Tunnelling performance prediction of cantilever boring machine in sedimentary hard-rock tunnel using deep belief network

Evaluating the adaptability of cantilever boring machine(CBM) through in-depth excavation and analysis of tunnel excavation data and rock mass parameters is the premise of mechanical design and efficient excavation in the field of underground space engineering.This paper presented a case study of tunnelling performance prediction method of CBM in sedimentary hard-rock tunnel of Karst landform type by using tunneling data and surrounding rock parameters.The uniaxial compressive strength(UCS),rock integrity factor(Kv),basic quality index([BQ]),rock quality index RQD,brazilian tensile strength(BTS) and brittleness index(BI) were introduced to construct a performance prediction database based on the hard-rock tunnel of Guiyang Metro Line 1 and Line 3,and then established the performance prediction model of cantilever boring machine.Then the deep belief network(DBN) was introduced into the performance prediction model,and the reliability of performance prediction model was verified by combining with engineering data.The study showed that the influence degree of surrounding rock parameters on the tunneling performance of the cantilever boring machine is UCS > [BQ] > BTS >RQD > Kv > BI.The performance prediction model shows that the instantaneous cutting rate(ICR) has a good correlation with the surrounding rock parameters,and the predicting model accuracy is related to the reliability of construction data.The prediction of limestone and dolomite sections of Line 3 based on the DBN performance prediction model shows that the measured ICR and predicted ICR is consistent and the built performance prediction model is reliable.The research results have theoretical reference significance for the applicability analysis and mechanical selection of cantilever boring machine for hard rock tunnel.

Design Theory of Full Face Rock Tunnel Boring Machine Transition Cutter Edge Angle and Its Application

At present, the inner cutters of a full face rock tunnel boring machine (TBM) and transition cutter edge angles are designed on the basis of indentation test or linear grooving test. The inner and outer edge angles of disc cutters are characterized as symmetric to each other with respect to the cutter edge plane. This design has some practical defects, such as severe eccentric wear and tipping, etc. In this paper, the current design theory of disc cutter edge angle is analyzed, and the characteristics of the rock-breaking movement of disc cutters are studied. The researching results show that the rotational motion of disc cutters with the cutterhead gives rise to the difference between the interactions of inner rock and outer rock with the contact area of disc cutters, with shearing and extrusion on the inner rock and attrition on the outer rock. The wear of disc cutters at the contact area is unbalanced, among which the wear in the largest normal stress area is most apparent. Therefore, a three-dimensional model theory of rock breaking and an edge angle design theory of transition disc cutter are proposed to overcome the flaws of the currently used TBM cutter heads, such as short life span, camber wearing, tipping. And a corresponding equation is established. With reference to a specific construction case, the edge angle of the transition disc cutter has been designed based on the theory. The application of TBM in some practical project proves that the theory has obvious advantages in enhancing disc cutter life, decreasing replacement frequency, and making economic benefits. The proposed research provides a theoretical basis for the design of TBM three-dimensional disc cutters whose rock-breaking operation time can be effectively increased.

Wear Analysis of Disc Cutters of Full Face Rock Tunnel Boring Machine

Wear is a major factor of disc cutters’ failure. No current theory offers a standard for the prediction of disc cutter wear yet. In the field the wear prediction method commonly used is based on the excavation length of tunnel boring machine（TBM） to predict the disc cutter wear and its wear law, considering the location number of each disc cutter on the cutterhead（radius for installation）; in theory, there is a prediction method of using arc wear coefficient. However, the preceding two methods have their own errors, with their accuracy being 40% or so and largely relying on the technicians’ experience. Therefore, radial wear coefficient, axial wear coefficient and trajectory wear coefficient are defined on the basis of the operating characteristics of TBM. With reference to the installation and characteristics of disc cutters, those coefficients are modified according to penetration, which gives rise to the presentation of comprehensive axial wear coefficient, comprehensive radial wear coefficient and comprehensive trajectory wear coefficient. Calculation and determination of wear coefficients are made with consideration of data from a segment of TBM project（excavation length 173 m）. The resulting wear coefficient values, after modification, are adopted to predict the disc cutter wear in the follow-up segment of the TBM project（excavation length of 5621 m）. The prediction results show that the disc cutter wear predicted with comprehensive radial wear coefficient and comprehensive trajectory wear coefficient are not only accurate（accuracy 16.12%） but also highly congruous, whereas there is a larger deviation in the prediction with comprehensive axial wear coefficient（accuracy 41%, which is in agreement with the prediction of disc cutters’ life in the field）. This paper puts forth a new method concerning prediction of life span and wear of TBM disc cutters as well as timing for replacing disc cutters.

