Application of Bayesian approach to the assessment of mine gas explosion

Tong, Xing; Fang, Weipeng; Yuan, Shuaiqi; Ma, Jie; Bai, Yiping

doi:10.1016/j.jlp.2018.04.003

Cited by 36 publications

(15 citation statements)

References 24 publications

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“…Historical data is typically used in Bayesian network learning algorithms as the prior probability of each node, and some comprehensive decision-making methods, such as the Delphi method [17] and fuzzy analytic hierarchy process [18] are adopted to consult expert opinions. The prior probability table and conditional probability table of the Bayesian network can be determined through systematic test statistics and expert advice, providing data support for Bayesian network process learning.…”

Section: 2 Conditional Probability Table For Bayesian Nodesmentioning

confidence: 99%

Reliability Evaluation of a Disaster Airflow Emergency Control System Based on Bayesian Networks

Zhang

Guo

et al. 2020

IJE

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This study proposed a novel method for system failure reasoning based on Bayesian networks to solve emergency airflow control system reliability problems. A system fault tree model was established to identify the logical relationship between the units, which was then transformed into a Bayesian network fault analysis model to determine network node states and the conditional probability table, as well as to carry out diagnostic reasoning on the system node branches. The reliability analysis of the model based on Netica Bayesian tool shows that the probability of system failure caused by substation communication node is the highest under normal conditions, and data monitoring and central station communication nodes have a greater impact on intelligent control. By predicting and diagnosing system faults, the optimization of system design is realized on the framework of Bayesian network to improve the reliability, and there by establishing a theoretical foundation for future disaster prevention research.

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Section: 2 Conditional Probability Table For Bayesian Nodesmentioning

confidence: 99%

Reliability Evaluation of a Disaster Airflow Emergency Control System Based on Bayesian Networks

Zhang

Guo

et al. 2020

IJE

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“…An expert scoring method (i.e., the Delphi method) was used for the CPTs of the nodes with multiple states. The Delphi method has been shown to be a feasible alternative for deriving a BN in various domains [39][40][41][42]. In the Delphi method, expert evaluations are typically collected via questionnaires.…”

Section: Conditional Probability Tablesmentioning

confidence: 99%

Quantitative risk assessment of a natural gas pipeline in an underground utility tunnel

Fang

Bai

et al. 2019

Process Safety Progress

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With rapid urbanization in China, many underground utility tunnels have been established these years. This huge underground construction facilitates city life, but may introduce societal risks due to the installation of high-risk pipelines. Natural gas pipelines have the potential to cause catastrophic accident if a gas leakage and a subsequent explosion occurs. The potential hazards in the gas compartments of a utility tunnel are quite different from those in conventional directly buried gas pipelines. This study developed a dynamic quantitative risk analysis method for natural gas pipelines in a utility tunnel. First, potential accident scenarios of natural gas pipelines situated in a utility tunnel were identified and implemented in a Bow-tie diagram based on case studies of typical gas pipeline accidents and expert experience. Then, a Bayesian network was established from the Bow-tie diagram using a mapping algorithm. Based on a comprehensive analysis of the results of probability updating and sensitivity analysis, critical influencing factors were identified. The proposed framework provides a predictive analysis of the gas pipeline accident evolution process from causes to consequences and examines key challenges in gas pipeline risk management in utility tunnels.where P (NM) is the probability of "Near Miss", P (VS-good) represents the probability of good "Ventilation System", and P (VS-poor) indicates the Probability of poor "Ventilation System".

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“…To overcome drawbacks of classical techniques, many scholars have merged classical methods with fuzzy theory or evidence theory, Petri nets and BN. One of the sophisticated techniques, BN, has several advantages as follows [4,5]: (1) They contain multi-state node variables capable of displaying multiple effect factors simultaneously, (2) They have an ability of dynamic probability updating, (3) They can easily demonstrate problems in which nodes represent random variables and arcs represent direct probabilistic dependencies among them, (4) They solve decision models with variables of several types.…”

Section: Introductionmentioning

confidence: 99%

“…Liu et al [9] suggested a new approach to build BN from GO model. Tong et al [5] investigated the mine gas explosion by employing BN. Based expert evaluations and mine gas accident data, they proposed a mine gas explosion model with twenty BN nodes.…”

Section: Introductionmentioning

confidence: 99%

A Bayesian Network-Based Approach for Failure Analysis in Weapon Industry

Güneri

Gül

Yücesan

2021

Journal of Thermal Engineering

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Gun and rifle manufacturing contain various failures in the process of CNC machining, material supply, research & development, infrastructure and, operator. Due to these failures, the enterprise is exposed to great economic losses and a decrease in competition in the global market. In addition, failures in production cause events that seriously threaten human health. Failure analysis can increase safety by determining the cause of potential errors and taking measures for identified errors in the life cycle of the products. Therefore, this study employs a Bayesian Network (BN)based modeling approach for capturing dependency among the basic events and obtaining top event probability. Firstly, a fault tree analysis (FTA) diagram is constructed, since its target is to pinpoint how basic event failures result in a top event (system) failure by an AND/OR logical gate. While, AND logical gate should take place in both cases, it is sufficient to realize one of the states in the OR logical gate. Then, a BN-based on fault tree transformation is applied. A case study in a leading weapon factory that produces various types of guns and rifles in the Black Sea region of Turkey is performed. For the application viewpoint, appropriate control measures can be taken into account to decrease the number of failed products based on the performed failure analysis.

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Application of Bayesian approach to the assessment of mine gas explosion

Cited by 36 publications

References 24 publications

Reliability Evaluation of a Disaster Airflow Emergency Control System Based on Bayesian Networks

Reliability Evaluation of a Disaster Airflow Emergency Control System Based on Bayesian Networks

Quantitative risk assessment of a natural gas pipeline in an underground utility tunnel

A Bayesian Network-Based Approach for Failure Analysis in Weapon Industry

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