Industries - Volume 51, January 2018, Pages 29-35
نویسندگان
Jianfeng Liu, Carl D. Laird,