Performance characteristics of tunnel boring machine in basalt and pyroclastic rocks of Deccan traps–A case study

A12.24km long tunnel between Maroshi and Ruparel College is being excavated by tunnel boring machine(TBM)to improve the water supply system of Greater Mumbai,India.In this paper,attempt has been made to establish the relationship between various litho-units of Deccan traps,stability of tunnel and TBM performances during the construction of5.83km long tunnel between Maroshi and Vakola.The Maroshi–Vakola tunnel passes under the Mumbai Airport and crosses both runways with an overburden cover of around70m.The tunneling work was carried out without disturbance to the ground.The rock types encountered during excavation arefine compacted basalt,porphyritic basalt,amygdaloidal basalt pyroclastic rocks with layers of red boles and intertrappean beds consisting of various types of shales Relations between rock mass properties,physico-mechanical properties,TBM specifications and the cor responding TBM performance were established.A number of support systems installed in the tunne during excavation were also discussed.The aim of this paper is to establish,with appropriate accuracy the nature of subsurface rock mass condition and to study how it will react to or behave during under ground excavation by TBM.The experiences gained from this project will increase the ability to cope with unexpected ground conditions during tunneling using TBM.

Technical innovation in the “Beishan No. 1” hard rock tunnel boring machine for high-gradient spiral tunnels

1 Project overview The“Beishan No.1”,the world’s first-ever hard rock Tunnel Boring Machine(TBM)tailored for high-gradient spiral tunnels,constitutes a pivotal element within the Beishan Underground Research Laboratory(URL)initiative in China.Beishan URL,the first URL for geological disposal of high level radioactive waste(HLW)in China,is a national key construction project listed in the“13th Five-Year Plan”.In 2019,subsequent to receiving approval from the China Atomic Energy Authority,the Beijing Research Institute of Uranium Geology(BRIUG),serving as the project’s owner,initiated its construction.This underground facility,categorized as a“third generation”URL for HLW disposal,i.e.,area-specific URL,was located in Beishan,Jiuquan City,Gansu Province,China,following more than three decades of rigorous research on site selection.

Theoretical prediction of wear of disc cutters in tunnel boring machine and its application

Predicting the cutter consumption and the exact time to replace the worn-out cutters in tunneling projects constructed with tunnel boring machine(TBM) is always a challenging issue. In this paper, we focus on the analyses of cutter motion in the rock breaking process and trajectory of rock breaking point on the cutter edge in rocks. The analytical expressions of the length of face along which the breaking point moves and the length of spiral trajectory of the maximum penetration point are derived. Through observation of rock breaking process of disc cutters as well as analysis of disc rock interaction, the following concepts are proposed: the arc length theory of predicting wear extent of inner and center cutters, and the spiral theory of predicting wear extent of gage and transition cutters. Data obtained from5621 m-long Qinling tunnel reveal that among 39 disc cutters, the relative errors between cumulatively predicted and measured wear values for nine cutters are larger than 20%, while approximately 76.9% of total cutters have the relative errors less than 20%. The proposed method could offer a new attempt to predict the disc cutter's wear extent and changing time.

Excavation of underground research laboratory ramp in granite using tunnel boring machine: Feasibility study

Underground research laboratory(URL)plays an important role in safe disposal of high-level radioactive waste(HLW).At present,the Xinchang site,located in Gansu Province of China,has been selected as the final site for China’s first URL,named Beishan URL.For this,a preliminary design of the Beishan URL has been proposed,including one spiral ramp,three shafts and two experimental levels.With advantages of fast advancing and limited disturbance to surrounding rock mass,the tunnel boring machine(TBM)method could be one of the excavation methods considered for the URL ramp.This paper introduces the feasibility study on using TBM to excavation of the Beishan URL ramp.The technical challenges for using TBM in Beishan URL are identified on the base of geological condition and specific layout of the spiral ramp.Then,the technical feasibility study on the specific issues,i.e.extremely hard rock mass,high abrasiveness,TBM operation,muck transportation,water drainage and material transportation,is investigated.This study demonstrates that TBM technology is a feasible method for the Beishan URL excavation.The results can also provide a reference for the design and construction of HLW disposal engineering in similar geological conditions.2020 Institute of Rock and Soil Mechanics,Chinese Academy of Sciences.Production and hosting by Elsevier B.V.This is an open access article under the CC BY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/).

