LAPSE:2024.1151
Published Article

LAPSE:2024.1151
Comparative Analysis of Ultrasonic and Traditional Gas-Leak Detection Systems in the Process Industries: A Monte Carlo Approach
June 21, 2024
Gas leaks can cause disasters at process sites, including fires and explosions, and thus, effective gas-leak detection systems are required. This study investigated the limitations of conventional detectors and introduced an innovative ultrasonic sensor-based approach for continuous monitoring. A new configuration for a stationary remote ultrasonic gas-leak monitoring system is proposed. The selected material was 1-Butene. The detection probability was assessed through a simulation based on a gas-leak scenario, detailing the selection criteria for leak sites and simulation conditions. Computational fluid-dynamics (CFD) simulations were used to evaluate the detection capability of the existing system, whereas Monte Carlo simulations were used to compare it with the proposed ultrasonic system. The CFD simulation was performed by setting the lower detection limit of the concentration-measurement-type gas detector to 600 ppm, and the leak-detection time was approximately 8.895 s. A Monte Carlo simulation accounting for wind direction showed that the existing system’s average detection probability was 3.41%. By integrating the existing and new systems, the detection probability increased by 96.58% and 3.92% compared with that using only the concentration-measurement and ultrasonic measurement methods, respectively. These rates provide valuable insights for future applications in oil refining and petrochemical industries.
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Keywords
Computational Fluid Dynamics, detection probability, fixed monitoring system, gas-leak detection, Monte Carlo simulation, oil refining and petrochemical industries, ultrasonic
Subject
Suggested Citation
Lee JH, Kim Y, Kim I, Hong SB, Yun HS. Comparative Analysis of Ultrasonic and Traditional Gas-Leak Detection Systems in the Process Industries: A Monte Carlo Approach. (2024). LAPSE:2024.1151
Author Affiliations
Lee JH: Fire Insurers Laboratories of Korea Affiliated with Korean Fire Protection Association, 1030, Gyeongchung-daero, Ganam-eup, Yeoju 12661, Republic of Korea; Interdisciplinary Program for Crisis, Disaster and Risk Management, Sungkyunkwan University, Suwon
Kim Y: Stratio, Inc., Seongnam-si 13449, Republic of Korea
Kim I: Sound Camera Business/Software Laboratory, SM Instruments, Inc., Daejeon 34109, Republic of Korea
Hong SB: Interdisciplinary Program for Crisis, Disaster and Risk Management, Sungkyunkwan University, Suwon 16419, Republic of Korea
Yun HS: School of Civil and Architectural Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea [ORCID]
Kim Y: Stratio, Inc., Seongnam-si 13449, Republic of Korea
Kim I: Sound Camera Business/Software Laboratory, SM Instruments, Inc., Daejeon 34109, Republic of Korea
Hong SB: Interdisciplinary Program for Crisis, Disaster and Risk Management, Sungkyunkwan University, Suwon 16419, Republic of Korea
Yun HS: School of Civil and Architectural Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea [ORCID]
Journal Name
Processes
Volume
12
Issue
1
First Page
67
Year
2023
Publication Date
2023-12-27
ISSN
2227-9717
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Original Submission
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PII: pr12010067, Publication Type: Journal Article
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LAPSE:2024.1151
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https://doi.org/10.3390/pr12010067
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[v1] (Original Submission)
Jun 21, 2024
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Jun 21, 2024
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