Estimation of the performance of the tunnel boring machine (TBM) using uniaxial compressive strength and rock mass rating classification (RMR)–A case study from the Deccan traps,India

The competency of any TBM in any geological condition is determined by a rock or rock mass breakage process. A 12.24 km long tunnel between Maroshi and Ruparel College was excavated by Brihanmumbai municipal corporation (BMC) to improve water supply system of greater Mumbai, India, using open-type hard rock tunnel boring machines (TBMs). In this paper an attempt has been made to establish the relationship between rock mass characteristics i.e. RMR and UCS of the Deccan trap rocks and TBMs performance characteristics for 5.83 km long Maroshi–Vakola tunnel section of the Maroshi–Ruparel college tunnel project. To analyze the effect of variable rock mass conditions on the TBM performance, the operating parameters i.e. thrust force, torque and RPM of the machine, were recorded and intact rock strength was determined. The effect of rock mass properties on machine penetration rate (PR) and the relation with other operational parameters were analyzed. The rock strength affects the rock behaviour under compression. When the rolling cutters indent the rock, the stress exerted must be higher than the rock strength i.e.; the rock strength is directly relevant to the performance of TBM. Studies show that the penetration rate decreases with increase in uniaxial compressive strength (UCS). The comparison of measured penetration rate with empirical model developed by Graham, in which, the penetration rate is computed using UCS and average thrust per cutter, showed good agreement with coefficient of determination (R²), i.e. 0.97. The study shows that the TBM performance was maximum in rock mass rating (RMR) range from 40 to 75, while slower penetration was recorded both in very poor and very good rock masses.     

TBM岩体可掘性预测及其分级研究

全断面硬岩隧道掘进机（tunnel boring machine, TBM）对岩体条件极其敏感,且其前期投入较大,准确地评估岩体可掘性、预测TBM掘进性能对TBM隧道施工至关重要。基于来自中国、伊朗两国涵盖3种不同岩性的5条TBM施工引水隧洞约300组现场数据,以现场贯入度指数FPI为岩体可掘性评价指标,分析了岩石单轴抗压强度UCS、岩体完整性指数 、岩体主要结构面与洞轴线的夹角?、隧洞直径D等与岩体可掘性之间的关系;探讨了适用于岩体可掘性研究的岩体参数统一方法,进一步建立了精度较高的（相关系数为0.768）岩体可掘性经验预测方法。基于该预测方法,运用K中心聚类分析方法,将岩体可掘性分为6类,探讨了不同岩体可掘性条件下TBM平均单刀推力、刀盘转速分布规律,相应成果可为实际工程中TBM施工隧洞岩体可掘性评估、掘进参数的选择、施工进度的安排提供一定的指导。     

水力切缝上方TBM滚刀贯入破坏机制模拟研究

为了提高坚硬岩层隧道掘进机（tunnel boring machine, TBM）贯入度和降低滚刀受力,高压水射流辅助TBM滚刀破岩已在工业界初步应用。为了揭示水力切缝滚刀破岩机制,基于水力切缝岩石滚刀贯入试验进行了三维颗粒流模拟,研究了滚刀贯入力和贯入刚度随切缝深度的变化规律,揭示了不同切缝深度滚刀纵横剖面内的裂纹扩展和力链演化过程,分析了拉裂纹和剪裂纹随切缝深度的变化规律,明确了不同切缝岩石滚刀贯入的破坏模式和破坏机制。结果表明,第1次贯入的贯入刚度和贯入力随切缝深度的增加大致呈线性降低,第2次贯入的峰值力和贯入刚度小于第1次。而且,50～80 mm刀间距的变化对峰值贯入力的影响并不显著。随着切缝深度的增加,滚刀下方力链集中区边缘的倾角变大。由此导致破坏倾向于倾斜向下发展,当刀间距增加时,破坏由切缝一侧倾斜破坏向两切缝中间岩脊倾斜破坏转变,研究结果可为TBM滚刀与水射流布置和切缝深度的选取提供一定参考。     

Full-scale linear cutting test in Chongqing Sandstone and the comparison with field TBM excavation performance

In this study, determination of some machine parameters and performance prediction for tunnel boring machine (TBM) are conducted based on laboratory rock cutting test. Firstly, laboratory full-scale linear cutting test is carried out using 432-mm CCS (constant cross section) disc cutter in Chongqing Sandstone. Then, the input parameters for TBM cutterhead design are extracted; some TBM specifications are determined and then compared to the manufactured values. Finally, laboratory full-scale linear cutting test results are compared with the field TBM excavation performance data collected in Chongqing Yangtze River Tunnel. Results show that laboratory full-scale linear cutting test results, combined with some engineering considerations, can be used for the preliminary and rough design of TBM machine capacity. Meanwhile, combined with some modification factors, it can also well predict the field TBM excavation performance.

