Prediction of the tunnel boring machine (TBM) performance is critically important for project scheduling and cost estimation. Various models have been proposed to estimate the TBM performance. However, most of these models used the parameters of rock specimens acquired from the laboratory tests, which differed from the in-situ conditions. It is difficult to apply these models to the engineering practice. In the present study, to overcome these limitations, an in-situ indentation testing system for the force-penetration response was proposed and applied to a TBM-excavated tunnel. A database that integrates 33 groups of in-situ indentation testing (235 tests in total) and the corresponding TBM operating parameters was established, including 12 indentation indices extracted from the force-penetration curve and 6 operating parameters recorded by the TBM. A series of correlation analysis was carried out to investigate the relationships between these indices/parameters. The analysis indicates that the 12 indentation indices are highly or moderately correlated with each other. A similar phenomenon was found in the TBM operating parameters. Consequently, four indentation indices and one operating parameter (field penetration index, FPI) were selected to establish the predictive models. Predictive models of the TBM performance (FPI) with high correlation coefficient (r = 0.960) were proposed using the multiple indices obtained from the in-situ indentation testing.

隧道掘进机的预测(TBM) 性能对于项目调度和成本估算至关重要。已经提出了各种模型来估计 TBM 性能。然而，这些模型中的大多数使用了从实验室测试中获得的岩石标本的参数，这与现场条件不同。很难将这些模型应用到工程实践中。在本研究中，为了克服这些限制，提出了一种用于力渗透响应的原位压痕测试系统，并将其应用于 TBM 开挖隧道。建立了33组原位压痕试验（共235次试验）及相应的TBM运行参数的数据库，包括从力-贯入曲线中提取的12个压痕指标和TBM记录的6个运行参数。进行了一系列相关分析以研究这些指标/参数之间的关系。分析表明，12 个压痕指数彼此高度或中度相关。在 TBM 运行参数中也发现了类似的现象。因此，选择四个压痕指数和一个操作参数（场渗透指数，FPI）来建立预测模型。具有高相关系数的 TBM 性能（FPI）预测模型（选择四个压痕指数和一个操作参数（场渗透指数，FPI）来建立预测模型。具有高相关系数的 TBM 性能（FPI）预测模型（选择四个压痕指数和一个操作参数（场渗透指数，FPI）来建立预测模型。具有高相关系数的 TBM 性能（FPI）预测模型（r  = 0.960) 是使用从原位压痕测试获得的多个指数提出的。