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.     

Experimental and analytical studies of the parameters influencing the action of TBM disc tools in tunnelling

The use of tunnel boring machines (TBMs) is increasingly popular in tunnelling. One of the most important aspects in the use of these machines is to assess with certain accuracy the effectiveness of the action of the discs on the cutter-head in the different rock types to be excavated. A specific machine, called an intermediate linear cutting machine (ILCM), has been developed at the Politecnico di Torino in order to study, on a reduced scale in detail in the laboratory, the interaction between the discs of the TBM and the rock: this machine allows a series of grooves to be cut on a rock sample of 0.5 × 0.3 × 0.2 m, through the rolling of a 6.5-in. disc, and evaluation, during testing, of the parameters associated with the action of the cutting tool. The parameters measured during the tests were compared with the results obtained employing two analytical methods widely used for predicting the performance of TBMs: the Colorado School of Mines (CSM) model and the Norwegian University of Science and Technology (NTNU) model. The latter showed a greater ability to reproduce tests conducted using the ILCM. However, as with the CSM model, it does not allow the optimal excavation condition (the ratio, which minimizes the specific energy of excavation, between the groove spacing and the penetration of the disc), necessary for the correct design of the TBM cutter-head, to be identified. An example, based on a real case of a tunnel in Northern Italy, allowed a demonstration of how the NTNU model provides results in line with the measurements taken during the excavation and represents, therefore, a model that is able to reliably simulate both laboratory tests and the action of a TBM on site. The NTNU model, together with the results of the tests with ILCM targeted on the identification of the optimal conditions of excavation, may allow the correct dimensioning of the TBM cutter-head to be attained in order to effectively implement the excavation.     

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.     

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。（...     

复合地层隧道围岩强度实时估算研究

隧道TBM开挖过程中经常会遇到复合岩层,在这种地质环境下,隧道掘进机（tunnel boring machine,简称TBM）开挖过程中的隧道围岩强度很难估计,隧道开挖掌子面和围岩容易发生坍塌。为了提高隧道掘进效率、预防事故发生,对开挖隧道围岩强度进行实时估算方面的研究很有必要。在重庆轨道九号线隧道TBM施工中,通过室内试验和现场实测数据发现,TBM推力F_N与岩石强度成正比、TBM扭矩推力比T/F_N（T为扭矩）与贯入度p^0.5成正比例关系。针对砂质泥岩、砂岩和灰岩组成的复合岩层,提出了一种利用现场实测推力F_N和扭矩T的值来快速估算开挖隧道围岩强度的方法,进一步对TBM实测数据进行线性拟合,从而得到估算公式中两个常数α₁、α₂的取值方法,并在10多个隧道实际工程中得到验证。结果表明,对于这种复合岩层地质环境,两个常数α₁、α₂的值与滚刀数量n和滚刀直径d相关。该研究成果为实时快速估算开挖隧道围岩强度提供了一种新的切实可行的思路,能提高隧道TBM施工的可靠性和安全性,具有重要的应用价值。     

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。     

Applications of NTNU/SINTEF Drillability Indices in Hard Rock Tunneling

Drillability indices, i.e., the Drilling Rate Index? (DRI), Bit Wear Index? (BWI), Cutter Life Index? (CLI), and Vickers Hardness Number Rock (VHNR), are indirect measures of rock drillability. These indices are recognized as providing practical characterization of rock properties used in the Norwegian University of Science and Technology (NTNU) time and cost prediction models available for hard rock tunneling and surface excavation. The tests form the foundation of various hard rock equipment capacity and performance prediction methods. In this paper, application of the tests for tunnel boring machine (TBM) and drill and blast (D&B) tunneling is investigated and the impact of the indices on excavation time and costs is presented.     

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.     