Real-time rock mass condition prediction with TBM tunneling big data using a novel rock-machine mutual feedback perception method

Real-time perception of rock mass information is of great importance to efficient tunneling and hazard prevention in tunnel boring machines(TBMs).In this study,a TBM-rock mutual feedback perception method based on data mining(DM) is proposed,which takes 10 tunneling parameters related to surrounding rock conditions as input features.For implementation,first,the database of TBM tunneling parameters was established,in which 10,807 tunneling cycles from the Songhua River water conveyance tunnel were accommodated.Then,the spectral clustering(SC) algorithm based on graph theory was introduced to cluster the TBM tunneling data.According to the clustering results and rock mass boreability index,the rock mass conditions were classified into four classes,and the reasonable distribution intervals of the main tunneling parameters corresponding to each class were presented.Meanwhile,based on the deep neural network(DNN),the real-time prediction model regarding different rock conditions was established.Finally,the rationality and adaptability of the proposed method were validated via analyzing the tunneling specific energy,feature importance,and training dataset size.The proposed TBM-rock mutual feedback perception method enables the automatic identification of rock mass conditions and the dynamic adjustment of tunneling parameters during TBM driving.Furthermore,in terms of the prediction performance,the method can predict the rock mass conditions ahead of the tunnel face in real time more accurately than the traditional machine learning prediction methods.

Laboratory tests to study the influence of rock stress confinement on the performances of TBM discs in tunnels

To clarify some aspects of rock destruction with a disc acting on a high confined tunnel face, a series of tests were carried out to examine fracture mechanisms under an indenter that simulates the tunnel boring machine （TBM） tool action, in the presence of an adjacent groove, when a state of stress （lateral confinement） is imposed on a rock sample. These tests proved the importance of carefully establishing the optimal distance of grooves produced by discs acting on a confined surface, and the value （as a mere order of magnitude） of the increase of the thrust to produce the initiation of chip formation, as long as the confinement pressure becomes greater.

Machine learning-based classification of rock discontinuity trace:SMOTE oversampling integrated with GBT ensemble learning

This paper presents a hybrid ensemble classifier combined synthetic minority oversampling technique(SMOTE),random search(RS)hyper-parameters optimization algorithm and gradient boosting tree(GBT)to achieve efficient and accurate rock trace identification.A thirteen-dimensional database consisting of basic,vector,and discontinuity features is established from image samples.All data points are classified as either‘‘trace”or‘‘non-trace”to divide the ultimate results into candidate trace samples.It is found that the SMOTE technology can effectively improve classification performance by recommending an optimized imbalance ratio of 1:5 to 1:4.Then,sixteen classifiers generated from four basic machine learning(ML)models are applied for performance comparison.The results reveal that the proposed RS-SMOTE-GBT classifier outperforms the other fifteen hybrid ML algorithms for both trace and nontrace classifications.Finally,discussions on feature importance,generalization ability and classification error are conducted for the proposed classifier.The experimental results indicate that more critical features affecting the trace classification are primarily from the discontinuity features.Besides,cleaning up the sedimentary pumice and reducing the area of fractured rock contribute to improving the overall classification performance.The proposed method provides a new alternative approach for the identification of 3D rock trace.

Influence of confining stress on fracture characteristics and cutting efficiency of TBM cutters conducted on soft and hard rock

Combined with numerical simulation, the influence of confining stress on cutting process, fracture conditions and cutting efficiencies of soft and hard rock has been conducted on the triaxial testing machine(TRW-3000) designed and manufactured in Central South University(China). Results are obtained by performing analysis on the fracture scopes of cement and granite plates,the characteristics of cutting force in cutting processes and the cutting efficiency. Firstly, the increase of latitude fracture scope and the decrease of longitude fracture scope are both more notable in the tests conducted on cement plates subjected to the increasing confining stresses; secondly, the increase tendency of peak penetration forces obtained from tests conducted on granite plates is more obvious, however, the increase tendencies of average penetration forces achieved from cement and granite plates are close to each other; thirdly, the cutting efficiency could be improved by increasing the spacing between cutters when the confining stress which acts on soft and hard rock increases in a certain degree, and the cutting efficiency of soft rock is more sensitive to the varying confining stresses.

