Application of DFN approach for the selection of maximized penetration rate model of TBM in hard rock

IF 1.3 4区地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY Journal of Earth System Science Pub Date : 2024-08-31 DOI:10.1007/s12040-024-02376-2

Enayatallah Emami Meybodi, Syed Khaliq Hussain

{"title":"Application of DFN approach for the selection of maximized penetration rate model of TBM in hard rock","authors":"Enayatallah Emami Meybodi, Syed Khaliq Hussain","doi":"10.1007/s12040-024-02376-2","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3>Various models have been proposed to estimate the TBM penetration rate. Generally, the input parameters of these models can be divided into two categories: Machine parameters and geological engineering parameters. The engineering geological parameters will significantly influence the penetration rate if the machine operational parameters are kept within a reasonable near-optimal range. However, while some performance prediction models can be used for many common project settings, they have lower accuracy in certain applications. This study compared the observed penetration rate of a hard rock TBM with those predicted by MCSM, Norwegian University of Science and Technology (NTNU), Farrokh–Rostami, and Ramezanzadeh’s models in the Kerman water tunnel (KWT). Next, joint survey data are collected from the different zones of the KWT. For this purpose, a 3D discrete fracture network (DFN) model code was generated in Mathematica© version 13. The joint data’s orientation, persistence, and spacing were used to develop a 3D-DFN model for estimating the blockiness rate (BR) index. The BR index is the actual joint intensity in 2D (P21) and 3D (P32). In this study, the BR index is the newest rock mass parameter introduced and used to predict the penetration rate of TBM. This index can serve as a rock mass parameter that provides excellent and realistic results for predicting penetration rate (PR). The corresponding determination coefficient values of the PR with P32 and P21 are R2 = 0.96 and R2 = 0.98, respectively, and with CIA and UCS, are R2 = 0.42 and R2 = 0.49, respectively. Furthermore, using the DFN model showed its potential to be an accurate and reliable method for the overall estimation of the in-situ rock mass fragmentation, which highly controls the penetration rate of TBM.<h3 data-test=\"abstract-sub-heading\">Research Highlights</h3><ul>\n<li>\nThe penetration rate of a hard rock TBM was compared with the NTNU, MCSM, Farrokh-Rostami, and Ramezanzadeh predictive models in the Kerman water tunnel (KWT).\n</li>\n<li>\nA 3D-Discrete fracture network (DFN) model code was generated.\n</li>\n<li>\nFour different zones of KWT were studied to discriminate rock mass parameters or intact rock parameters that affect the penetration rate of TBM.\n</li>\n<li>\nThe BR index is the newest rock mass parameter that has been introduced and used to predict the penetration rate of TBM.\n</li>\n<li>\nThe Blockiness Rate (BR) index as rock mass parameters has verified that it highly influences the penetration rate of TBM.\n</li>\n</ul>","PeriodicalId":15609,"journal":{"name":"Journal of Earth System Science","volume":"10 1","pages":""},"PeriodicalIF":1.3000,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Earth System Science","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1007/s12040-024-02376-2","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}

引用次数: 0

Abstract

Various models have been proposed to estimate the TBM penetration rate. Generally, the input parameters of these models can be divided into two categories: Machine parameters and geological engineering parameters. The engineering geological parameters will significantly influence the penetration rate if the machine operational parameters are kept within a reasonable near-optimal range. However, while some performance prediction models can be used for many common project settings, they have lower accuracy in certain applications. This study compared the observed penetration rate of a hard rock TBM with those predicted by MCSM, Norwegian University of Science and Technology (NTNU), Farrokh–Rostami, and Ramezanzadeh’s models in the Kerman water tunnel (KWT). Next, joint survey data are collected from the different zones of the KWT. For this purpose, a 3D discrete fracture network (DFN) model code was generated in Mathematica^© version 13. The joint data’s orientation, persistence, and spacing were used to develop a 3D-DFN model for estimating the blockiness rate (BR) index. The BR index is the actual joint intensity in 2D (P₂₁) and 3D (P₃₂). In this study, the BR index is the newest rock mass parameter introduced and used to predict the penetration rate of TBM. This index can serve as a rock mass parameter that provides excellent and realistic results for predicting penetration rate (PR). The corresponding determination coefficient values of the PR with P₃₂ and P₂₁ are R² = 0.96 and R² = 0.98, respectively, and with CIA and UCS, are R² = 0.42 and R² = 0.49, respectively. Furthermore, using the DFN model showed its potential to be an accurate and reliable method for the overall estimation of the in-situ rock mass fragmentation, which highly controls the penetration rate of TBM.