Analysis of support requirements for a shallow diversion tunnel at Guledar dam site, Turkey

Engineering geological properties and support design of a planned diversion tunnel at Guledar dam site, which was located at the North of Ankara, Turkey were studied in this article. The main purpose of the construction of the planned tunnel is to regulate, drainage and to provide water for irrigation purposes. The diversion tunnel runs mainly through formations of limestone, sandstone and diabase. Rock masses at the site were characterized using Rock Mass Rating (RMR), Rock Mass Quality (Q), Rock Mass Index (RMi) and Geological Strength Index (GSI). RMR, Q, RMi and GSI were determined by using field data and mechanical properties of intact rock samples, measured in the laboratory. Support requirements for the planned diversion tunnel were determined accordingly in terms of the rock mass classification systems. Recommended support systems by empirical methods were also analyzed using 2D Finite Element method. Calculated parameters based on empirical methods were used as input parameters in the finite element models. The results from both methods were compared with each other. This comparison suggests that more reliable support design could be achieved by using the finite element method together with the empirical methods.     

Prediction of TBM Penetration Rate Using Fuzzy Logic,Particle Swarm Optimization and Harmony Search Algorithm

Geotechnical and Geological Engineering - Tunnel Boring Machine (TBM) penetration rate prediction is one of the most important problem in tunneling projects. Estimating of Tunnel Boring Machine...     

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.

     

Prediction of Safe Charge to Protect Surrounding Structures Using Support Vector Machine

The present paper mainly with deals the prediction of safe explosive charge used per delay (Q_MAX) using support vector machine (SVM) incorporating peak particle velocity (PPV) and distance between blast face to monitoring point (D). 150 blast vibration data sets were monitored at different vulnerable and strategic locations in and around a major coal producing opencast coal mines in India. 120 blast vibrations records were used for the training of the SVM model vis-à-vis to determine site constants of various conventional vibration predictors. Rest 30 new randomly selected data sets were used to compare the SVM prediction results with widely used conventional predictors. Results were compared based on coefficient of correlation (R) between measured and predicted values of safe charge of explosive used per delay (Q_MAX). It was found that coefficient of correlation between measured and predicted Q_MAX by SVM was 0.997, whereas it was ranging from 0.063 to 0.872 by different conventional predictor equations.     

The Derivation and Validation of TBM Disc Cutter Wear Prediction Model

The problem of disc cutter wear is inevitable when shield or TBM excavating hard rock for a long distance, thus, the study of disc cutter wear model has an important project value on predicting its service life and replacement opportunity. It is put forward by analyzing disc cutter wear mechanism that the main wear form is abrasive wear, which is based on plastic removal mechanism. Then, disc cutter wear rate and linear wear rate prediction models are obtained by approximate calculation and mathematical deduction, which are based on Rabinowicz equation and CSM model. At last, the two models are verified through field test data from three projects, and the results show that the prediction model can accurately reflect the real wear situation of disc cutter.     

陕西延安Q_2原状黄土抗拉强度试验研究

对陕西延安新宝塔山隧道Q2原状黄土进行了不同加载速率的无侧限抗压与贯入抗拉试验,研究了Q2原状黄土抗压与抗拉强度的影响因素。结果表明:加载速率对宝塔山Q2原状黄土抗压和抗拉强度影响较大,抗压强度与抗拉强度随加载速率增大而增大;高径比对抗拉强度也有较大影响,试验时当高径比控制在1.0左右时,高径比对宝塔山Q2原状黄土的抗拉强度影响相对较小,因此采用轴向压裂法测量黄土的抗拉强度时,高径比宜控制在1.0;在试验加载速率范围内,加载速率对宝塔山Q2原状黄土的压拉比影响不大,其压拉比在9.88~13.68范围内变化。     

Statistical Evaluation of CPT and CPTu Based Methods for Prediction of Axial Bearing Capacity of Piles

