• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

利用非侵入式可控源音频大地电磁法通过二维和三维岩体质量指标预测进行深部地下工程结构的开发。

Development of deep-underground engineering structures via 2D and 3D RQD prediction using non-invasive CSAMT.

作者信息

Hasan Muhammad, Su Lijun, Cui Peng, Shang Yanjun

机构信息

State Key Laboratory of Mountain Hazards and Engineering Resilience, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610299, China.

Joint Research Center on Earth Sciences, China, CAS-HEC, Pakistan, Islamabad, China.

出版信息

Sci Rep. 2025 Jan 9;15(1):1403. doi: 10.1038/s41598-025-85626-7.

DOI:10.1038/s41598-025-85626-7
PMID:39789080
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11718167/
Abstract

The stability criterion based on the characterization of rock masses can be used to advance deep underground engineering projects. A key geomechanical criterion in geotechnical engineering is rock quality designation (RQD), which assesses risk for engineering design success criteria. Time, cost, and credibility constraints make it difficult to accurately estimate RQD. Point-scale data makes engineering design less precise and confusing, while traditional drilling for RQD estimation are expensive and time-consuming. An innovative geophysical approach to 2D and 3D RQD estimation is presented in this study. It provides easier, faster, and cheaper access to geomechanical volumetric data. So far, no other work has used non-invasive CSAMT to estimate RQD over 1 km depth in a highly diverse rock setting. The suggested approach provides a more precise and thorough evaluation of the rock's integrity for the effective installation of the neutrino detector 700 m below ground. The results are significant because they help us make sense of complicated geological situations, estimate the likelihood of early collapse, and build deep underground structures safely, steadily, and affordably. Our approach leads to more objective indices, helps in the development of more accurate geotechnical structures, and reduces inconsistencies between appropriate geomechanical models and sparse data.

摘要

基于岩体特征的稳定性准则可用于推进深部地下工程项目。岩土工程中的一个关键地质力学准则是岩石质量指标(RQD),它评估工程设计成功标准的风险。时间、成本和可信度限制使得准确估计RQD变得困难。点尺度数据使工程设计不够精确且令人困惑,而传统的用于RQD估计的钻探既昂贵又耗时。本研究提出了一种用于二维和三维RQD估计的创新地球物理方法。它提供了更简便、快速且廉价的获取地质力学体积数据的途径。到目前为止,还没有其他工作在高度多样化的岩石环境中使用非侵入性可控源音频大地电磁法(CSAMT)来估计超过1公里深度的RQD。所建议的方法为有效安装地下700米深处的中微子探测器提供了对岩石完整性更精确和全面的评估。这些结果意义重大,因为它们有助于我们理解复杂的地质情况,估计早期坍塌的可能性,并安全、稳定且经济地建造深部地下结构。我们的方法能得出更客观的指标,有助于开发更精确的岩土结构,并减少合适的地质力学模型与稀疏数据之间的不一致性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b9d/11718167/cc0079f95da0/41598_2025_85626_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b9d/11718167/e9f0bfe0d2cc/41598_2025_85626_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b9d/11718167/c3c8b7a03581/41598_2025_85626_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b9d/11718167/867839cd6198/41598_2025_85626_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b9d/11718167/c69864fcd06a/41598_2025_85626_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b9d/11718167/2b2a79369e4c/41598_2025_85626_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b9d/11718167/e3fb403dc9a9/41598_2025_85626_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b9d/11718167/a7df497650bd/41598_2025_85626_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b9d/11718167/ef6a57943b7e/41598_2025_85626_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b9d/11718167/cc0079f95da0/41598_2025_85626_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b9d/11718167/e9f0bfe0d2cc/41598_2025_85626_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b9d/11718167/c3c8b7a03581/41598_2025_85626_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b9d/11718167/867839cd6198/41598_2025_85626_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b9d/11718167/c69864fcd06a/41598_2025_85626_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b9d/11718167/2b2a79369e4c/41598_2025_85626_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b9d/11718167/e3fb403dc9a9/41598_2025_85626_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b9d/11718167/a7df497650bd/41598_2025_85626_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b9d/11718167/ef6a57943b7e/41598_2025_85626_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b9d/11718167/cc0079f95da0/41598_2025_85626_Fig9_HTML.jpg

