Risk Analysis of Grounding Accidents by Mapping a Fault Tree Into a Bayesian Network

Şakar, Cenk; Töz, Ali Cemal; Büber, Müge; Köseoğlu, Burak

doi:10.1016/j.apor.2021.102764

Cited by 57 publications

(13 citation statements)

References 54 publications

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“…The hazard analysis by Fault Tree Analysis was performed as shown in Figure . The previous Boolean principle was used to identify the underlying cause of dust explosions in Figure …”

Section: Resultsmentioning

confidence: 99%

“…The previous Boolean principle was used to identify the underlying cause of dust explosions in Figure 2. 27 Using the diagram, where the hazards are represented by the letters W1−W10 within the rectangles and the fundamental causes are within circles and pentagons represented by the letters A−U, the probability of dust explosion at a tubular oven is shown in eq 1…”

Section: ■ Results and Discussionmentioning

confidence: 99%

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Dust Explosion Risk Assessment of Extruded Food Production Process by Fault Tree Analysis

Pahasup-anan

Kreetachat

Ruengphrathuengsuka

et al. 2021

ACS Chem. Health Saf.

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Dust explosions in compressed food factories can cause severe injury and death as well as damage to assets. This research aimed to assess the risk of dust explosions using the Fault Tree Analysis (FTA) technique from grain extruded food production. The results showed that there were possible situations in which 14 dust explosions were generated at the belt-drying area of puffed food. Considering some fundamental factors, the primary reason for the most significant dust explosion risk is seen to be welding/cutting operations. These processes create a source of ignition or heat in the environment. Therefore, an extruded food production factory should train welding and metal cutting to prevent dust explosions. Moreover, a flameless venting device and an explosion suppression detector should be installed in dust collectors. The FTA method demonstrated the risk of a dust explosion caused by machinery and equipment that must be reduced and controlled to an acceptable level to prevent the occurrence of dust explosions, which has a serious impact on occupational health assets and the environment.

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“…The hazard analysis by Fault Tree Analysis was performed as shown in Figure . The previous Boolean principle was used to identify the underlying cause of dust explosions in Figure …”

Section: Resultsmentioning

confidence: 99%

Section: ■ Results and Discussionmentioning

confidence: 99%

Dust Explosion Risk Assessment of Extruded Food Production Process by Fault Tree Analysis

Pahasup-anan

Kreetachat

Ruengphrathuengsuka

et al. 2021

ACS Chem. Health Saf.

View full text Add to dashboard Cite

show abstract

“…Classic grounding risk analysis methods aim to provide an estimate of the probability or frequency of grounding accidents using accident records and expert judgment. Examples are statistical models (e.g., Ventikos et al, 2017;Youssef et al, 2018;Liu et al, 2018); Bayesian network methods (e.g., Uğurlu et al, 2020;Özlem et al, 2020); Fault tree and event tree methods (e.g., Tunçel et al, 2021;Sakar et al, 2021). These models are useful for the evaluation of the probability of grounding risk from a macro-perspective.…”

Section: Scientific Approaches For Grounding Risk Analysismentioning

confidence: 99%

A Predictive Analytics Method for the Avoidance of Ship Grounding in Real Operational Conditions

Taimuri

Zhang

Hirdaris

2022

Day 1 Tue, September 27, 2022

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This paper presents a rapid method for the evaluation of ship grounding risk and the estimation of avoidance action in real operational conditions. The approach makes use of big data analytics from Automatic Identification System (AIS), nowcast and General Bathymetric Chart of the Oceans (GEBCO) to generate potential grounding scenarios. Following the identification of potential grounding scenarios, a Fluid Structure Interaction (FSI) model is adopted to simulate grounding avoidance actions that account for the influence of surrounding water and ship controlling devices in 6- DoF. Application for the case of a passenger ship operating under ice free conditions in the Gulf of Finland demonstrates the potential of the method for the development of improved decision support systems and operational practices.

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“…Hybrid Methodology Risk Scenario [32] AcciMap-ANP Ship grounding accident [33] BN-TRACEr Ship collision [34] ANP-HFACS LPG leakage accident from gas carrier [35] Fuzzy theory-FTA Ship mooring operation [36] FTA-Modified CREAM Oil tanker collision accident [37] BN-TOPSIS Maritime accident prevention [38] FAHP-spatial fuzzy multi-criteria approach Maritime accidents in the South China sea [23] Fuzzy theory-BN Maritime accidents associated with sand carriers [25] FT-ANN-HFACS Maritime accidents associated with sand carriers in coastal waters in China [39] DT-BN Ship oil spill accident [40] FTA-BN Ship grounding accidents [27] ETA-CN Ship grounding accidents [41] SEM-BN Human-related factors in ship grounding accidents [42] FRAM-BN Maritime liquid cargo leakage accidents Lots of complex causal relationships and uncertain risks are involved in shipyard accidents, which can hardly be addressed by statistics-based approaches. Therefore, it is necessary to consider hybrid methodologies to improve the safety management in shipyards by analyzing human-factor-related accidents.…”

Section: Sourcementioning

confidence: 99%

Human-Related Hazardous Events Assessment for Suffocation on Ships by Integrating Bayesian Network and Complex Network

et al. 2022

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To investigate the human-related factors associated with suffocation on ships during docking repair, a comprehensive analysis model composed of a Bayesian network (BN) and a complex network (CN) is proposed in the present study. The principle of event tree analysis (ETA) is firstly applied to identify the hazardous events involved in the accident according to the accident report, based on which the CN would then be developed with the logic relationships among the hazardous events. The improved K-shell decomposition algorithm is utilized to determine the criticality of nodes in the CN, the results of which are then used to develop the BN model within the framework of a human factor analysis classification system (HFACS). Then, the developed BN model can be simulated with the probability distribution of all the nodes within the BN, which are obtained on the basis of node criticality. Finally, the results of the BN simulation are interpreted from the perspectives of a brief analysis, backward analysis and sensitivity analysis. The results are verified with existing studies and the accident investigation report issued by authority, which are presented as evidence to verify the effectiveness of the proposed methodology to evaluate the human-related risk involved in the suffocation on ships. The methodology proposed in this study integrates the advantages of BN and CN to investigate the human-related hazardous events involved in maritime accidents, which can be seen as the main innovation of this work.

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Risk Analysis of Grounding Accidents by Mapping a Fault Tree Into a Bayesian Network

Cited by 57 publications

References 54 publications

Dust Explosion Risk Assessment of Extruded Food Production Process by Fault Tree Analysis

Dust Explosion Risk Assessment of Extruded Food Production Process by Fault Tree Analysis

A Predictive Analytics Method for the Avoidance of Ship Grounding in Real Operational Conditions

Human-Related Hazardous Events Assessment for Suffocation on Ships by Integrating Bayesian Network and Complex Network

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