Piles are structural members made of steel, concrete, or wood installed into the ground to transfer superstructure loads to the soil. Nowadays, many structures are built on poor lands, and therefore piles have crucial roles in such structures. Performing in-situ tests such as cone penetration (CPT) and piezocone penetration tests (CPTu) have always been of great importance in designing piles. These tests have a brilliant consistency with reality, and as a result, the outcome data can be used in order to achieve reliable pile designing models and reduce uncertainty in this regard. In this paper, the capability of various CPT and CPTu based methods developed from 1961 to 2016 has been investigated using four statistical methods. Such CPT and CPTu based methods are adopted for direct prediction of axial bearing capacity of piles using CPT and CPTu field data. For this purpose, 61 sets of field data prepared from CPT and CPTu have been collected. The data sets were utilized in order to calculate the axial bearing capacity of piles (Q_E) through 25 different methods. In addition, the measured axial pile capacities (Q_M) have been collected, recorded and prepared from field static load tests, respectively. Then, four different statistical approaches have been applied to assess the accuracy of these methods. Finally, the most reliable and accurate methods are presented.

     

TBM滚刀破岩过程影响因素数值模拟研究

全断面岩石掘进机（TBM）的破岩效率主要受刀盘设计和岩体特征的影响。采用颗粒流方法建立了岩石试件与滚刀的数值模型,对TBM滚刀破岩过程的影响因素进行了分析。研究表明,单刃滚刀交替作用下强度较低的岩石中易形成规则的张拉裂纹而生成较大岩碴;强度较高的岩石中滚刀的侧向挤压促使形成块度较小的片状岩碴;双刃滚刀作用下岩石表面受到强烈挤压后出现较大的拉应力,使岩石更易破碎,且仅在强度较高的岩石中才易形成透镜状岩碴。滚刀破岩过程中存在能耗最小的最佳间距,该最佳间距随着岩石强度的增大而减小。滚刀破岩过程中,结构面对裂纹扩展具有显著的控制性作用,并阻隔损伤向结构面下的岩石中渗透;随着结构面与滚刀侵入方向夹角的减小,结构面将引导裂纹向岩石深部扩展,而当夹角较大时,结构面则会引导裂纹横向扩展,易导致大块岩碴的形成     

Assessment of direct CPT and CPTU methods for predicting the ultimate bearing capacity of single piles

Twelve methods to determine axial pile capacity directly based on cone penetration test (CPT) and piezocone penetration test (CPTU) data are presented, compared and evaluated. Analyses and evaluation were conducted on three types of piles of different size and length. All the tested piles have failed at the end of static load test. Both the CPT methods and the CPTU methods were used to estimate the load bearing capacities of the investigated piles (Q_p). The static load test was performed to determine the measured load bearing capacities (Q_m). The pile capacities determined through different methods were compared with the measured values obtained from the static load tests. Two criteria were selected as bases of evaluation: the best fit line for Q_p versus Q_m and the arithmetic mean and standard deviation for the ratio Q_p/Q_m. Results of the analyses showed that the best methods for determining pile capacity are the two CPTU methods. Furthermore, the CPTU method is simple, easy to apply, and not influenced by the subjective judgements of operating staff. Therefore, it is quite suitable for the application in pile engineering practice.     

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.     

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。     

全断面隧道掘进机护盾受力监测及卡机预警

全断面隧道掘进机(简称TBM)在穿越深部软弱地层时围岩收敛变形较大,围岩容易挤压护盾,导致TBM卡机,影响TBM正常掘进。通过分析TBM卡机灾害孕育过程,得到了预测TBM卡机的重要条件：一是围岩变形量大于预留的空间,二是额定推力不能克服摩擦阻力。为了监测实际工程TBM卡机状态,提出了一种监测护盾变形的方案以及护盾受力的计算方法,可通过监测得到的变形估算护盾的受力,进而计算出护盾受到的摩擦阻力,得到TBM卡机的状态。根据TBM受到的摩擦阻力、TBM正常掘进时所需推力和TBM额定推力之间的关系,将TBM卡机状态分为4个等级,即无卡机、轻微卡机、卡机和严重卡机,并提出了对应的处理措施。结合TBM卡机条件以及护盾受力监测方案,提出了TBM卡机灾害预警流程。在兰州水源地输水隧洞工程中应用了该监测方案和卡机灾害预警流程,应用结果表明,预测的卡机状态与TBM实际状态基本一致,说明该方法具有一定的可靠性,对指导TBM隧道施工具有重要意义。