PERFORMANCE PREDICTION ASSESSMENTS OF A HARD ROCK TBM USED IN MINING DEVELOPMENT

机译：矿山开发中硬岩TBM的性能预测评估

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Tunnel boring has shown to be a suitable excavation method on underground expansion.rnMining development requires often long tunnels with limited access points whichrnhave to be constructed on a limited amount of time. In many cases, Tunnel BoringrnMachines (TBMs) can be a good choice of tunnelling method. Planning and risk managementrnis of greater importance for technical successfulness and economic benefitrnon tunnel boring compared to drill and blast tunnelling. Therefore, good predictions ofrnperformances and excavations costs take great importance for this issue. A completernanalysis of geological mapping from probe drilling cores, rock drillability testing andrnTBM log data has been performed in order to analyze performances on a hard rockrnTBM used in mining development. Assessments and comparison between actual andrnperformance predictions by using the NTNU prediction model for hard rock TBMs hasrnbeen carried out.

机译：隧道掘进已被证明是一种适合地下扩展的开挖方法。采矿开发通常需要较长的隧道，且具有有限的出入点，因此必须在有限的时间内建造。在许多情况下，隧道镗床（TBM）可能是隧道方法的不错选择。规划和风险管理对于钻探和爆破隧道技术的成功和经济利益而言，比隧道掘进更重要。因此，对性能和挖掘成本的良好预测对于此问题非常重要。为了分析在采矿开发中使用的硬岩石TBM的性能，已经对探针钻芯，岩石可钻性测试和rnTBM测井数据进行了完整的地质分析。已经使用NTNU预测模型对硬岩TBM进行了实际和性能预测之间的评估和比较。

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来源
《Rapid Excavation and Tunneling Conference 2015 proceedings》|2015年|1272-1288|共17页
会议地点 Washington DC(US)
作者
F.J. Macias; L.N.R. Eide; P.D. Jakobsen; C. Jacobs; A. Bruland;
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作者单位

Department of Civil and Transport Engineering, NTNU;

Norwegian National Rail Administration;

Department of Civil and Transport Engineering, NTNU, andNorwegian Public Roads Administration;

Stillwater Mining CO.;

Department of Civil and Transport Engineering, NTNU;

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1. Rock Joint Rate (RJR); a new method for performance prediction of tunnel boring machines (TBMs) in hard rocks [J] . Maleki Mandi Rasouli Tunnelling and underground space technology . 2018,第MARa期

机译：岩石结合率（RJR）;硬岩隧道掘进机性能预测的新方法
2. Comments on the article "Performance prediction of hard rock TBM using Rock Mass Rating (RMR) system" by J.K. Hamidi et al. [Tunneling and Underground Space Technology 25 (2010) 333-345] [J] . Saffet Yagiz Tunnelling and underground space technology . 2011,第5期

机译：J.K.发表的文章“使用岩石质量评级（RMR）系统预测硬岩TBM的性能” Hamidi等。 [隧道和地下空间技术25（2010）333-345]
3. Response by the authors to S. Yagiz discussion to the paper: J. Khademi Hamidi et al., Performance prediction of hard rock TBM using Rock Mass Rating (RMR) system [Tunnell. Undergr. Space Technol. 25 (2010) 333-345] [J] . Jafar Khademi Hamidi, Kourosh Shahriar, Bahram Rezai, Tunnelling and underground space technology . 2011,第6期

机译：作者对S. Yagiz讨论文件的回应：J. Khademi Hamidi等人，《使用岩石质量评级（RMR）系统预测硬岩TBM的性能》 [Tunnell。本科生太空技术。 25（2010）333-345]
4. Impact of Cutter Ring Design on TBM Performance in Exceptionally Hard Rock: Case Study of TBM Tunneling in Hard Rock Formation in Uma Oya Project, Sri Lanka [C] . Ataollah Rahbar, Jamal Rostami, Juergen Paulzen ITA-AITES world tunnel congress . 2016

机译：刀环设计对超硬岩石中TBM性能的影响：以斯里兰卡乌玛奥亚项目硬岩层中TBM隧道掘进为例
5. A Computational Methodology for Modeling Rock Cutting with a Discrete Element Method: Prediction of TBM Rock Cutting Performance [D] . Moon, Taehyun 2006

机译：用离散元法模拟岩石切割的计算方法：TBM岩石切割性能的预测
6. A multifactor coupling prediction model for the failure depth of floor rocks in fully mechanized caving mining: a numerical and in situ study [O] . Yulong Jiang, Tingting Cai, Xiaoqiang Zhang 2019

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7. From Exploratory Tunnel to Base Tunnel: Hard Rock TBM Performance Prediction by Means of a Stochastic Approach [O] . Andrea Rispoli, Anna Maria Ferrero, Marilena Cardu 2020

机译：从探索性隧道到基隧道：硬岩TBM性能通过随机方法预测
8. Toward Development of a Hard-Rock Mining Machine - Drag Cutter Experiments in Hard, Abrasive Rocks [R] . Morrell, R. J. , Wilson, R. J. 1983

机译：开发硬岩采矿机 - 硬质磨料岩中的切割机实验

PERFORMANCE PREDICTION ASSESSMENTS OF A HARD ROCK TBM USED IN MINING DEVELOPMENT

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