A novel risk evaluation method for fire and explosion accidents in oil depots using bow-tie analysis and risk matrix analysis method based on cloud model theory

Xie, Siqi; Dong, Sheng; Chen, Yinuo; Peng, Yujie; Li, Xincai

doi:10.1016/j.ress.2021.107791

Cited by 68 publications

(23 citation statements)

References 48 publications

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“…[13]. The inductive models are ultimately linked to the structure of an integrated Bow Tie diagram which, in one side, clearly illustrates the relationship between the root causes and aggravating factors that can lead to the creation of an event, as well as, in the other side, the path from the leading event to the potential consequences through the mitigating factors that make up the independent ILP i protection levels, with the aim of limiting its escalation [14].…”

Section: Methodsmentioning

confidence: 99%

The application of the Bow Tie approach in the risk assessment of a municipal solid waste management system

Georgousoglou

Mouzakitis

Adamides

2022

IOP Conf. Ser.: Earth Environ. Sci.

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Effective municipal solid waste management requires rigorous risk assessment, evaluation and monitoring through a risk management system. In this line, this study aims first to highlight the importance of using the Bow Tie risk analysis method as a quantitative analysis tool for optimal waste management, and second to demonstrate the fact that the reliability of the method’s results, depends entirely on the uncertainty inherent in the various estimates of the stakeholders. Methodologically the work is based on two pillars: first, a study of the existing literature on risk management in the context of waste management is undertaken, and second, a bow-tie type risk analysis model is developed. Towards this end, and building on previous work, we concentrate on the highest impact event / hazard, identified in the existing municipal waste management system of the Municipality of Patra, Greece, and we apply the Bow Tie type analysis method in order to re-estimate its risk. This method’s results are then subjected to statistical and sensitivity analysis using Monte Carlo simulation to ensure the reliability of the results. Overall, the impacts of the most important risk are presented, and the advantages of the method are highlighted.

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Section: Methodsmentioning

confidence: 99%

The application of the Bow Tie approach in the risk assessment of a municipal solid waste management system

Georgousoglou

Mouzakitis

Adamides

2022

IOP Conf. Ser.: Earth Environ. Sci.

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“…The CM is a model for the conversion of qualitative concepts and quantitative values proposed on the basis of fuzzy set theory and probability, and it can reveal the inherent relevance of the randomness and ambiguity of certain factors or concepts themselves [27]. It was first proposed in 1995 by Li Deyi, an academician of the Chinese Academy of Engineering, and has been applied in many fields, such as risk assessment [28] and engi-neering benefit evaluation [29]. A CM can take the form of a rectangular cloud, trapezoidal cloud, normal cloud, etc.…”

Section: Evaluation Methods Cloud Model (Cm)mentioning

confidence: 99%

Evaluation of Serviceability of Canal Lining Based on AHP–Simple Correlation Function Method–Cloud Model: A Case Study in Henan Province, China

Zhou

Ma³

et al. 2021

Sustainability

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In the process of sustainable development within modern agriculture, in order to ensure that agricultural production has adequate water resources, canal lining (CL) is often used to transport water in order to reduce water seepage, thus promoting the sustainable utilization of water resources. However, due to the influence of the terrain, environment, human factors and other factors, the CL often suffers a certain degree of damage. Therefore, it is necessary to evaluate the serviceability of the CL, so to realize the sustainable use of the CL strategy. Aiming at the weight assignment of CL evaluation indices that are subjective and not combined with actual index data, a weight calculation method based on the Analytic Hierarchy Process (AHP)–simple correlation function (SCF) method was proposed, and game theory was used to achieve combination weighting. For the evaluation indices with the characteristics of fuzziness and randomness, the cloud model (CM) was used to comprehensively consider these characteristics in order to realize the evaluation. Finally, a method to measure serviceability of CL based on AHP–SCF–CM was proposed. Taking a CL project in China as an example, this method was used to evaluate the serviceability of the CL. The evaluation result showed that the serviceability of the CL was poor, and the qualitative evaluation result was consistent with the actual damage condition of the project; meanwhile, a comparative study was performed in combination with the AHP–Entropy Weight (EW)–unascertained measurement theory (UMT). The quantitative evaluation results of the two methods displayed the same grade of serviceability, which verifies that the method proposed in this paper is more reasonable, objective and feasible from both qualitative and quantitative perspectives. Furthermore, the evaluation results lay the foundation for subsequent maintenance and fault prevention of the canal.

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“…Blast Model Based on SVM. Prediction on sensitivity to coal ash blast not only can guide the scientific application of explosion-proof measures and reduce the amount of explosion-proof measure works but also ensure the personal safety of coal seam operators due to the uninterrupted inspection of the explosion hazard at the working face [30]. Therefore, the establishment of SVM-based prediction on sensitivity to coal ash blast model is particularly important.…”

Section: Establishment Of Prediction On Sensitivity To Coal Ashmentioning

confidence: 99%

A Support Vector Machine Based Prediction on Sensitivity to Coal Ash Blast for Different Degrees of Deterioration

et al. 2022

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Coal ash blast is a potential hazard that causes serious disasters in coal mines. In explosion control, research work on coal ash sensitivity prediction is of practical importance to improve accuracy, reduce blindness of explosion protection measures, and strengthen targets. The potential and destructive characteristics of coal ash blast vary greatly from coal to coal, especially in coal mines with complex and changing environments, where the characteristics of coal ash blast show great variability under the influence of various factors. In addition, due to the lack of systematic and comprehensive understanding of the occurrence mechanism of coal ash blast, it is necessary to conduct systematic research on the occurrence mechanism of coal ash blast. Current coal ash blast sensitivity summarizes and concludes prediction methods to create reliable predictions for coal ash blast. A new general learning method, support vector machine (SVM), has been developed, which provides a unified framework for solving limited sample training problems and can better solve small sample training problems. With the purpose of determining the coal mine problem and coal ash sensitivity prediction sensitivity indicators and thresholds, the SVM method is used to set the sensitivity function of each prediction indicator, and the sensitivity of each prediction indicator for the proposed study mine is expressed quantitatively. The experimental results show that the prediction accuracy of SVM for positive and negative categories is 15.6% higher than that of BP neural network and 35.1% higher than that of Apriori algorithm. Therefore, the prediction effectiveness of the SVM algorithm is proved. Therefore, it is practical to adopt SVM method for prediction on sensitivity to coal ash blast and apply the latest statistical learning theory SVM to predict the risk of coal ash.

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A novel risk evaluation method for fire and explosion accidents in oil depots using bow-tie analysis and risk matrix analysis method based on cloud model theory

Cited by 68 publications

References 48 publications

The application of the Bow Tie approach in the risk assessment of a municipal solid waste management system

The application of the Bow Tie approach in the risk assessment of a municipal solid waste management system

Evaluation of Serviceability of Canal Lining Based on AHP–Simple Correlation Function Method–Cloud Model: A Case Study in Henan Province, China

A Support Vector Machine Based Prediction on Sensitivity to Coal Ash Blast for Different Degrees of Deterioration

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