     

复合岩层中滚刀旋转切割破岩效率试验研究

TBM掘进经常遇到复合岩层,在该地层中施工对滚刀破岩非常不利。为了提高掘进效率,降低工程造价,开展复合岩层滚刀破岩效率研究很有必要。鉴于此,采用滚刀岩机作用综合试验台对砂岩、花岗岩复合(复合比例为4(25) 6)而成的岩层进行5组刀间距下3种贯入度的3把滚刀同步旋转切割试验;试验过程中监测破岩总法向力、总扭矩,并分别收集两种岩石的岩渣进行筛分、称重;依据试验结果分析不同刀间距、贯入度下的法向力、扭矩及比能的关系。研究表明:不同刀间距时,平均法向力、平均扭矩随贯入度的增加而增大但两者的增加趋势不同,即平均法向力随着贯入度的增加几乎呈直线增大,而平均扭矩随着贯入度的增加其递增趋势减小;不同贯入度下存在不同的最优刀间距;砂岩、花岗岩切割轨迹长度比例为4:6时刀间距与贯入度的比值在14左右,破岩效率最高。     

A Study of Optimal Rock-Cutting Conditions for Hard Rock TBM Using the Discrete Element Method

The efficiency of TBM performance affected by the specific s/p (s: spacing and p: penetration) ratio of the disc cutter is a research issue in demand. This article presents a multi-indentation simulation using discrete element method (DEM) analysis to study the optimal rock-cutting phenomena in terms of the interaction of the s/p ratio with intact rock properties. The multi-indentation simulation attempts to represent a linear cutting machine (LCM) test, which is a full-scale test for evaluating the optimal rock-cutting condition and measuring required reaction forces based on the intact rock condition in general practice. A governing equation relating mechanical rock properties with geometric characteristics for the optimal rock-cutting condition is derived by the numerical simulation, and its performance is evaluated with the result of the laboratory LCM tests. The results of simulations and real LCM tests show that the effective rock-cutting condition corresponding to the minimum specific energy can be estimated by an optimized s/p ratio, which, in turn, is linearly proportional to the square of the material brittleness, B ², and cutter tip width, t (i.e., s/p?=?cB ² t, where c is coefficient). The limitation of the numerical simulation associated with the sample preparation is also discussed.     

基于颗粒流模型的TBM滚刀破岩过程数值模拟研究

为了研究全断面岩石掘进机（TBM）盘型滚刀的破岩机制及其影响因素,采用颗粒流方法建立了岩石与滚刀的二维数值模型,实现了对TBM滚刀破岩过程的模拟。分析表明,滚刀的破岩过程可分为冲击挤压破碎、大量微裂纹生成、张拉性主裂纹扩展3个阶段,证实了滚刀破岩的挤压-张拉破坏理论。在滚刀侵入深度相同的前提下,随着刀圈刃角以及刃宽的增加,滚刀下的压碎区也相应增大,张拉性主裂纹数目增多,滚刀的破岩能力提高;与平刃刀圈相比,楔刃刀圈的“楔块劈裂”作用更加显著,使径向裂纹扩展得更快且更深入岩石内部。TBM滚刀对强度较高或较低岩石的破坏损伤较小,而对中等强度的岩石破坏损伤最为显著。     

Some Attempts for Estimating Rock Strength and Rock Mass Classification from Cutting Force and Investigation of Optimum Operation of Tunnel Boring Machines

Summary. Tunnel face and wall collapse are common during excavations performed by tunnel boring machines (TBMs) due to the difficulty of correctly identifying the properties of the excavated rock. This identification, however, can be simplified by using the cutting force to estimate rock strength, a method that has already proved quite successful in Japanese tunnel excavations. This paper summarizes knowledge relating to the cutting force obtained through tunnel excavation experience, and the relationship between rock strength and TBM operation is discussed. Although TBM operators rely on intuition to set the cutter head speed appropriately, this decision process represents a logical method of operation that takes advantage of the variable speed capability of the cutter head. Selection of appropriate support methods for the excavated face is also a critical issue in tunnel excavation. This selection process is based on the condition of the rock, which is difficult to determine quickly and accurately during tunnel excavation. The present paper uses the excavation of two tunnels to demonstrate that it is possible to assign rock mass classifications accurately based on rock strength when boring a uniform rock type. It is also shown that the rock mass can be classified from the rock strength normalized by the uniaxial compressive strength when boring through mixed rock types.     

