A Risk-based MILP Approach for Optimal Placement of Flammable Gas Detectors

Abstract

Gas detectors play an important role in safety of process plants. In-time detection of flammable gas releases may prevent major fire and explosion as well as property loss in process plants. One of the challenges of the gas detection system design is determining the best layout for detectors in order to reduce the risk of gas releases as much as possible. However, current methods do not address the risk concept in placement of detectors quantitatively. A risk-based methodology is proposed for optimal placement of point type flammable gas detectors in which first the risk (defined as a combination of scenario frequency, delayed ignition probability and damage) is estimated for any release scenario. Then, an MILP (Mixed Integer Linear Programming) formulation called MwRR (Maximum weighted Risk Reduction) is proposed for optimal placement. The methodology uses steady-state dispersion results which is an advantage compared to approaches that use dynamic results. The proposed approach is tested on a real petrochemical process unit. For this purpose, the methodology was implemented in MATLAB programming language and the required dispersion data was prepared by means of DNV PHAST software.