岩土力学 ›› 2025, Vol. 46 ›› Issue (5): 1595-1604.doi: 10.16285/j.rsm.2024.0938CSTR: 32223.14.j.rsm.2024.0938

• 岩土工程研究 • 上一篇    下一篇

基于隧道掘进机掘进参数的现场岩体力学参数快速估计方法

佘磊1,赵阳1,李炎隆1,李东锋2,宋卿2,郑继光2,陈晨2   

  1. 1. 西安理工大学 旱区水工程生态环境全国重点实验室,陕西 西安 710048;2. 中国水利水电第三工程局有限公司,陕西 西安 710024
  • 收稿日期:2024-07-29 接受日期:2024-10-18 出版日期:2025-05-06 发布日期:2025-05-07
  • 通讯作者: 李炎隆,男,1980年生,博士,教授,主要从事主要研究方向为水利工程施工大数据分析技术。E-mail: liyanlong@xaut.edu.com
  • 作者简介:佘磊,男,1994年生,博士后,副教授,主要从事深埋长大隧洞TBM掘进关键技术方面的研究。E-mail: shelei187@163.com
  • 基金资助:
    国家自然科学基金青年项目(No. 52309171);国家资助博士后人员计划项目(No. GZB20230589);陕西省教育厅科学研究计划项目资助(No. 23JK0560)。

Rapid estimation method for in-site rock mass mechanical parameters using tunnel boring machine tunneling parameters

SHE Lei1, ZHAO Yang1, LI Yan-long1, LI Dong-feng2, SONG Qing2, ZHENG Ji-guang2, CHEN Chen2   

  1. 1. State Key Laboratory of Water Engineering Ecology and Environment in Arid Area, Xi’an University of Technology, Xi’an, Shaanxi 710048, China; 2. Power China Sinohydro Bureau 3 Co., Ltd., Xi’an, Shaanxi 710024, China
  • Received:2024-07-29 Accepted:2024-10-18 Online:2025-05-06 Published:2025-05-07
  • Supported by:
    This work was supported by the Youth Fund of National Natural Science Foundation Projects (52309171), the Postdoctoral Fellowship Program of CPSF (GZB20230589) and and the Scientific Research Program Funded by Education Department of Shaanxi Provincial Government (23JK0560).

摘要:

岩体单轴抗压强度σcm是影响隧道掘进机(tunnel boring machine,简称TBM)围岩开挖及支护优化的重要力学参数之一。为实现TBM工程中现场岩体力学参数的快速准确评估,基于我国4条典型的长距离硬岩隧洞详细编制了包含159组岩体特征、掘进参数、技术指标的TBM综合数据库,提出并推导了适用于TBM刀盘破岩系统的掘进比能SETBM理论方程,建立了SETBMσcm之间的经验模型,并对其有效性进行验证和讨论。研究结果表明:相比于现场贯入度指数FPI,SETBM有效消除了TBM掘进参数和技术指标差异化带来的影响,可作为准确评估岩体可掘性的新可靠指标。依据4种岩体分类标准或系统获取的岩体单轴抗压强度经验关系均表现较好(决定系数R2>0.84),其中基于岩体完整性指数Kv的预测模型性能最佳。利用上下限方程修正后的岩体单轴抗压强度预测新模型的平均相对误差为11.37%,总体预测精度较高。利用海量的TBM掘进参数可以为现场岩体单轴抗压强度的快速估算提供一种新的思路。

关键词: 隧道掘进机, 岩体单轴抗压强度, 掘进参数, 岩体分类系统, 掘进比能

Abstract:

