硬岩隧道掘进机性能预测模型研究进展

发布时间：2018-04-08 17:39

本文选题：隧道工程　切入点：隧道掘进机(TBM)　出处：《岩石力学与工程学报》2016年S1期

【摘要】：由于硬岩隧道掘进机(TBM)对地质条件极其敏感,且前期投资较大,准确预测特定地质条件下的TBM性能对于隧道施工方法选择、施工进度安排和成本估计至关重要,同时也是隧道行业内的热门话题。首先回顾国内外TBM性能预测模型的研究进展,对目前常用的TBM性能预测模型进行较为详细地介绍。基于对理论模型和复杂经验模型(总计17个)中使用的岩体参数和机器参数的频率统计,发现影响TBM性能的岩体参数主要包括不连续面间距、岩石单轴抗压强度、不连续面和隧道轴向之间的夹角、隧道直径和岩石脆性等;影响TBM性能的机器参数主要包括单刀推力、刀盘转速、刀具直径、刀间距、刀尖宽度和滚刀岩石接触角等。基于统计结果论述各参数对TBM性能的影响,最后根据国外TBM性能预测模型的发展历程对国内开发TBM性能预测模型提出一些建议。
[Abstract]:Because the hard rock tunnel tunneling machine is very sensitive to geological conditions and has a large investment in the early stage, it is very important to accurately predict the TBM performance under specific geological conditions for the selection of tunnel construction methods, construction schedule and cost estimation.At the same time is also a hot topic in the tunnel industry.Firstly, the research progress of TBM performance prediction model at home and abroad is reviewed, and the commonly used TBM performance prediction model is introduced in detail.Based on the frequency statistics of the rock mass parameters and machine parameters used in the theoretical model and the complex empirical model (17 in total), it is found that the rock mass parameters that affect the performance of TBM mainly include discontinuous plane spacing, uniaxial compressive strength of rock.The machine parameters which affect the performance of TBM include single thrust, rotating speed of cutter head, tool diameter, tool spacing, tip width and rock contact angle of hob, etc, such as the angle between discontinuous surface and tunnel axial direction, tunnel diameter and rock brittleness, etc.Based on the statistical results, the influence of various parameters on the performance of TBM is discussed. Finally, according to the development history of foreign TBM performance prediction models, some suggestions for developing TBM performance prediction models in China are put forward.
【作者单位】：中国科学院武汉岩土力学研究所岩土力学与工程国家重点实验室;武汉大学土木建筑工程学院岩土与结构工程安全湖北省重点实验室;
【基金】：国家重点基础研究发展计划(973)项目(2014CB046904,2015CB058102) 国家自然科学基金重点项目(41130742)~~
【分类号】：U455.31

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