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Prediction of TBM penetration rate from brittleness indexes using multiple regression analysis

机译:使用多元回归分析预测脆性指数的TBM渗透率

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Abstract One of the most important aspects in the excavation of tunnels with a Tunnel Boring Machine (TBM) is the reliable prediction of its penetration rate. This affects the planning and other decision making on the organization of the construction site of the tunneling project, and, therefore, total costs. In this study, raw data obtained from the experimental works of different researchers were used to establish the new statistical models for prediction of rock TBM penetration rate from brittleness indexes, B~(1), B~(2), and B~(3). For this, correlation between the TBM penetration rate with brittleness indexes statistically was investigated using multiple regression analyses. In these analyses, the TBM penetration rate was considered to be the dependent variable, which is dependent on the independent variables of the brittleness indexes. The validity of the predictive models was validated by statistical tests. The results showed that statistical models are in good accuracy for prediction of TBM penetration rate, and thus making a rapid assessment of the TBM performance.
机译:摘要隧道镗床(TBM)挖掘隧道挖掘中最重要的方面是其渗透率的可靠预测。这会影响隧道工程施工现场的规划和其他决策,因此总成本。在这项研究中,从不同研究人员的实验过程中获得的原始数据用于建立新的统计模型,用于从脆性指数预测岩石TBM渗透率,B〜(1),B〜(2)和B〜(3 )。为此,使用多元回归分析研究了TBM渗透率与统计级别的旋转性指标之间的相关性。在这些分析中,TBM渗透率被认为是依赖变量,这取决于脆性指标的独立变量。通过统计测试验证了预测模型的有效性。结果表明,统计模型具有良好的准确性,可预测TBM渗透率,从而快速评估TBM性能。

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