Skip to main content

ORIGINAL RESEARCH article

Front. Earth Sci.
Sec. Petrology
Volume 12 - 2024 | doi: 10.3389/feart.2024.1453912

An engineering rock mass quality classification system for deep-buried hard rock tunnels

Provisionally accepted
Zhijue Wu Zhijue Wu 1*Longliang Wu Longliang Wu 2*Tao Lin Tao Lin 1*Wen-jing Niu Wen-jing Niu 1*
  • 1 Guangxi University, Nanning, China
  • 2 Bureau Public Works of Shenzhen Municipality,, Shenzhen,Guangdong, China

The final, formatted version of the article will be published soon.

    Rockburst events occur sporadically following tunnel excavation in deep-buried hard rock formations. These failures in the surrounding rock masses are primarily induced by high ground stress, rendering conventional rock mass quality classification systems less applicable. This study discusses the limitations of existing rock mass quality classification systems when applied to deepburied hard rock tunnels. A rockburst intensity tendency index, quantified through micro-seismic (MS) monitoring, is introduced and integrated into the Rock Mass Rating (RMR) system, resulting in the development of an engineering rock mass quality classification system for deep-buried hard rock tunnels (DHRT-RMR). The development process involves: (i) selecting input parameters, including the rockburst intensity tendency index, and defining their weightings using the Analytic Hierarchy Process (AHP); and (ii) establishing the DHRT-RMR system based on the principles of the RMR system. The rockburst intensity tendency index, DHRT-RMR system, and RMR system are then applied to two test sites selected from a tunnel in southwest China. Results indicate that the standalone use of RMR or the rockburst intensity tendency index is limited in engineering rock mass classification for deep-buried hard rock tunnels. However, the DHRT-RMR system accurately assesses rock mass qualities in such tunnels.

    Keywords: Deep-buried hard rock tunnels, Engineering rock mass quality classification, Micro-seismic monitoring, rockburst intensity tendency index, DHRT-RMR system

    Received: 24 Jun 2024; Accepted: 26 Jul 2024.

    Copyright: © 2024 Wu, Wu, Lin and Niu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Zhijue Wu, Guangxi University, Nanning, China
    Longliang Wu, Bureau Public Works of Shenzhen Municipality,, Shenzhen,Guangdong, China
    Tao Lin, Guangxi University, Nanning, China
    Wen-jing Niu, Guangxi University, Nanning, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.