{"title":"喜马拉雅铁路隧道预测岩体状况与实际岩体状况对比研究","authors":"Vikas Yadav, Ashutosh Kainthola","doi":"10.1016/j.pce.2025.104026","DOIUrl":null,"url":null,"abstract":"<div><div>Rishikesh-Karnprayag BG Rail Link project in Uttarakhand Himalaya, presents excavation challenges due to the complex geological setting. This study investigates discrepancies between predicted and actual rock mass conditions, encountered during the excavation of the package-5 tunnel. Despite thorough pre-construction investigation, through bore log data, in-situ tests and geophysical surveys, substantial deviations in rock quality were observed during the construction. Deviation in rock mass conditions force change in support classes, ultimately overrunning the project cost. This study aims to investigate the disparity between the predicted and actual rock mass conditions, with respect to overburden thickness. RMR, Q-System and ÖNORM B 2203, have been utilized to discern the rockmass character. A total of 632 data points were collected in the field. Lithology, presence of shear zones, and overburden thickness have been discussed to understand variance between predicted and actual rockmass condition, during the excavation. Study highlights the presence of shear zones and other uncertainties play a crucial role in discrepancies between predicted and actual conditions. At shallower depths, overestimation of rockmass is identified, with actual RMR values being lesser, along with high deviations. As overburden depth increases, the predicted and actual rockmass distributions become more aligned and fall close to each other. Additionally, four different predictive models—Random Forest (RF), Linear Regression (LR), Support Vector Regression (SVR), and K-Nearest Neighbors (KNN) are also employed in this study to estimate actual rockmass, using predicted rockmass and overburden thickness as features. This research will ultimately aid in better planning and cost management for future Himalayan tunneling projects.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"140 ","pages":"Article 104026"},"PeriodicalIF":4.1000,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparative study of predicted and actual rock mass condition in Himalayan railway tunnels\",\"authors\":\"Vikas Yadav, Ashutosh Kainthola\",\"doi\":\"10.1016/j.pce.2025.104026\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Rishikesh-Karnprayag BG Rail Link project in Uttarakhand Himalaya, presents excavation challenges due to the complex geological setting. This study investigates discrepancies between predicted and actual rock mass conditions, encountered during the excavation of the package-5 tunnel. Despite thorough pre-construction investigation, through bore log data, in-situ tests and geophysical surveys, substantial deviations in rock quality were observed during the construction. Deviation in rock mass conditions force change in support classes, ultimately overrunning the project cost. This study aims to investigate the disparity between the predicted and actual rock mass conditions, with respect to overburden thickness. RMR, Q-System and ÖNORM B 2203, have been utilized to discern the rockmass character. A total of 632 data points were collected in the field. Lithology, presence of shear zones, and overburden thickness have been discussed to understand variance between predicted and actual rockmass condition, during the excavation. Study highlights the presence of shear zones and other uncertainties play a crucial role in discrepancies between predicted and actual conditions. At shallower depths, overestimation of rockmass is identified, with actual RMR values being lesser, along with high deviations. As overburden depth increases, the predicted and actual rockmass distributions become more aligned and fall close to each other. Additionally, four different predictive models—Random Forest (RF), Linear Regression (LR), Support Vector Regression (SVR), and K-Nearest Neighbors (KNN) are also employed in this study to estimate actual rockmass, using predicted rockmass and overburden thickness as features. 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引用次数: 0
摘要
北阿坎德邦喜马拉雅地区的Rishikesh-Karnprayag BG铁路连接项目,由于复杂的地质环境,提出了挖掘挑战。本研究调查了在5号包隧道开挖过程中所遇到的预测与实际岩体条件之间的差异。尽管进行了彻底的施工前调查,但通过钻孔测井数据、现场测试和地球物理测量,在施工过程中观察到岩石质量存在重大偏差。岩体条件的偏差迫使支护等级发生变化,最终超出工程成本。本研究旨在探讨覆盖层厚度预测与实际岩体条件之间的差异。利用RMR、Q-System和ÖNORM B 2203对岩体特征进行了识别。现场共收集了632个数据点。在开挖过程中,讨论了岩性、剪切带的存在和覆盖层厚度,以了解预测和实际岩体状况之间的差异。研究强调,剪切带的存在和其他不确定性在预测和实际条件之间的差异中起着至关重要的作用。在较浅的深度,发现了对岩体的高估,实际RMR值较小,偏差较大。随着覆盖层深度的增加,预测岩体分布与实际岩体分布更加接近。此外,本研究还采用随机森林(RF)、线性回归(LR)、支持向量回归(SVR)和k近邻(KNN)四种不同的预测模型,以预测的岩体和覆盖层厚度为特征来估计实际岩体。这项研究最终将有助于未来喜马拉雅隧道项目更好的规划和成本管理。
Comparative study of predicted and actual rock mass condition in Himalayan railway tunnels
Rishikesh-Karnprayag BG Rail Link project in Uttarakhand Himalaya, presents excavation challenges due to the complex geological setting. This study investigates discrepancies between predicted and actual rock mass conditions, encountered during the excavation of the package-5 tunnel. Despite thorough pre-construction investigation, through bore log data, in-situ tests and geophysical surveys, substantial deviations in rock quality were observed during the construction. Deviation in rock mass conditions force change in support classes, ultimately overrunning the project cost. This study aims to investigate the disparity between the predicted and actual rock mass conditions, with respect to overburden thickness. RMR, Q-System and ÖNORM B 2203, have been utilized to discern the rockmass character. A total of 632 data points were collected in the field. Lithology, presence of shear zones, and overburden thickness have been discussed to understand variance between predicted and actual rockmass condition, during the excavation. Study highlights the presence of shear zones and other uncertainties play a crucial role in discrepancies between predicted and actual conditions. At shallower depths, overestimation of rockmass is identified, with actual RMR values being lesser, along with high deviations. As overburden depth increases, the predicted and actual rockmass distributions become more aligned and fall close to each other. Additionally, four different predictive models—Random Forest (RF), Linear Regression (LR), Support Vector Regression (SVR), and K-Nearest Neighbors (KNN) are also employed in this study to estimate actual rockmass, using predicted rockmass and overburden thickness as features. This research will ultimately aid in better planning and cost management for future Himalayan tunneling projects.
期刊介绍:
Physics and Chemistry of the Earth is an international interdisciplinary journal for the rapid publication of collections of refereed communications in separate thematic issues, either stemming from scientific meetings, or, especially compiled for the occasion. There is no restriction on the length of articles published in the journal. Physics and Chemistry of the Earth incorporates the separate Parts A, B and C which existed until the end of 2001.
Please note: the Editors are unable to consider submissions that are not invited or linked to a thematic issue. Please do not submit unsolicited papers.
The journal covers the following subject areas:
-Solid Earth and Geodesy:
(geology, geochemistry, tectonophysics, seismology, volcanology, palaeomagnetism and rock magnetism, electromagnetism and potential fields, marine and environmental geosciences as well as geodesy).
-Hydrology, Oceans and Atmosphere:
(hydrology and water resources research, engineering and management, oceanography and oceanic chemistry, shelf, sea, lake and river sciences, meteorology and atmospheric sciences incl. chemistry as well as climatology and glaciology).
-Solar-Terrestrial and Planetary Science:
(solar, heliospheric and solar-planetary sciences, geology, geophysics and atmospheric sciences of planets, satellites and small bodies as well as cosmochemistry and exobiology).