Paper Info
Title
A stochastic programming approach for gas detector placement using CFD-based dispersion simulations.
Abstract
A stochastic programming formulation is developed for determining the optimal placement of gas detectors in petrochemical facilities. FLACS, a rigorous gas dispersion package, is used to generate hundreds of scenarios with different leak locations and weather conditions. Three problem formulations are investigated: minimization of expected detection time, minimization of expected detection time including a coverage constraint, and a placement based on coverage alone. The extensive forms of these optimization problems are written in Pyomo and solved using CPLEX. A sampling procedure is used to find confidence intervals on the optimality gap and quantify the effectiveness of detector placements on alternate subsamples of scenarios. Results show that the additional coverage constraint significantly improves performance on alternate subsamples. Furthermore, both optimization-based approaches dramatically outperform the coverage-only approach, making a strong case for the use of rigorous dispersion simulation coupled with stochastic programming to improve the effectiveness of these safety systems.
Year
DOI
Venue
2012
10.1016/j.compchemeng.2012.05.010
Computers & Chemical Engineering
Keywords
Field
DocType
Gas leak detection,Process safety,Sensor placement,Stochastic programming,Mixed-integer linear programming
Mathematical optimization,System safety,Process safety,Minification,Sampling (statistics),Computational fluid dynamics,Detector,Stochastic programming,Optimization problem,Mathematics
Journal
Volume
ISSN
Citations 
47
0098-1354
5
PageRank 
References 
Authors
0.53
7
7
Name
Order
Citations
PageRank
Sean Legg191.09
A. J. Benavides-Serrano250.53
J. D. Siirola350.53
Jean-Paul Watson460447.20
S. G. Davis550.53
A. Bratteteig650.53
Carl D. Laird729016.49