A new Fuzzy-Bayesian approach for the determination of failure probability due to thermal radiation in domino effect accidents. (February 2021)

• Record Type: Journal Article
• Authors: Dueñas Santana, Julio Ariel; Orozco, Jesús Luis; Furka, Daniel; Furka, Samuel; Boza Matos, Yinet Caridad; Febles Lantigua, Dainelys; González Miranda, Amelia; Barrera González, Mary Carla
• Is Part Of: Engineering failure analysis. Volume 120(2021)
• Publication Date: 2021-02
• Subjects: Domino effect -- Bayesian network -- Expert criteria -- Fuzzy logic -- Failure probability; System failures (Engineering) -- Periodicals; Fracture mechanics -- Periodicals; Reliability (Engineering) -- Periodicals; Pannes -- Périodiques; Rupture, Mécanique de la -- Périodiques; Fiabilité -- Périodiques; Fracture mechanics; Reliability (Engineering); System failures (Engineering); Periodicals; Electronic journals; 620.112
• DOI: 10.1016/j.engfailanal.2020.105106
• Languages: English
• ISSNs: 1350-6307

Abstract

Graphical abstract: Highlights: A Fuzzy-Bayesian approach is proposed for the determination of failure probability. Use of material mechanics for prediction of failure due to thermal radiation. Determination of failure probabilities using Artificial Intelligence. Prediction of the domino effect due to pool fires and their synergic effects. Includes expert criteria for the failure probability using Fuzzy logic. Abstract: In recent years, domino effect accidents and domino effect prediction have been intensively studied by the scientific community. The reason for this is the serious impact of these phenomena on people, the environment, the economy, and society as well. In addition, the European Commission has defined this type of study as mandatory. One scenario that can lead to domino effect propagation is a pool fire, which has high values of thermal radiation. This research proposes a novel five-step approach for the determination of failure probability, especially when taking into consideration the structure mechanism of failure in the case of domino effect propagation due to pool fires. In addition, the determination of time to failure, escalation probability, as well as failure due to the received thermal radiation are combined using expert criteria (Fuzzy logic) to obtain an overall failure probability. In all cases, failure due to the decreasing of the strength material is very likely, due to the actual shape thickness of all of the process units. Highest values of failure probability correspond to process units which are in the same subarea. In order to quantify synergic effects, a Bayesian network is developed resulting in domino effect probabilities of 1.0000E−4, which means that there is a high probability of domino effect occurrence. In order to validate the new proposed approach, this approach in combination with another are applied to an actual hydrocarbon storage area as well.