Predicting TBM penetration rate in hard rock condition: A comparative study among six XGB-based metaheuristic techniques

A reliable and accurate prediction of the tunnel boring machine(TBM) performance can assist in minimizing the relevant risks of high capital costs and in scheduling tunneling projects.This research aims to develop six hybrid models of extreme gradient boosting(XGB) which are optimized by gray wolf optimization(GWO), particle swarm optimization(PSO), social spider optimization(SSO), sine cosine algorithm(SCA), multi verse optimization(MVO) and moth flame optimization(MFO), for estimation of the TBM penetration rate(PR).To do this, a comprehensive database with 1286 data samples was established where seven parameters including the rock quality designation, the rock mass rating, Brazilian tensile strength(BTS), rock mass weathering, the uniaxial compressive strength(UCS), revolution per minute and trust force per cutter(TFC), were set as inputs and TBM PR was selected as model output.Together with the mentioned six hybrid models, four single models i.e., artificial neural network, random forest regression, XGB and support vector regression were also built to estimate TBM PR for comparison purposes.These models were designed conducting several parametric studies on their most important parameters and then, their performance capacities were assessed through the use of root mean square error, coefficient of determination, mean absolute percentage error, and a10-index.Results of this study confirmed that the best predictive model of PR goes to the PSO-XGB technique with system error of(0.1453, and 0.1325), R~2 of(0.951, and 0.951), mean absolute percentage error(4.0689, and 3.8115), and a10-index of(0.9348, and 0.9496) in training and testing phases, respectively.The developed hybrid PSO-XGB can be introduced as an accurate, powerful and applicable technique in the field of TBM performance prediction.By conducting sensitivity analysis, it was found that UCS, BTS and TFC have the deepest impacts on the TBM PR.     

楔刀作用下岩石微观劣化的试验研究

通过改装RMT-150C系统,使用不同刃角的楔形刀具对花岗岩进行贯切试验,利用DISP声发射测试系统进行声发射的定位特征分析,研究岩石在楔形刀具作用下损伤劣化破坏的全过程。试验结果表明：声发射试验是一种研究TBM滚刀破岩微观机制的有效方法,脆性岩石材料的破坏过程是内部微裂纹的萌生和扩展过程的宏观反映;在楔刃刀具匀速贯入时,声发射信号随着荷载的变化呈一定对应趋势的变化,荷载-贯入度曲线能反映试件内的损伤历程;声发射2D定位结果显示,在岩石破碎区的密实核下方存在“损伤核”,它由微震裂源增生丛聚分布形成,核内劣化程度高,是孕育密实核的场所,为TBM滚刀作用下岩石的宏观破裂现象提供了解释和依据;楔刀跃进式的挤压贯切岩板试件,钝刃刀具产生“球状”损伤核,尖刃刀具产生“水滴状”损伤核,钝刃刀具贯切试件产生更深的贯入度和更宽的损伤核,致使试件中不仅破碎深度大,而且破损范围广,破岩效果优于尖刃刀具。     

Prediction model of tunnel boring machine performance by ensemble neural networks

The penetration rate of a tunnel boring machine (TBM) depends on many factors ranging from the machine design to the geological properties. Therefore it may not be possible to capture this complex relationship in an explicit mathematical expression. In this paper, we propose an ensemble neural network (ENN) to predict TBM performance. Based on site data, a four-parameter ENN model for the prediction of the specific rock mass boreability index is constructed. Such a neural-network-based model has the advantages of taking into account the uncertainties embedded in the site data and making appropriate inferences using very limited data via the re-sampling technique. The ENN-based prediction model is compared with a non-linear regression model derived from the same four parameters. The ENN model outperforms the non-linear regression model.     