Uniaxial compressive strength σcm of rock mass is a crucial mechanical parameters affecting the excavation and support optimization of tunnel boring machine (TBM) surrounding rock. To rapidly and accurately evaluate in-situ rock mass mechanical parameters in TBM engineering, a comprehensive TBM database with 159 sets of rock mass characteristics, tunneling parameters, and technical indexes was developed from four typical long-distance hard rock tunnels in China. Additionally, the specific energy SETBM theoretical equation, suitable for the TBM cutterhead rock breaking system, was proposed and derived. The empirical model between SETBM and σcm was established, and its validity was verified and discussed. The results show that, compared to FPI, SETBM effectively eliminates the influence of varying TBM excavation parameters and technical indexes, serving as a new reliable index for accurately evaluating rock mass excavatability. The empirical relationship of uniaxial compressive strength of rock mass derived from four rock mass classification criteria demonstrates strong performance (coefficient of determination R2>0.84), with the prediction model based on rock mass integrity index Kv exhibiting the best performance. The new model’s average relative error for predicting uniaxial compressive strength of rock mass, modified by upper and lower limit equations, is 11.37%, indicating high overall prediction accuracy. Utilizing extensive TBM tunneling parameters offers a novel approach to quickly estimate the uniaxial compressive strength of in-situ rock mass.

Key words: tunnel boring machine, uniaxial compressive strength of rock mass, tunneling parameters, classification system of rock mass, specific energy

中图分类号: TU 470
[1] 姜启武, 黄明, 崔明娟, 靳贵晓, 彭仪欣, . 酶诱导碳酸钙沉淀技术加固TBM壁后吹填豆砾石最优配比试验及机制研究[J]. 岩土力学, 2024, 45(7): 2037-2049.
[2] 周小雄, 肖禹航, 龚秋明, 刘晓丽, 刘俊豪, 刘东鑫. 基于图像分析的TBM掘进参数与岩碴特征关系研究[J]. 岩土力学, 2024, 45(4): 1142-1153.
[3] 孙浩凯, 高阳, 朱光轩, 徐飞, 郑新雨, . 隧道掘进机滚刀破岩动态荷载理论模型及试验研究[J]. 岩土力学, 2023, 44(6): 1657-1670.
[4] 闫长斌, 李高留, 陈健, 李严, 杨延栋, 杨风威, 杨继华, . 基于新表面理论的TBM破岩效率评价指标[J]. 岩土力学, 2023, 44(4): 1153-1164.
[5] 张金良, 杨风威, 曹智国, 苏伟林, . 大线速度下超高压水射流破岩试验研究[J]. 岩土力学, 2023, 44(3): 615-623.
[6] 张魁, 杨长, 陈春雷, 彭赐彩, 刘杰, . 激光辅助TBM盘形滚刀压头侵岩缩尺试验研究[J]. 岩土力学, 2022, 43(1): 87-96.
[7] 闫长斌, 汪鹤健, 杨继华, 陈馈, 周建军, 郭卫新, . 利用PLSR-DNN耦合模型预测TBM净掘进速率[J]. 岩土力学, 2021, 42(2): 519-528.
[8] 史林肯, 周辉, 宋明, 卢景景, 张传庆, 路新景, . 深部复合地层TBM开挖扰动模型试验研究[J]. 岩土力学, 2020, 41(6): 1933-1943.
[9] 吴鑫林, 张晓平, 刘泉声, 李伟伟, 黄继敏. TBM岩体可掘性预测及其分级研究[J]. 岩土力学, 2020, 41(5): 1721-1729.
[10] 刘鹤, 刘泉声, 唐旭海, 罗慈友, 万文恺, 陈磊, 潘玉丛, . TBM护盾−围岩相互作用荷载识别方法[J]. 岩土力学, 2019, 40(12): 4946-4954.
[11] 刘泉声,彭星新,黄 兴,雷广峰,魏 莱,刘 鹤,. 全断面隧道掘进机护盾受力监测及卡机预警[J]. , 2018, 39(9): 3406-3414.
[12] 翟淑芳,周小平,毕 靖, . TBM滚刀破岩的广义粒子动力学数值模拟[J]. , 2018, 39(7): 2699-2707.
[13] 刘泉声,赵怡凡,张晓平,孔晓璇. 灰岩隧道掘进机隧道点荷载试验评价岩石强度方法的研究与探讨[J]. , 2018, 39(3): 977-984.
[14] 陈卫忠,马池帅,田洪铭,杨建平,. TBM隧道施工期岩爆预测方法探讨[J]. , 2017, 38(S2): 241-249.
[15] 马池帅,陈卫忠,田洪铭,杨建平,. 基于TBM掘进参数的岩石强度估算方法探讨[J]. , 2017, 38(S2): 295-303.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!