相似文献

1
Development of deep-underground engineering structures via 2D and 3D RQD prediction using non-invasive CSAMT.利用非侵入式可控源音频大地电磁法通过二维和三维岩体质量指标预测进行深部地下工程结构的开发。
Sci Rep. 2025 Jan 9;15(1):1403. doi: 10.1038/s41598-025-85626-7.
2
Evaluation of rock mass units using a non-invasive geophysical approach.采用非侵入性地球物理方法对岩体单元进行评估。
Sci Rep. 2023 Sep 3;13(1):14493. doi: 10.1038/s41598-023-41570-y.
3
Application of electrical resistivity tomography (ERT) for rock mass quality evaluation.电阻率层析成像(ERT)在岩体质量评价中的应用。
Sci Rep. 2021 Dec 8;11(1):23683. doi: 10.1038/s41598-021-03217-8.
4
Dataset on physical properties and mechanical parameters of limestone rocks from Central Apennines (Italy) by laboratory test on intact rock specimens.通过对意大利亚平宁山脉中部石灰岩完整岩石样本进行实验室测试得出的关于其物理性质和力学参数的数据集。
Data Brief. 2023 Jan 6;46:108886. doi: 10.1016/j.dib.2023.108886. eCollection 2023 Feb.
5
Geomechanical characterization of a heterogenous rock mass using geological and laboratory test results: a case study of the Niobec Mine, Quebec (Canada).利用地质和实验室测试结果对非均质岩体进行地质力学特性描述:以加拿大魁北克省的尼奥贝克矿为例
SN Appl Sci. 2021;3(6):640. doi: 10.1007/s42452-021-04617-1. Epub 2021 May 17.
6
Rock Mechanical Properties and Wellbore Stability of Fractured Dolomite Formations.裂缝性白云岩地层的岩石力学性质与井筒稳定性
ACS Omega. 2023 Sep 11;8(38):35152-35166. doi: 10.1021/acsomega.3c04768. eCollection 2023 Sep 26.
7
Prediction of rock burst intensity based on multi-source evidence weight and error-eliminating theory.基于多源证据权重和误差消除理论的岩爆强度预测。
Environ Sci Pollut Res Int. 2023 Jun;30(29):74398-74408. doi: 10.1007/s11356-023-27609-7. Epub 2023 May 20.
8
A Deep Learning Method for the Prediction of the Index Mechanical Properties and Strength Parameters of Marlstone.一种用于预测泥灰岩力学性能指标和强度参数的深度学习方法。
Materials (Basel). 2022 Oct 5;15(19):6899. doi: 10.3390/ma15196899.
9
Applicability of geomechanical classifications for estimation of strength properties in Brazilian rock masses.地质力学分类在巴西岩体强度特性估算中的适用性。
An Acad Bras Cienc. 2017 Apr-Jun;89(2):859-872. doi: 10.1590/0001-3765201720160065.
10
Research Progress on the Geomechanical Properties of Block-in-Matrix Rocks.基质块体岩石地质力学性质的研究进展
Materials (Basel). 2024 Mar 1;17(5):1167. doi: 10.3390/ma17051167.

引用本文的文献

1
Miniaturizing Controlled-Source EM Transmitters for Urban Underground Surveys: A Bipolar Square-Wave Inverter Approach with SiC-MOSFETs.用于城市地下探测的小型化可控源电磁发射器:一种采用碳化硅金属氧化物半导体场效应晶体管的双极方波逆变器方法
Sensors (Basel). 2025 Jul 4;25(13):4183. doi: 10.3390/s25134183.
2
Energy dissipation and dilation processes of rock mass under incremental cyclic loading and unloading.岩体在增量循环加卸载作用下的能量耗散与扩容过程
Sci Rep. 2025 May 19;15(1):17303. doi: 10.1038/s41598-025-02146-0.

本文引用的文献

1
Development of empirical equations between uniaxial compressive strength and point load index: a case study for sandy dolomite.单轴抗压强度与点荷载指数之间经验方程的建立:以砂质白云岩为例
Sci Rep. 2024 Nov 2;14(1):26399. doi: 10.1038/s41598-024-77169-0.
2
Development of correlations between various engineering rockmass classification systems using railway tunnel data in Garhwal Himalaya, India.利用印度加瓦尔喜马拉雅地区铁路隧道数据建立各种工程岩体分类系统之间的相关性。
Sci Rep. 2024 May 10;14(1):10716. doi: 10.1038/s41598-024-60289-y.
3
Evaluation of rock mass units using a non-invasive geophysical approach.
采用非侵入性地球物理方法对岩体单元进行评估。
Sci Rep. 2023 Sep 3;13(1):14493. doi: 10.1038/s41598-023-41570-y.
4
A probability prediction method for the classification of surrounding rock quality of tunnels with incomplete data using Bayesian networks.一种基于贝叶斯网络的不完整数据隧道围岩质量分类概率预测方法。
Sci Rep. 2022 Nov 18;12(1):19846. doi: 10.1038/s41598-022-19301-6.
5
Application of electrical resistivity tomography (ERT) for rock mass quality evaluation.电阻率层析成像(ERT)在岩体质量评价中的应用。
Sci Rep. 2021 Dec 8;11(1):23683. doi: 10.1038/s41598-021-03217-8.