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Title: A mathematical programming approach for the optimal placement of flame detectors in petrochemical facilities

Abstract

Flame detectors provide an important layer of protection for personnel in petrochemical plants, but effective placement can be challenging. A mixed-integer nonlinear programming formulation is proposed for optimal placement of flame detectors while considering non-uniform probabilities of detection failure. We show that this approach allows for the placement of fire detectors using a fixed sensor budget and outperforms models that do not account for imperfect detection. In this study, we develop a linear relaxation to the formulation and an efficient solution algorithm that achieves global optimality with reasonable computational effort. We integrate this problem formulation into the Python package, Chama, and demonstrate the effectiveness of this formulation on a small test case and on two real-world case studies using the fire and gas mapping software, Kenexis Effigy.

Authors:
 [1];  [2];  [3];  [3];  [4]
  1. Purdue Univ., West Lafayette, IN (United States)
  2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  3. Kenexis Consulting Corporation, Columbus, OH (United States)
  4. Purdue Univ., West Lafayette, IN (United States); Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1570261
Report Number(s):
SAND2019-11845J
Journal ID: ISSN 0957-5820; 679917
Grant/Contract Number:  
AC04-94AL85000; NA0003525
Resource Type:
Accepted Manuscript
Journal Name:
Process Safety and Environmental Protection
Additional Journal Information:
Journal Volume: 132; Journal Issue: C; Journal ID: ISSN 0957-5820
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
47 OTHER INSTRUMENTATION; optimization; flame detection; process safety

Citation Formats

Zhen, Todd, Klise, Katherine A., Cunningham, Sean, Marszal, Edward, and Laird, Carl D. A mathematical programming approach for the optimal placement of flame detectors in petrochemical facilities. United States: N. p., 2019. Web. doi:10.1016/j.psep.2019.08.030.
Zhen, Todd, Klise, Katherine A., Cunningham, Sean, Marszal, Edward, & Laird, Carl D. A mathematical programming approach for the optimal placement of flame detectors in petrochemical facilities. United States. doi:10.1016/j.psep.2019.08.030.
Zhen, Todd, Klise, Katherine A., Cunningham, Sean, Marszal, Edward, and Laird, Carl D. Sun . "A mathematical programming approach for the optimal placement of flame detectors in petrochemical facilities". United States. doi:10.1016/j.psep.2019.08.030.
@article{osti_1570261,
title = {A mathematical programming approach for the optimal placement of flame detectors in petrochemical facilities},
author = {Zhen, Todd and Klise, Katherine A. and Cunningham, Sean and Marszal, Edward and Laird, Carl D.},
abstractNote = {Flame detectors provide an important layer of protection for personnel in petrochemical plants, but effective placement can be challenging. A mixed-integer nonlinear programming formulation is proposed for optimal placement of flame detectors while considering non-uniform probabilities of detection failure. We show that this approach allows for the placement of fire detectors using a fixed sensor budget and outperforms models that do not account for imperfect detection. In this study, we develop a linear relaxation to the formulation and an efficient solution algorithm that achieves global optimality with reasonable computational effort. We integrate this problem formulation into the Python package, Chama, and demonstrate the effectiveness of this formulation on a small test case and on two real-world case studies using the fire and gas mapping software, Kenexis Effigy.},
doi = {10.1016/j.psep.2019.08.030},
journal = {Process Safety and Environmental Protection},
number = C,
volume = 132,
place = {United States},
year = {2019},
month = {12}
}

Journal Article:
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This content will become publicly available on December 1, 2020
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