HSP超前探测技术在煤矿TBM掘进巷道中的应用研究

随着全断面掘进机TBM(Tunnel Boring Machine)逐渐应用于煤矿岩巷掘进,对不良地质构造进行超前准确快速预测的需求日益迫切。通过对主动源地震波超前探测方法的特点和TBM破岩震源超前探测技术的适用性进行分析,结合煤矿巷道地质和生产条件,提出了适用于煤矿巷道TBM掘进的HSP超前探测方法。以河南平顶山首山一矿TBM掘进底板瓦斯治理巷道为工程背景,选用防爆硬件一体化设计的探测仪器在煤矿巷道中进行应用。构建了空间型观测方式对煤矿巷道近水平煤线进行探测,优化了双护盾TBM掘进巷道狭小空间检波器阵列式布置参数;基于时频分析、互相关干涉处理、反射与散射联合反演等方法处理原始信号并进行探测结果成像。研究表明:采用空间型观测方式可实现与巷道小角度斜交煤线的识别,设计震源与首检波器间距离为15 m时最优。通过时频分析提取有效信号,利用互相关干涉法获取虚拟震源道和反射特征曲线,并结合反射与散射联合反演成像得到探测区域地层反射能量分布图,能够较准确地推测得到围岩存在的不良地质构造。通过比较现场开挖揭露情况与探测结果发现两者吻合度较高,表明HSP超前探测方法可实现掘进工作面前方100 m范围内超前无损地质预测,有助于提高煤矿岩巷TBM掘进速度。

基于图像分析的TBM掘进参数与岩碴特征关系研究

岩碴图像分析是隧道掘进机(tunnelboringmechine,TBM)智能掘进中实时破岩效率评价和掘进参数优化的重要手段。为了研究掘进参数与岩碴图像特征的关系,依托青岛地铁6号线创石区间TBM施工段,在一段较完整花岗岩地层中开展了分步推力掘进试验,并通过搭载的岩碴图像分析系统对岩碴图像进行采集和分析。结果表明,岩碴图像的中位粒径d50、最大粒径dmax和粗糙度指数CI与推力、扭矩和贯入度之间均表现出正相关,与现场贯入指数FPI和工程比能SE之间均呈现出良好的负相关。当推力超过破岩临界值后,推力的提升将显著提高岩碴的d50和CI,而只有当推力进一步增大到一定水平后dmax才显著增大。此外,随着推力的提升,大岩片的二维形状逐渐呈现出长条形,其平均长短轴比也将增加,但是推力超过一定水平后,大岩片长短轴将保持不变。上述研究结果表明,岩碴粒径和形状参数均反映出破岩效率,可作为实时TBM掘进参数优化的评价指标。

天山胜利隧道敞开式TBM钢管片支护作用效果研究

针对TBM穿越断层破碎带地层洞壁围岩松动掉块严重的问题,依托乌尉天山胜利隧道,采用数值模拟的方法,通过对比研究传统支护方式与新型钢管片支护方式下围岩变形和围岩塑性区情况,研究钢管片支护的作用效果;同时,为说明不同支护的适用条件,采用现场调研方法开展不同支护方式下施工效率和经济性对比分析。结果表明:1)断层破碎带地层中,当围岩出露护盾后,变形量与塑性区范围增大,围岩破坏程度加剧,以锚杆和钢拱架为主的传统支护方式无法较好地控制围岩变形和塑性区发展。2)断层破碎带地层中,钢管片支护较传统支护的围岩累计沉降值降低53%,围岩变形收敛快,能更好地控制围岩变形和发展。3)钢管片支护较传统支护的围岩塑性区范围小,其中边墙的最终塑性区缩小44%,且钢管片支护可实现早封闭、及时支护,塑性区均匀,更有利于围岩的稳定。4)一般地层中,传统支护方式的经济性和效率更佳;断层破碎带地层中,钢管片支护方式可提供安全作业空间,减小钢拱架+喷锚支护作业量,较传统支护经济性和施工效率更佳。

高压富水硬岩地层双护盾TBM前置式超前注浆堵水技术研究

晋中引黄输水隧洞双护盾TBM施工穿越高压富水裂隙,掌子面高压大流量突涌水严重,采用常规后置式超前注浆技术对掌子面突涌水进行超前处置效果不佳,主要原因是受外插角影响,采用常规后置式超前注浆存在注浆目标区域受限、钻探效率低、超前注浆控制难度大等问题,难以形成有效的止水帷幕结构。对隧洞水文地质条件、突涌水情况及超前注浆技术进行系统研究分析,提出双护盾TBM前置式超前注浆堵水工艺,通过优化注浆设备,在掌子面处实施超前注浆堵水。开展现场注浆试验,对坚硬岩面钻孔施工、注浆材料、注浆参数控制及注浆段长优化等技术进行研究,并根据现场试验信息,不断优化注浆设备及工艺。通过对晋中引黄输水隧洞实施前置式超前注浆堵水技术,洞内平均出水量降至3 702m~3/d,降幅达75.9%,同时在一定程度上提高了TBM施工效率。实践证明该技术方法有效。