基于新表面理论的TBM破岩效率评价指标

岩碴是岩-机作用的直接产物,也是评价隧道掘进机（TBM）破岩效率和优化TBM掘进参数的有效指标。依托兰州水源地建设工程和龙岩万安溪引水工程,开展不同岩性条件下TBM岩碴筛分试验,得到了岩碴粒径分布规律。基于新表面理论,从滚刀破岩能量转化角度出发,提出了一种新的TBM破岩效率评价指标。基于岩碴粒径分布规律和TBM掘进参数统计,探讨了新表面理论指标与比能、岩碴粗糙度指数之间的关系,指出了新表面理论指标在反映岩碴破碎程度和评价TBM破岩效率方面的优势。对新表面理论指标与TBM掘进推力以及刀间距s与贯入度p的比值进行回归分析,得到了硬岩（围岩等级为Ⅱ级）和软岩（围岩等级为III级）掘进条件下的TBM最优掘进推力和s/p取值区间。研究表明：（1）新表面理论指标符合岩石破碎学原理,可准确评价TBM破岩效率。岩碴越是破碎,新表面理论指标越大,掘进能耗越高,此时TBM破岩效率相对较低。（2）新表面理论指标与比能、岩碴粗糙度指数均具有良好的线性相关关系。岩碴越是破碎,破碎单位体积岩石的能量消耗越大,新表面理论指标越大,对应的粗糙度指数越小。软岩掘进条件下TBM掘进比能低于硬岩,而岩碴破碎程度高于硬岩。（...     

关于用岩体分类预测TBM掘进速率AR的讨论

以Maen、Pieve、Cogolo和Varzo 4条隧道为例,本文分析说明了岩体质量分类系统不能预测TBM净掘进速率PR的原因:由于影响岩体可掘进性的因素与影响岩体质量的因素不一样,且岩体质量分类系统多采用半定性半定量的评分形式描述岩体条件,故岩体的质量分数值与TBM的净掘进速率PR很难有一一对应的关系。因此,岩体质量分类系统和基于此的预测模型不能够用来预测TBM的净掘进速率PR。根据TBM施工隧道岩体分类的目的及TBM施工的特点,提出预测TBM净掘进速率PR的岩体分类系统应与评价岩体稳定的岩体分类系统分开进行。用岩体可掘进性分类系统预测净掘进速率PR,用岩体质量分类系统预测TBM利用率U,从而计算出TBM的掘进速率AR。     

Developing new equations for TBM performance prediction in carbonate-argillaceous rocks: a case history of Nowsood water conveyance tunnel

Nowsood water conveyance tunnel is 49 km long and has been designed for transferring 70 m³/s water from Sirvan river southward to Dashte Zahab plain in the west of Iran. This long tunnel has been divided into three sections, namely 1A, 1B and 2. By April 2008, about 5.3 km of the lot 2 of this project, with a total length of 26 km, were excavated by a double-shield TBM. The bored section of tunnel passed through different geological units of three main formations of the Zagross mountain ranges which mainly consist of weak to moderately strong argillaceous-carbonate rocks. This paper will offer an overview of the project, concentrating on the TBM operation, and review the results of the field performance of the machine. Also results of statistical analyses to evaluate correlation of TBM performance parameters with rock mass characteristics will be discussed. The results of machine performance analysis indicated that there are strong relationships between geomechanical parameters and TBM performance parameters in this particular project. In this research some empirical equations and a chart have been developed to estimate TBM performance parameters in similar cases based on common rock mass properties.     

全断面岩石掘进机滚刀最优刀间距计算公式研究

基于剪切与张拉破岩机制,提出拉剪综合失效机制假设;建立了非协同切削与协同切削体积模型,推导了协同切削模式的滚刀比能耗理论模型;通过离散元仿真得到滚刀侵入岩石裂纹长度与贯入度的映射关系;推导出滚刀最优刀间距理论公式;以全断面岩石掘进机（TBM）回转切削试验台为基础,水泥模拟料为切削对象,通过多次压痕试验得到滚刀贯入度和岩石裂纹长度的趋势曲线,验证了仿真结果;通过滚刀滚动破岩进行了12组不同贯入度与刀间距的物理切削试验,统计滚刀做功与岩石破碎体积,拟合得到比能耗关系曲线,验证了最优刀间距理论公式的结论。研究表明：TBM滚刀最优刀间距计算公式综合考虑了岩石特性与滚刀结构特性,适应性较广泛;刀间距超过滚刀协同工作距离时,滚刀破岩以剪切破碎为主;刀间距小于2倍岩石裂纹长度时,张拉破碎的影响更加明显;随着贯入度的增加,最优刀间距逐渐增大,而最优滚刀间距S与贯入度P之比（S/P）值则逐渐减小。     

Influence of Rock Mass Parameters on the Performance of a TBM in a Gneissic Formation (Varzo Tunnel)

