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Modelling of heating furnace fire scenarios using fault tree analysis,a bayesian network,and a thermal transfer method for system reliability analysis
Institution:1. Laboratoire de L’Ingénierie de La Sécurité Industrielle et de Développement Durable, Institut de Maintenance et de Sécurité Industrielle, Université Mohamed Ben Ahmed Oran 2, Sécurité Industrielle et Environnement, Oran, 31000, Algeria;2. Laboratoire Matériaux LABMAT, Ecole Nationale Polytechnique D’Oran- Maurice Audin, Oran, 31000, Algeria;1. Swiss Process Safety Consulting GmbH, Schönenbuchstrasse 36, CH-4123, Allschwil, Switzerland;2. Covestro Deutschland AG, Kaiser-Wilhelm-Allee 101–103, D-51373, Leverkusen, Germany;1. UFRJ, Brazil;2. ANP, Brazil;1. College of Safety Science and Engineering, Henan Polytechnic University, Jiaozuo, 454003, Henan, PR China;2. State Collaborative Innovation Center of Coal Work Safety and Clean-efficiency Utilization, Jiaozuo, 454003, Henan, PR China;3. State Key Laboratory Cultivation Base for Gas Geology and Gas Control, Jiaozuo, 454003, Henan, PR China;1. Université de Toulouse, INSA, UPS, Mines d’Albi, ISAE, ICA (Institut Clément Ader), 135 Avenue de Rangueil, Cedex, 31077, Toulouse, France;2. Defence Technology Institute, 47/433 Moo 3, Ban Mai, Pak Kret, Nonthaburi, 11120, Thailand;3. Faculty of Engineering, Burapha University, 169 Long-Hard Bangsaen Road, Chonburi, 20131, Thailand
Abstract: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 performance parameters of each equipment, which are key indicators of its functionality and can indicate the possibility 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 (η), 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 accumulation inside the combustion chamber. Corrosion, overheating, coke formation inside the tubes, dumper deformation, and burner tip clogging all contribute to this fault.
Keywords:System's reliability  Bayesian network  Fault tree analysis  Performance parameters  Furnace  Probabilistic importance factors
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