A stochastic programming approach for the optimization of gas detector placement in offshore platforms. (1st September 2019)

• Record Type: Journal Article
• Authors: Zhou, Cancan; Zhang, Bo; Qiao, Shen; Mu, Chao
• Is Part Of: Ocean engineering. Volume 187(2019)
• Publication Date: 2019-09-01
• Subjects: Offshore platform -- Leakage scenarios -- Gas detector placement -- Computational fluid dynamics (CFD) -- Stochastic programming (SP) -- Particle swarm optimization (PSO) algorithm; Ocean engineering -- Periodicals; Ocean engineering; Periodicals; 620.4162
• DOI: 10.1016/j.oceaneng.2019.106223
• Languages: English
• ISSNs: 0029-8018

Abstract

Abstract: In offshore platforms, effective gas detection system is an essential layer of protection for preventing potential gas release accident from turning to fire and explosion disasters. However, according to statistics the actual efficiency of gas detection systems is still unsatisfactory. In this work, a stochastic programming (SP) approach is proposed to arrange gas detectors in optimal places. Combined with meteorological data and the hydrocarbon releases (HCR) database, the equipment leakage scenarios are envisaged. The computational fluid dynamics (CFD) commercial code Ansys-Fluent is used to simulate selected scenarios and predict the consequences. With the objective of minimizing the cumulative risk of gas leakage scenarios, a stochastic mixed-integer linear programming formulation based on p-median value theorem is proposed. Then particle swarm optimization (PSO) algorithm is used to solve the optimization model. The gas detector placement optimization on an oil drilling production platform (DPP) is also carried out as a case example. This methodology can be used in the design phase of offshore platform and can hopefully enhance the performance of the gas detection system. Highlights: A stochastic programming approach is proposed for the optimization of gas detectors' placement in offshore platform. An effective technique combining the offshore hydrocarbon releases database is provided to scientifically identify potential leakage scenarios and improve risk characterization. The complete accident scenario set (CASS) is constructed by considering the leakage sources and wind fields to enhance the performance of the gas detection system. This methodology can be used in the design phase of offshore platform, giving the high efficiency detector layout scheme on the basis of satisfying the standards and achieving optimal risk control effect of the gas detection system.