Development of deep-underground engineering structures via 2D and 3D RQD prediction using non-invasive CSAMT
文献类型:期刊论文
作者 | Hasan, Muhammad2,3,4,5; Su, Lijun3,4,5![]() |
刊名 | SCIENTIFIC REPORTS
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出版日期 | 2025-01-09 |
卷号 | 15期号:1页码:18 |
关键词 | Rock quality designation (RQD) Geotechnical engineering Rock mass quality Controlled-source audio-frequency magnetotellurics (CSAMT) Engineering structure |
ISSN号 | 2045-2322 |
DOI | 10.1038/s41598-025-85626-7 |
英文摘要 | 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. |
WOS关键词 | ELECTRICAL-RESISTIVITY ; GEOPHYSICAL METHODS ; WAVE VELOCITY ; ROCK ; INDEX ; EXPLORATION ; PARAMETERS ; STRENGTH ; TAIWAN ; REGION |
资助项目 | The National Natural Science Foundation of China's Research Fund for International Young Scientists (RFIS-I) ; National Natural Science Foundation of China ; State Key Laboratory of Mountain Hazards and Engineering Resilience, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences ; International Science and Technology Cooperation Program of Shanghai Cooperation Organization, Science and Technology Department, Xinjiang, China |
WOS研究方向 | Science & Technology - Other Topics |
语种 | 英语 |
WOS记录号 | WOS:001395002400043 |
出版者 | NATURE PORTFOLIO |
资助机构 | The National Natural Science Foundation of China's Research Fund for International Young Scientists (RFIS-I) ; National Natural Science Foundation of China ; State Key Laboratory of Mountain Hazards and Engineering Resilience, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences ; International Science and Technology Cooperation Program of Shanghai Cooperation Organization, Science and Technology Department, Xinjiang, China |
源URL | [http://ir.imde.ac.cn/handle/131551/58669] ![]() |
专题 | 成都山地灾害与环境研究所_山地灾害与地表过程重点实验室 |
通讯作者 | Hasan, Muhammad; Su, Lijun |
作者单位 | 1.Inst Geog Sci & Nat Resources Res CAS, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Geol & Geophys, State Key Lab Lithospher & Environm Coevolut, Beijing 100029, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 4.CAS HEC, Joint Res Ctr Earth Sci, Islamabad, Pakistan 5.Chinese Acad Sci, Inst Mt Hazards & Environm, State Key Lab Mt Hazards & Engn Resilience, Chengdu 610299, Peoples R China |
推荐引用方式 GB/T 7714 | Hasan, Muhammad,Su, Lijun,Cui, Peng,et al. Development of deep-underground engineering structures via 2D and 3D RQD prediction using non-invasive CSAMT[J]. SCIENTIFIC REPORTS,2025,15(1):18. |
APA | Hasan, Muhammad,Su, Lijun,Cui, Peng,&Shang, Yanjun.(2025).Development of deep-underground engineering structures via 2D and 3D RQD prediction using non-invasive CSAMT.SCIENTIFIC REPORTS,15(1),18. |
MLA | Hasan, Muhammad,et al."Development of deep-underground engineering structures via 2D and 3D RQD prediction using non-invasive CSAMT".SCIENTIFIC REPORTS 15.1(2025):18. |
入库方式: OAI收割
来源:成都山地灾害与环境研究所
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