2014
DOI: 10.1016/j.tust.2014.05.007
|View full text |Cite
|
Sign up to set email alerts
|

Introduction of an empirical TBM cutter wear prediction model for pyroclastic and mafic igneous rocks; a case history of Karaj water conveyance tunnel, Iran

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1

Citation Types

0
19
0
1

Year Published

2015
2015
2023
2023

Publication Types

Select...
5
1

Relationship

0
6

Authors

Journals

citations
Cited by 102 publications
(20 citation statements)
references
References 3 publications
0
19
0
1
Order By: Relevance
“…RQD, RMR, Q and GSI) for selected tunnel sections. In addition to the database used to develop prognosis equations, a separate part of the database, mainly containing the data collected after 2009, was used to assess the validity and accuracy of the proposed equations that were developed based on the data for the period 2003 to 2009, which were analyzed and published before [6], [7], [8], [9,] [10], [11]. In this part of the database, each engineering geological unit was considered as an individual tunnel section with average values of geological and TBM performance parameters.…”
Section: Tbm Field Performance Data For Penetration Rate (Rop)mentioning
confidence: 99%
See 3 more Smart Citations
“…RQD, RMR, Q and GSI) for selected tunnel sections. In addition to the database used to develop prognosis equations, a separate part of the database, mainly containing the data collected after 2009, was used to assess the validity and accuracy of the proposed equations that were developed based on the data for the period 2003 to 2009, which were analyzed and published before [6], [7], [8], [9,] [10], [11]. In this part of the database, each engineering geological unit was considered as an individual tunnel section with average values of geological and TBM performance parameters.…”
Section: Tbm Field Performance Data For Penetration Rate (Rop)mentioning
confidence: 99%
“…Many researchers have worked on developing various prediction models or adjustment factors for the common existing models for estimating the performance and penetration rate of hard rock TBMs. Research works by Bruland [1], Barton [2], Yagiz [3], Gong and Zhao [4], Frenzel [5], Hassanpour [6], Hassanpour et al [7], [8], [9], [10], [11], Delisio and Zhao [12], etc. are some of the most recent examples of such studies.…”
Section: Introductionmentioning
confidence: 99%
See 2 more Smart Citations
“…预测理论公式 [4] ;MAIDL 等 [5] 基于 UCS 和 CAI,建 立了切削不同岩石的 432 mm(17 in)滚刀滚动切削 总距离预测公式;FRENZEL 等 [6] 基于 CAI 和工程 数 据 分 析 提 出 了 一 套 滚 刀 消 耗 预 测 模 型 ; HASSANPOUR 等 [7][8] 通过对伊朗一条隧道的滚刀 消耗数据进行分析,建立了基于岩石硬度(Vicker's hardness number of rock, VHNR)和 UCS 的滚刀寿命 预 测 公 式 ; 万 治 昌 等 [9][10][11] 分 析 了 秦 岭 隧 道 TB880E-TBM 的滚刀磨损消耗情况,是国内最早的 滚刀磨损消耗研究;赵战欣 [12][13] 对西秦岭隧道的滚 刀消耗进行了初步分析,发现刀盘外侧区域滚刀消 耗严重;杨延栋等 [14] 从宏观能量理论和微观磨损机 制的角度对滚刀刃的磨损消耗进行了预测。 本文从能量角度,基于两条隧道掘进的滚刀磨 损数据,通过引入滚刀刃单位磨损功和等效磨损函 数等概念,对不同 TBM 刀盘、掘进参数、工程地 质条件和不同刀盘区域的滚刀磨损消耗进行了分析 研究,论证了使用能量方法进行滚刀磨损分析预测 的合理性,并从滚刀磨损消耗的角度为滚刀的安装 布局设计提出了一些建议。 1 基于磨损功的滚刀磨损预测方法 [15] 。图 2 为开挖秦岭隧道的 TB880E TBM 的滚刀消耗和磨损数据 [10] …”
unclassified