Integrated accident risk assessment in mines

2019 ◽  
Vol 11 ◽  
pp. 180-192 ◽  
Author(s):  
M.V. Pelipenko ◽  
◽  
S.V. Balovtsev ◽  
I.I. Aynbinder ◽  
◽  
...  
2020 ◽  
Vol 192 ◽  
pp. 03005
Author(s):  
Gennady Einbinder ◽  
Natalia Mitishova ◽  
Dmitry Radchenko ◽  
Egor Knyazkin

In the modern conditions, the scale of subsoil transformation in the process of mineral extraction is characterized by an increased risk of accidents, often accompanied by man-made disasters. In this regard, hazard analysis and accident risk assessment is the most important scientific and technical task, the solution of which is based on methods for identification of hazards, study of development trends and assessment of consequences of theoretically possible accidents. In relation to development conditions of sulfide ore deposits, only an accident risk assessment with determination of the possible accident hazard degree, as well as preparation and timely correction of measures aimed at reduction of accident risks can ensure an acceptable level of industrial safety at the hazardous production facility.


2013 ◽  
Vol 726-731 ◽  
pp. 1101-1104 ◽  
Author(s):  
Li Na Zheng ◽  
Lin Zhang ◽  
Lei Zhang ◽  
Heng Ming Liu

In this paper, to explore the risk identification, the source term analysis, the consequences calculations, risk assessment, risk management of petrochemical project, a case analysis was conducted, which is a petrochemical company planned 900,000 tons / year of gasoline refining unit construction project. The results showed that the project spill will not spread to the outside environment, the explosion will cause part of the plant severelydamaged, but the accident risk value is lower, the maximum credible accident on the environment could be caused by the less risk. Risk level of the maximum credible accident is acceptable.


2021 ◽  
Vol 33 (6) ◽  
pp. 226-237
Author(s):  
Seon Jung Park ◽  
Seol Hwa Park ◽  
Heui Jung Seo ◽  
Seung Min Park

Coastal safety accidents are characterized by a high proportion of human negligence and repeated occurrences of accidents caused by the same factors. The Korea Coast Guard prepares and implements various countermeasures to prevent accidents at coastal safety accident sites. However, there is a shortage of safety facilities and safety management personnel according to the limited budget. In addition, the ability to be proactively and proactively respond is low due to the limitations of the coastal safety accident risk forecasting system, which relies on the meteorological warning of the Korea Meteorological Administration. In this study, as part of preparing the foundation for establishing a preemptive and active coastal safety management system that can manage accident-causing factors, predict and evaluate risk, and implement response and mitigation measures after an accident occurs before coastal safety accidents occur. The establishment of a risk assessment system was proposed. The main evaluation factors and indicators for risk assessment were established through the analysis of the status of coastal safety accidents. The risk assessment methodology was applied to 40 major hazardous areas designated and managed by the Korea Coast Guard.


2021 ◽  
Vol 10 (2) ◽  
pp. 330-347
Author(s):  
Ana Kuzmanić Skelin ◽  
Lea Vojković ◽  
Dani Mohović ◽  
Damir Zec

Probabilistic maritime accident models based on Bayesian Networks are typically built upon the data available in accident records and the data obtained from human experts knowledge on accident. The drawback of such models is that they do not take explicitly into the account the knowledge on non-accidents as would be required in the probabilistic modelling of rare events. Consequently, these models have difficulties with delivering interpretation of influence of risk factors and providing sufficient confidence in the risk assessment scores. In this work, modelling and risk score interpretation, as two aspects of the probabilistic approach to complex maritime system risk assessment, are addressed. First, the maritime accident modelling is posed as a classification problem and the Bayesian network classifier that discriminates between accident and non-accident is developed which assesses state spaces of influence factors as the input features of the classifier. Maritime accident risk are identified as adversely influencing factors that contribute to the accident. Next, the weight of evidence approach to reasoning with Bayesian network classifier is developed for an objective quantitative estimation of the strength of factor influence, and a weighted strength of evidence is introduced. Qualitative interpretation of strength of evidence for individual accident influencing factor, inspired by Bayes factor, is defined. The efficiency of the developed approach is demonstrated within the context of collision of small passenger vessels and the results of collision risk assessments are given for the environmental settings typical in Croatian nautical tourism. According to the results obtained, recommendations for navigation safety during high density traffic have been distilled.


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