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A quantitative assessment on the placement practices of gas detectors in the process industries

机译:对过程工业中气体探测器放置实践的定量评估

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摘要

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. (c) 2014 Published by Elsevier Ltd.
机译:气体检测是重要的安全系统,具有与其他几个安全保障措施的接口。但是,法规,标准和建议措施的普遍性以及气体探测器放置问题的固有挑战,导致了规范性和定性探测器放置策略的广泛使用。为了利用色散模拟提供的定量信息,作者先前提出,开发和验证了随机编程公式(SP-UV)。该公式确定了气体探测器的布局,该布局在给定一组分散场景的情况下将整体损坏系数的预期值最小化(即,将风险度量标准最小化)。结果证明了数值优化解决气体检测器放置问题的潜力和适用性,同时严格考虑了其固有的不确定性。在这项工作中,实施了四种现有的气体探测器放置方法,并与根据气体探测系统目标使用三种不同性能指标的先前提出的基于定量优化的方法进行了比较。结果提供了证据,证明了使用弥散模拟和数学编程来补充气体探测器放置问题的有效性。 (c)2014年由Elsevier Ltd发布。

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