摘要
以Maen、Pieve、Cogolo和Varzo 4条隧道为例,本文分析说明了岩体质量分类系统不能预测TBM净掘进速率PR的原因:由于影响岩体可掘进性的因素与影响岩体质量的因素不一样,且岩体质量分类系统多采用半定性半定量的评分形式描述岩体条件,故岩体的质量分数值与TBM的净掘进速率PR很难有一一对应的关系。因此,岩体质量分类系统和基于此的预测模型不能够用来预测TBM的净掘进速率PR。根据TBM施工隧道岩体分类的目的及TBM施工的特点,提出预测TBM净掘进速率PR的岩体分类系统应与评价岩体稳定的岩体分类系统分开进行。用岩体可掘进性分类系统预测净掘进速率PR,用岩体质量分类系统预测TBM利用率U,从而计算出TBM的掘进速率AR。
Taking the TBM performance in four tunnels as case examples, this paper analyzes the two reasons that there are problems in using the conventional rock mass quality classification systems to predict the TBM performance. The first reason is the factors which control the rock mass quality are not the factors that influence the rock mass boreability. The second is that most of the factors in rock mass classification systems are semi - quantitative. As a result of the two reasons, the value of the rock mass quality cannot reflect the rock mass boreabihy. According to the purpose of the rock mass classification for tunnels tunneling by TBM and the features of the TBM cutting process, this paper suggests two systems to classify the rock mass: (a) the rock mass boreability classification system for estimating how difficulty the rock mass are bored by TBM and (b) the rock mass quality classification system for estimating the stability of surrounding rock mass. The factors which are used to classify the rock mass boreability group in the system (a) are lithology, weathering degree and joint characters. The factors which are used to classify the rock mass quality in the system ( b ) are factors which will caus~ geological problems in the cutting ,5 process. The system (a) predicts the net penetration rate ( PR ) of the TBM, the system (b) evaluates the utilization ( U ) of the TBM, then the advance rate ( AR ) of the TBM is calculated by PR and U.
出处
《工程地质学报》
CSCD
2008年第4期470-475,共6页
Journal of Engineering Geology
基金
中国科学院知识创新工程重要方向项目(KZCX2-YW-109,KJCX3-SW-L1)
国家重点基础研究发展规划(973)项目(2002CB412702)
国家自然科学基金项目(40702052)
关键词
TBM
岩体分类
可掘进性
掘进速率预测
TBM, Rock mass classification, Rock mass boreability, Advance rate