基于TBM掘进大数据和特征参数的引水隧洞塌方分析

针对TBM掘进过程中缺乏对围岩质量和塌方风险快捷、精准的预测预警方法,通过对TBM掘进大数据的深入挖掘,结合对实际工程塌方数据的剖析,提出潜在塌方风险的辅助判断依据。首先,对冗杂、连续的原始采集数据进行预处理,获取高质量的分析数据;然后,基于参数的相关性分析提出围岩特征参数的计算方法,并围绕特征参数的合理性和适用性,通过理论推导、室内试验和现场原位掘进试验进行论证;最后,结合实际的TBM塌方案例分析特征参数与围岩地质情况的相关性,提出塌方风险快速判断依据。结果表明:基于TBM掘进数据获取的围岩特征参数在一定程度上反映了围岩质量,其数值与围岩质量正相关,当其数值显著降低、变幅超过69.2%时,当前的掘进循环极大可能存在塌方风险。

TBM窄刃刀与标准刀现场性能对比测试与分析

极硬岩条件下如何进行刀具选型,使TBM掘进速度和刀具消耗取得综合效益,是有待解决的具有争议性的问题。为此,依托新疆YE工程现场TBM实际掘进,在岩石单轴抗压强度为100~150 MPa的完整Ⅱ类凝灰岩条件下,对比测试刀盘主要区域窄刃刀和标准刀的掘进性能表现以及刀具消耗情况,探索降低滚刀刀圈刃宽,提升TBM贯入度和掘进速度的可行性与合理性。结果表明:1)使用窄刃刀破岩对贯入度和施工速度有着较为明显的提升,且随着围岩抗压强度的增加,窄刃刀对掘进速度的提升效果明显;2)与标准刀相比,窄刃刀消耗数量也有较大增加,但2种滚刀的失效形式占比情况大致相同,对TBM作业利用率影响极小;3)经综合成本估算,窄刃刀通过提升施工速度节省的成本远高于刀具消耗增加的成本。

全断面竖井掘进机锥形刀盘破岩机理研究

刀盘刀具系统作为全断面竖井掘进机的关键组成部分,不同刀盘锥度及刀间距对滚刀破岩起决定性的作用。运用ABAQUS软件建立滚刀动态破岩模型,分析不同刀盘锥度和不同刀间距对滚刀破岩的影响,并获取了滚刀在破岩过程中的受力情况及破岩效率。结果表明:滚刀破岩效率随着刀盘锥度的增大而减小,滚刀破岩效率随着滚刀安装半径的增大而减小,综合滚刀受力、破岩效率和实际工况,得到刀盘锥度为120°、滚刀刀间距为40 mm时,滚刀破岩效率最高。为竖井掘进机锥形刀盘设计提供了理论依据,有效提高了竖井掘进机破岩效率和整机研制水平。

典型地层下TBM滚刀刀座系统振动特性实验研究

在全断面硬岩隧道掘进机(tunnel boring machine,TBM)滚刀破岩过程中,强冲击载荷下产生的切削应力通过刀座系统传递至刀盘,引起刀座系统剧烈振动,造成螺栓松动断裂甚至滚刀掉落等严重的工程问题。为此,通过开展破岩实验来研究TBM滚刀刀座系统的振动特性。利用多功能刀具切削性能测试实验台开展TBM滚刀切削红砂岩和花岗岩的实验,并采集滚刀破岩过程中的三向载荷和刀轴振动加速度数据。通过对比分析红砂岩和花岗岩地层下滚刀破岩的载荷—时间历程曲线,得到破岩过程中滚刀刀座系统载荷的动态变化特性,以及不同地层下滚刀刀轴的振动响应特性。研究结果可为TBM滚刀刀座系统的减振设计提供理论依据。

小断面土石组合地质条件下TBM施工围岩可掘性分级识别

围岩可掘性分级以及识别研究对隧道掘进机(TBM)高效率施工及智能化控制意义重大。依托南水北调安阳市西部调水工程TBM施工实际数据,利用掘进性能综合指标单位贯入度推力(FPI)、单位贯入度扭矩(TPI)建立了小断面土石组合地质条件下TBM施工围岩可掘性分级标准;提出了PCA-RF模型对围岩可掘性分级进行识别,并与BP、SVR和RF模型进行了比较讨论。结果表明:①建立的小断面土石组合围岩TBM施工可掘性分级标准是适用的,克服了土石组合围岩下传统围岩分类方法的局限性;②小断面土石组合围岩TBM施工可掘性分级PCA-RF识别模型的识别准确率达到了98.3%,高于BP、SVR和RF模型,可以满足工程施工需要。