Prediction of rockburst based on an accident database

Peixoto, Ana Patricia Bastos; Sousa, L. R.; Sousa, Rosiléa Alves de; Feng, Xia-Ting; Miranda, Tiago F. S.; Martins, Francisco F.

doi:10.1201/b11646-234

Cited by 2 publications

(3 citation statements)

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“…These phenomena are commonly reported in deep underground mining structures, but can also occur in deep tunnels, such as the Jinping II hydroelectric scheme (Figure 5). A rockburst triaxial experimental system is important in predicting these types of events both in mining and in other deep underground projects, and previous analysis of rockburst test results have allowed the authors to develop predictive models to estimate rockburst maximum stress and a risk index [90][91][92]. Rockburst is affected by different factors [9,92].…”

Section: Rockburst Events -Laboratory Experimentsmentioning

confidence: 99%

“…A rockburst triaxial experimental system is important in predicting these types of events both in mining and in other deep underground projects, and previous analysis of rockburst test results have allowed the authors to develop predictive models to estimate rockburst maximum stress and a risk index [90][91][92]. Rockburst is affected by different factors [9,92]. Figure 25 shows the influence diagram listing the factors that affected the probability of a rockburst as well as its potential consequences.…”

Section: Rockburst Events -Laboratory Experimentsmentioning

confidence: 99%

“…The rockburst cases were classified according to geometric characteristics, causes and consequences. DM techniques were then applied to the database with the aim of developing rockburst predictive models [92][93]. In order to understand the circumstances in which rockbursts occur, their magnitude, as well as the different consequences of rockburst, the authors gathered as much information as possible that could provide relevant information regarding the occurrence of the rockburst.…”

Section: In Situ Rockburst Database and Dmmentioning

confidence: 99%

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Int J Earth Environ Sci

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to assess and manage the risks associated underground construction [7][8][9][10]. Most accidents in underground construction are associated with uncertainties. It is therefore essential to develop risk analysis systems.Historically, risk assessment and risk analysis have not assumed particular relevance when evaluating underground projects and other major geotechnical projects. This has been changing, and risk analysis has been recently successfully implemented in major transportation infrastructures projects in UE, USA and Switzerland, using both commercial and research software for risk analysis. Special reference can be made to the Decision Aids for Tunneling (DAT), developed at the Massachusetts Institute of Technology in co-operation with Ecole Polytechnique Fédérale de Lausanne [11]. DAT is an interactive program that uses probabilistic modeling to analyze the effect of geotechnical uncertainties and construction uncertainties on construction costs and time through probabilistic modeling. Recent developments were introduced allowing dealing with other structures like embankments, bridges and engineered geothermal systems.Prediction of geotechnical formation behavior in geoengineering is complex because of the uncertainties associated with the characterization of rock masses. In large projects, there is often a great amount of geotechnical data available which can help in reducing

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Section: Rockburst Events -Laboratory Experimentsmentioning

confidence: 99%