Summary The paper analyses the influence of rock mass quality on the performance of a double shield TBM in the excavation of a tunnel in a gneiss formation which is characterized by high strength and low fracture intensity.As full observation of the rock conditions was prevented by the use of segmental lining, a geomechanical survey of the face was performed during maintenance downtime and the observed conditions were correlated with the machine performance parameters for that same day. A statistical analysis of the data shows that penetration rate correlates well with a slightly modified RMR index (in which the influence of the water conditions and joint orientation were discounted), but the most important factor is by far the partial rating of the RMR classification related to joint spacing only. However in tunnels characterized by greater variability in rock strength and joint conditions, it could be worthwhile using the complete RMR index.Given the toughness of the rock, failure of the cutter bearings and supports were a frequent occurrence during excavation. Owing to this factor the influence of rock quality on the rate of advance was found to be weak and the correlation more scattered.The results obtained for the Varzo tunnel were compared with those relative to other tunnels in granitic rocks and found to be in good agreement. However the relationships obtained should be considered valid only for this type of rock; machine behaviour could be found to be markedly different in other rock types, even where rock material strength and joint frequency are the same.     

TBM Performance Analysis in Pyroclastic Rocks: A Case History of Karaj Water Conveyance Tunnel

Karaj Water Conveyance Tunnel (KWCT) is 30-km long and has been designed for transferring 16 m³/s of water from Amir-Kabir dam to northwest of Tehran. Lot No. 1 of this long tunnel, with a length of 16 km, is under construction with a double shield TBM and currently about 8.7 km of the tunnel has been excavated/lined. This paper will offer an overview of the project, concentrating on the TBM operation and will review the results of field performance of the machine. In addition to analysis of the available data including geological and geotechnical information and machine operational parameters, actual penetration and advance rates will be compared to the estimated machine performance using prediction models, such as CSM, NTNU and Q_TBM. Also, results of analysis to correlate TBM performance parameters to rock mass characteristics will be discussed. This involves statistical analysis of the available data to develop new empirical methods. The preliminary results of this study revealed that the available prediction models need some corrections or modifications to produce a more accurate prediction in geological conditions of this particular project.     

Applying Optimized Support Vector Regression Models for Prediction of Tunnel Boring Machine Performance

One of the main factors in the effective application of a tunnel boring machine (TBM) is the ability to accurately estimate the machine performance in order to determine the project costs and schedule. Predicting the TBM performance is a nonlinear and multivariable complex problem. The aim of this study is to predict the performance of TBM using the hybrid of support vector regression (SVR) and the differential evolution algorithm (DE), artificial bee colony algorithm (ABC), and gravitational search algorithm (GSA). The DE, ABC and GSA are combined with the SVR for determining the optimal value of its user defined parameters. The optimization implementation by the DE, ABC and GSA significantly improves the generalization ability of the SVR. The uniaxial compressive strength (UCS), average distance between planes of weakness (DPW), the angle between tunnel axis and the planes of weakness (α), and intact rock brittleness (BI) were considered as the input parameters, while the rate of penetration was the output parameter. The prediction models were applied to the available data given in the literature, and their performance was assessed based on statistical criteria. The results clearly show the superiority of DE when integrated with SVR for optimizing values of its parameters. In addition, the suggested model was compared with the methods previously presented for predicting the TBM penetration rate. The comparative results revealed that the hybrid of DE and SVR yields a robust model which outperforms other models in terms of the higher correlation coefficient and lower mean squared error.     

基于UDEC的隧道掘进机滚刀破岩数值模拟研究

现今全断面隧道掘进机（TBM）施工方法在长大深埋隧道工程中已被广泛采用,对滚刀破岩关键技术的进一步认识具有重要的工程价值。为了研究滚刀破岩机制,分析刀圈断面形态、岩石强度和节理角度对其的影响,运用UDEC方法建立了滚刀贯切岩石的二维数值系列模型,对TBM滚刀破岩过程进行了仿真。分析表明：滚刀破岩是滚刀下岩石拉破坏和剪破坏的综合反映,拉破坏是裂纹萌生与扩展的主要驱动机制;刃宽较大的平刀与刃角较大的楔刀破岩效果较好;平刀与楔刀在软岩中破岩效果相近,平刀在硬岩施工中比楔刀的破岩效果好;滚刀对节理角度为30°～60°的岩石破坏效果较好,由于楔刀的“劈裂”作用,楔刀比平刀更适合用于贯切含有节理的岩石。