WeChat Mini Program
Old Version Features

城市地铁双护盾TBM穿越碎裂石断层加固范围 及施工关键技术研究

Journal of Water Resources and Architectural Engineering(2019)

Cited 4|Views5
Abstract
为解决城市地铁双护盾TBM穿越断层破碎带时掌子面坍塌、卡机等施工难题,利用数值模拟软件模拟碎裂石断层加固与否及管片和围岩位移变化规律,确定隧道纵径向断层加固范围,研究了双护盾TBM穿越碎裂石断层注浆加固技术.研究结果表明:双护盾TBM施工中碎裂石断层影响范围主要为隧道纵向为1.15D范围,径向为2.3D范围,因此建议双护盾TBM穿越碎裂石断层时应在该影响范围内进行注浆加固;断层注浆加固时,利用超前钻机进行钻孔,调整优化注浆压力进行水泥-水玻璃双浆液注浆,同时提出TBM掘进参数建议值,形成了双护盾TBM穿越碎裂石断层施工技术;该施工技术效果显著,注浆加固后碎裂石混合物加固体强度提高了2.62倍,抵抗变形的能力得到了加强,确保了双护盾TBM顺利通过碎裂石断层,提前实现了孖雅区间隧道贯通.
More
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined