Assessing the reliability of dynamic systems for safety units recovering flare gas, considering covariates

محورهای موضوعی : Statistical Modeling

Abolghasem Nobakhti ¹ , Sadigh Raissi ² , Kaveh Khalili Damghani ³ , Roya Soltani ⁴

1 - Department of Industrial Engineering, College of Engineering, South Tehran Branch, Islamic Azad University
2 - Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran.
3 - Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran
4 - Department of Industrial Engineering Khatam University, Tehran, Iran

تاریخ دریافت : 1402/03/31 تاریخ پذیرش : 1402/05/24 تاریخ انتشار : 1401/09/10

کلید واژه: Reliability assessment, Fault Tree Analysis, Fuzzy Inference System, Flare gas recovery system, Expert elicitation,

چکیده مقاله :

The Flare Gas Recovery System (GR) is a critical component in preventing the release of pollutants into the atmosphere. However, these systems are expensive to install and maintain, so ensuring their reliability and effectiveness during operation is critical task. Two safety system technologies have been developed for GR, the fast opening and closing valve system (OVS) and the closed drum system (CDS), but the dynamic operating conditions and lack of historical data make reliability estimates as a crucial complicated task. To address this issue, we propose a novel approach to develop a system reliability as a response surface based on multiple operating pressure and temperature using a hybrid fault tree and a fuzzy inference system. The result reveals an average 22.4% improvement in reliability for OVS compared to CDS in various operational scenarios. Our proposed method provides an operative technique to assess the reliability of GR security systems considering various operating conditions. Results also can help decision-makers to choose the security technology that best fits their particular application needs, ultimately reducing maintenance of costs while ensuring optimal performance over the long term.

منابع و مأخذ:

[1] C. D. Elvidge, M. D. Bazilian, M. Zhizhin, T. Ghosh, K. Baugh, and F.-C. Hsu, "The potential role of natural gas flaring in
meeting greenhouse gas mitigation targets," Energy strategy reviews, vol. 20, pp. 156-162, 2018.

[2] Sheldon M. Ross, Reliability Theory, Introduction to Probability Models (Third Edition), Academic Press, 2024, Pages 603-651, ISBN 9780443187612, https://doi.org/10.1016/B978-0-44-318761-2.00014-2.

[3] Jintao Xu, Maolei Gui, Rui Ding, Tao Dai, Mengyan Zheng, Xinhong Men, Fanpeng Meng, Tao Yu, Yang Sui, A new approach for dynamic reliability analysis of reactor protection system for HPR1000, Reliability Engineering & System Safety, Volume 234,2023, https://doi.org/10.1016/j.ress.2023.109147.

[4] hiyuan Jiang, Xianzhen Huang, Huizhen Liu, Zhiqun Zheng, Shangjie Li, Shanshan Du, Dynamic reliability analysis of main shaft bearings in wind turbines, International Journal of Mechanical Sciences, Volume 235, 2022,
https://doi.org/10.1016/j.ijmecsci.2022.107721.

[5] Min Xiong, Wenwen Wang, Yu Huang, System dynamic reliability evaluation of multiple failure modes of earth dams subjected to strong earthquake excitation, Soils and Foundations, Volume 63, Issue 2, 2023, https://doi.org/10.1016/j.sandf.2023.101298.

[6] D. PieTrusiAk, "Evaluation of large-scale load-carrying structures of machines with the application of the dynamic effects factor," Eksploatacja i Niezawodność, vol. 19, no. 4, pp. 542-551, 2017.

[7] B. Radim and P. Praaks, "Simulation approach for modeling of dynamic reliability using time dependent acyclic graph," W SKRÓCIE, p. 26, 2006.
[8] S. Rajakarunakaran, A. M. Kumar, and V. A. Prabhu, "Applications of fuzzy faulty tree analysis and expert elicitation for
evaluation of risks in LPG refuelling station," Journal of Loss Prevention in the Process Industries, vol. 33, pp. 109-123, 2015.
[9] D. Wang, P. Zhang, and L. Chen, "Fuzzy fault tree analysis for fire and explosion of crude oil tanks," Journal of Loss Preventionin the Process Industries, vol. 26, no. 6, pp. 1390-1398, 2013.
[10]J. H. Purba, "A fuzzy-based reliability approach to evaluate basic events of fault tree analysis for nuclear power plant probabilistic safety assessment," Annals of Nuclear Energy, vol. 70, pp. 21-29, 2014.
[11]A. A. Baig and R. Ruzli, "Estimation of failure probability using fault tree analysis and fuzzy logic for CO2 transmission,"
International Journal of Environmental Science and Development, vol. 5, no. 1, p. 26, 2014.
[12]V. Renjith, G. Madhu, V. L. G. Nayagam, and A. Bhasi, "Two-dimensional fuzzy fault tree analysis for chlorine release from a chlor-alkali industry using expert elicitation," Journal of hazardous materials, vol. 183, no. 1-3, pp. 103-110, 2010.
[13]I.-H. Choi and D. Chang, "Reliability and availability assessment of seabed storage tanks using fault tree analysis," Ocean engineering, vol. 120, pp. 1-14, 2016.
[14]X. Zhang, L. Sun, H. Sun, Q. Guo, and X. Bai, "Floating offshore wind turbine reliability analysis based on system grading and dynamic FTA," Journal of Wind Engineering and Industrial Aerodynamics, vol. 154, pp. 21-33, 2016.
[15]A. Azadeh, V. Ebrahimipour, and P. Bavar, "A fuzzy inference system for pump failure diagnosis to improve maintenance process: The case of a petrochemical industry," Expert Systems with Applications, vol. 37, no. 1, pp. 627-639, 2010.
[16]R. C. Ratnayake, "Application of a fuzzy inference system for functional failure risk rank estimation: RBM of rotating equipment and instrumentation," Journal of Loss Prevention in the Process Industries, vol. 29, pp. 216-224, 2014.
[17]T. Elsayed, "Fuzzy inference system for the risk assessment of liquefied natural gas carriers during loading/offloading at terminals," Applied Ocean Research, vol. 31, no. 3, pp. 179-185, 2009