Research Highlights

The penetration rate of a hard rock TBM was compared with the NTNU, MCSM, Farrokh-Rostami, and Ramezanzadeh predictive models in the Kerman water tunnel (KWT).
A 3D-Discrete fracture network (DFN) model code was generated.
Four different zones of KWT were studied to discriminate rock mass parameters or intact rock parameters that affect the penetration rate of TBM.
The BR index is the newest rock mass parameter that has been introduced and used to predict the penetration rate of TBM.
The Blockiness Rate (BR) index as rock mass parameters has verified that it highly influences the penetration rate of TBM.

Abstract Image

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

应用 DFN 方法选择硬岩中隧道掘进机的最大贯入率模型

摘要人们提出了各种模型来估算 TBM 的贯入率。一般来说，这些模型的输入参数可分为两类：机器参数和工程地质参数。如果机器运行参数保持在合理的近似最佳范围内，工程地质参数将对贯入率产生重大影响。然而，虽然一些性能预测模型可用于许多常见的项目设置，但在某些应用中精度较低。本研究比较了在克尔曼输水隧道（KWT）中观测到的硬岩 TBM 贯入率与 MCSM、挪威科技大学（NTNU）、Farrokh-Rostami 和 Ramezanzadeh 的模型预测的贯入率。接下来，从 KWT 的不同区域收集联合勘测数据。为此，在 Mathematica© 13 版本中生成了三维离散断裂网络（DFN）模型代码。利用节理数据的方向、持续性和间距来开发三维-DFN 模型，以估算块度率（BR）指数。阻塞率指数是二维（P21）和三维（P32）中的实际关节强度。在本研究中，BR 指数是最新引入并用于预测 TBM 贯入率的岩体参数。该指数可作为一种岩体参数，为预测贯入率（PR）提供出色而真实的结果。与 P32 和 P21 对应的贯入率决定系数值分别为 R2 = 0.96 和 R2 = 0.98，与 CIA 和 UCS 对应的贯入率决定系数值分别为 R2 = 0.42 和 R2 = 0.49。研究亮点在克尔曼输水隧道（KWT）中，将硬岩 TBM 的贯入率与 NTNU、MCSM、Farrokh-Rostami 和 Ramezanzadeh 预测模型进行了比较。对 KWT 的四个不同区域进行了研究，以区分影响 TBM 贯入率的岩体参数或完整岩石参数。BR 指数是最新引入并用于预测 TBM 贯入率的岩体参数。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Journal of Earth System Science Earth and Planetary Sciences-General Earth and Planetary Sciences

CiteScore

3.20

自引率

5.30%

发文量

226

期刊介绍： The Journal of Earth System Science, an International Journal, was earlier a part of the Proceedings of the Indian Academy of Sciences – Section A begun in 1934, and later split in 1978 into theme journals. This journal was published as Proceedings – Earth and Planetary Sciences since 1978, and in 2005 was renamed ‘Journal of Earth System Science’. The journal is highly inter-disciplinary and publishes scholarly research – new data, ideas, and conceptual advances – in Earth System Science. The focus is on the evolution of the Earth as a system: manuscripts describing changes of anthropogenic origin in a limited region are not considered unless they go beyond describing the changes to include an analysis of earth-system processes. The journal''s scope includes the solid earth (geosphere), the atmosphere, the hydrosphere (including cryosphere), and the biosphere; it also addresses related aspects of planetary and space sciences. Contributions pertaining to the Indian sub- continent and the surrounding Indian-Ocean region are particularly welcome. Given that a large number of manuscripts report either observations or model results for a limited domain, manuscripts intended for publication in JESS are expected to fulfill at least one of the following three criteria. The data should be of relevance and should be of statistically significant size and from a region from where such data are sparse. If the data are from a well-sampled region, the data size should be considerable and advance our knowledge of the region. A model study is carried out to explain observations reported either in the same manuscript or in the literature. The analysis, whether of data or with models, is novel and the inferences advance the current knowledge.