Modelling of heating furnace fire scenarios using fault tree analysis, a bayesian network, and a thermal transfer method for system reliability analysis

被引:4
|
作者
Nehal, Naima [1 ]
Lounis, Zakia [2 ]
Bouhadiba, Brahim [1 ]
Lounis, Zoubida [1 ]
机构
[1] Univ Mohamed Ben Ahmed Oran 2, Inst Maintenance & Securite Ind, Lab Ingn Secur Ind & Dev Durable, Secur Ind & Environm, Oran 31000, Algeria
[2] Ecole Natl Polytech Oran Maurice Audin, Lab Mat LABMAT, Oran 31000, Algeria
关键词
System?s reliability; Bayesian network; Fault tree analysis; Performance parameters; Furnace; Probabilistic importance factors; TRANSFER COEFFICIENT; RISK ANALYSIS; FAILURE; HAZARD; SHELL;
D O I
10.1016/j.jlp.2023.104995
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Energy production for oil companies requires high-performance equipment. However, after a certain period of use, this equipment could be damaged, causing numerous problems and defects, impeding production, and leading to incidents that may cause material and human losses. Therefore, it is necessary to master the perfor-mance parameters of each equipment, which are key indicators of its functionality and can indicate the possi-bility of reusing it after inspection and diagnosis. However, it is worth noting that the studied system is a vertical cylindrical furnace in Algeria's refinery. This paper describes a new hybrid approach, a methodology that evaluates system reliability by combining two studies. The first is based on the surety of the system's functioning through an analysis with a fault tree to identify the risks, followed by a quantitative analysis using a Bayesian method. The second study follows the thermal calculation of the equipment's performance parameters, namely: the thermal efficiency (eta), heat transfer coefficient (h), and heat absorbed quantity (Q), using heat balance equations to quantify the heat absorbed quantity and identify the fluid flow regime inside the tube. The calculation considers three cases: The design case, the failure case, and the after renovation case. The originality of this work appears when the collected findings from the second study are fed into the first study's Bayesian Network (BN) to analyse the system's reliability using the calculated parameters. Then, BN is used to calculate the Probabilistic Importance Factors (PIFs) in order to identify the most impactful system components. Finally, a prediction analysis was conducted. The latter reveals that one of the furnace's major faults is the fumes accu-mulation inside the combustion chamber. Corrosion, overheating, coke formation inside the tubes, dumper deformation, and burner tip clogging all contribute to this fault.
引用
收藏
页数:20
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