岩体分类
碎片(计算)
计算机科学
隧道掘进机
采矿工程
地质学
数据挖掘
岩土工程
工程类
结构工程
操作系统
作者
Xu Li,Lei-jie Wu,Yujie Wang,Jinhui Li
标识
DOI:10.1038/s41598-023-37306-7
摘要
Perception of rock condition (RC) is a challenge in tunnel boring machine (TBM) construction due to lack of space and time to observe and detect RC. To overcome this problem, this study aims to extract a new rock fragmentation index (RFI) that can reflect RC from real-time rock fragmentation data of the TBM. First, a comprehensive review of existing rock fragmentation models is conducted, which leads to some candidate RFIs that can reflect RC. Next, these candidate RFIs are investigated using data from 12,237 samples from a well-monitored tunnel boring process of the TBM in a 20,198 m tunnel. Further, a new RFI system is recommended as the parameter involving the optimal models. Finally, a preliminary study of the relationship between these RFIs and RC is carried out, and it is shown that these RFIs can reflect RC to a large extent. In the TBM boring process, these RFIs can be extracted from real-time TBM fragmentation data and used to predict the RC in the field. Therefore, the challenge of RC perception is solved with this new RFI system. The new RFI system offers significant potential for the real-time rock classification, prediction of the surrounding rock collapse potential, and selection of control parameters or support measures during TBM construction. This will be the key to improving TBM construction performance.
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