A risk-based approach to flammable gas detector spacing
TL;DR: To determine the optimum spacing of detectors, it is important to consider the probability that a detector will fail at some time and be inoperative until replaced or repaired, rather than a worst-case evaluation, which means that probability and severity of leak consequences must be evaluated together.
About: This article is published in Journal of Hazardous Materials.The article was published on 2008-11-15. It has received 48 citations till now. The article focuses on the topics: Flammable liquid & Leak.
Citations
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TL;DR: Results show that the additional coverage constraint significantly improves performance on alternate subsamples, making a strong case for the use of rigorous dispersion simulation coupled with stochastic programming to improve the effectiveness of these safety systems.
58 citations
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TL;DR: A strong case for the use of optimal sensor placement using stochastic programming considering Conditional-Value-at-Risk (CVaR) is made for improving safety systems.
Abstract: A stochastic programming formulation considering Conditional-Value-at-Risk (CVaR) is developed for the optimal placement of gas detectors in petrochemical process facilities. A rigorous gas dispersion simulator, FLACS, is used to generate release scenario data for a real process geometry. We consider two problem formulations: minimization of expected detection time and minimization of expected detection time subject to a restriction on CVaR across the scenario set. The extensive form of each stochastic program is formulated in Pyomo and solved using CPLEX. Considering all scenarios, we compare key values and histograms of detection times for both formulations. Minimizing the mean detection time only can lead to optimal detector placements with a good expected behavior, but unacceptable worst-case behavior. The formulations that minimize or constraint CVaR produce sensor placements with significantly better worst-case behavior and fewer scenarios having high detection times. Considering these results, a strong case for the use of optimal sensor placement using stochastic programming considering CVaR is made for improving safety systems.
43 citations
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TL;DR: Four existing approaches for gas detector placement were implemented and compared with the previously proposed quantitative optimization-based approach using three different performance metrics in accordance to the objectives of gas detection systems, providing evidence on the effectiveness of the use of dispersion simulations, and mathematical programming, to supplement the gas detectors placement problem.
Abstract: Gas detection is an important safety system with interfaces to several other safety safeguards. However, the generality of the regulations, standards and recommended practices in conjunction with the inherent challenges of the gas detector placement problem, has resulted in a widespread use of prescriptive and qualitative detector placement strategies. In order to take advantage of the quantitative information provided by dispersion simulations, a stochastic programming formulation (SP-UV) was previously proposed, developed and validated by the authors. This formulation identifies the gas detector layout that minimizes the expected value of an overall damage coefficient (i.e., the minimization of a risk metric) given a set of dispersion scenarios. Results demonstrated the potential and suitability of numerical optimization to solve the gas detector placement problem while rigorously considering its inherent uncertainties. In this work, four existing approaches for gas detector placement were implemented and compared with the previously proposed quantitative optimization-based approach using three different performance metrics in accordance to the objectives of gas detection systems. Results provide evidence on the effectiveness of the use of dispersion simulations, and mathematical programming, to supplement the gas detector placement problem.
31 citations
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TL;DR: This work proposes a methodology to estimate risk of technological hazards, focused on two components: the processing of meteorological databases to define the most probably and conservative scenario of study, and the application of a local social vulnerability index to classify the population.
27 citations
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TL;DR: The results show that an appropriate number of gas detectors with optimal cost-effectiveness can be obtained, and the total leak risk across all potential scenarios can be substantially reduced.
26 citations
References
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01 Jan 1999
1,666 citations
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23 Nov 1992TL;DR: In this article, the authors present a mathematical model for reliability, availability, and risk analysis in computer programs for Reliability and Risk Analysis, which is based on basic mathematics elements of component reliability.
Abstract: "Reliability, Availability, and Risk Analysis in Perspective Basic Mathematics Elements of Component Reliability System Reliability Analysis Reliability and Availability of Repairable Items Selected Topics in Reliability Analysis Risk Analysis Appendix A---Statistical Tables Appendix B---Generic Failure Data Appendix C---Computer Programs for Reliability and Risk Analysis "
173 citations
01 Jun 1975
TL;DR: The Vulnerability Model (VM) as discussed by the authors is a computerized simulation system for assessing damage that results from marine spills of hazardous materials; the final report, summarized here, describes the research background, computational techniques, and preliminary test results associated with the first stage of development of the VM.
Abstract: : The Vulnerability Model (VM) is a computerized simulation system for assessing damage that results from marine spills of hazardous materials; the final report, summarized here, describes the research background, computational techniques, and preliminary test results associated with the first stage of development of the VM. This first stage of model development consisted of the design and implementation of an operational computer simulation, thereby demonstrating the feasibility of the philosophy, concepts, and approaches pertaining to the VM. Certain aspects of the modeling, as now operational, are subject to enhancement by augmentation, increase in precision, or both. Ultimately, the model is intended to be a comprehensive tool for assessing damage resulting from marine spills.
167 citations