岩石隧道掘进机的施工预测模型

分析了岩石隧道掘进机的破岩机理,介绍了自上世纪70年代以来发展的一系列施工预测模型,包括单因素预测模型、综合预测模型(CSM模型和NTNU模型)、岩体分类预测模型(QTBM模型)、概率模型、模糊神经网络模型。单因素预测模型中包括的主要岩石材料参数有岩石单轴抗压强度、抗拉强度及岩石的总硬度;CSM模型主要是基于线性切割试验机岩石试验数据,其初始预测模型中包括岩石单轴抗压强度及抗拉强度;NTNU模型是一套完整的预测模型,包括掘进速度、进度预测、刀具的磨损预测及经济分析,在它的施工进度预测模型中,考虑到了岩石的可钻性、孔隙度及岩体节理的密度及方向;QTBM模型源自于Q系统,加入了一些与隧道掘进机及与掘进速度相关的参数;概率模型是基于一个庞大数据库的类比模拟模型;模糊神经网络模型是一种黑箱模型,克服了输入与输出之间的不确定性关系。     

Utilizing rock mass properties for predicting TBM performance in hard rock condition

The key parameters on the estimation of tunnel-boring machine (TBM) performance are rock strength, toughness, discontinuity in rock mass, type of TBM and its specifications. The aim of this study is to both assess the influence of rock mass properties on TBM performance and construct a new empirical equation for estimation of the TBM performance. To achieve this aim, the database composed of actual measured TBM penetration rate and rock properties (i.e., uniaxial compressive strength, Brazilian tensile strength, rock brittleness/toughness, distance between planes of weakness, and orientation of discontinuities in rock mass) were established using the data collected from one hard rock TBM tunnel (the Queens Water Tunnel # 3, Stage 2) about 7.5 km long, New York City, USA. Intact rock properties were obtained from laboratory studies conducted at the Earth Mechanics Institute (EMI) in the Colorado School of Mines, CO, USA. Based on generated database, the statistical analyses were performed between available rock properties and measured TBM data in the field. The result revealed that rock mass properties have strong affect on TBM performance. It is concluded that TBM performance could be estimated as a function of rock properties utilizing new equation (r = 0.82).     

Analysis and prediction of TBM performance in blocky rock conditions at the Lötschberg Base Tunnel

This paper focuses on the analysis of the TBM performance recorded during the excavation of the Lötschberg Base Tunnel. The southern part of the tunnel was excavated by two gripper TBMs, partly through blocky rock masses at great depth. The jointed nature of the blocky rock mass posed serious problems concerning the stability of the excavation face. A detailed analysis has been carried out to obtain a relationship between the rock mass conditions and the TBM performance, using the Field Penetration Index (FPI). In blocky rock conditions, the FPI is defined as the ratio between the applied thrust force and the actual penetration rate. A database of the TBM parameters and the geological/geotechnical conditions for 160 sections along the tunnel has been established. The analysis reveals a relationship between the FPI and two rock mass parameters: the volumetric joint count (J_v) and the intact rock uniaxial compressive strength (UCS). Through a multivariate regression analysis, a prediction model for FPI in blocky rock conditions (FPI_blocky) is then introduced. Finally, other TBM performance parameters such as the penetration rate, the net advance rate and the total advance rate are evaluated using FPI_blocky.     

Influence of rock brittleness on TBM penetration rate in Singapore granite

Brittleness is one of the most important rock properties, which affects the rock fragmentation process induced by TBM cutters, and then the TBM penetration rate. This paper presents the different measurements of rock brittleness. The ratio of uniaxial compressive strength to Brazilian tensile strength was adopted to quantify the rock brittleness. By the laboratory tests, the brittleness indices of more than 100 samples cored in Bukit Timah granite along the tunnel alignments of T05 and T06 tunnels of DTSS in Singapore were obtained. The brittleness index varies in a large range from less than 10 to more than 25. The tendency shows that the brittleness index decreases with the increase of the weathering grade of granite. A series of models were then set up to simulate the effect of rock brittleness on rock fragmentation process using UDEC. With the decrease of the brittleness index, the crushed zone decreases and the number and length of the main cracks outside the crushed zone also decrease. It is obvious that with the increase of the rock brittleness index the cutter indentation process gets easier. Through the statistical analysis of correlation between rock mass properties and the corresponding TBM performance in tunnel projects, it was noted that TBM penetration rate increases with increasing rock brittleness, which is consistency with the numerical simulation results.     

In situ TBM penetration tests and rock mass boreability analysis in hard rock tunnels

Boreability is popularly adopted to express the ease or difficulty with which a rock mass can be penetrated by a tunnel boring machine. Because the boreability is related to the rock mass properties, TBM specifications and TBM operation parameters, an accurately definable quantity has not been obtained so far. In order to analyze and compare rock mass boreability, a series of TBM shield friction tests were conducted in a TBM tunneling site. Two sets of TBM penetration tests were performed in different rock mass conditions during tunneling in rock. In each step of the penetration test, the rock muck was collected to perform the muck sieve analyses and the shape of large chips was surveyed in order to analyze the TBM chipping efficiency under different cutter thrusts. The results showed that a critical point exists in the penetration curves. The penetration per revolution increases rapidly with increasing thrust per cutter when it is higher than the critical value. The muck sieve analysis results verified that with increasing thrust force, the muck size increases and the rock breakage efficiency also increases. When the thrust is greater than the critical value, the muck becomes well-graded. The muck shape analysis results also showed with the increase of the thrust, the chip shape changes from flat to elongated and flat. The boreability index at the critical point of penetration of 1 mm/rev. defined as the specific rock mass boreability index is proposed to evaluate rock mass boreability.     

TBM滚刀破岩动态特性与最优刀间距研究

在对实际工况合理简化的基础上,从岩土细观角度出发,采用颗粒离散元法建立滚刀侵入岩体的二维模拟模型,研究双滚刀作用下岩体的动态响应机制,找出滚刀侵入过程中岩体裂纹、贯入度以及切削力三者的关系。在此基础上,通过数值模拟对常见切深下滚刀最优刀间距问题进行分析,得到不同切深下比能耗与刀间距的规律,并通过试验对双滚刀破岩过程中岩体动态特性以及最优刀间距问题进行验证,最后以工程实例验证研究结论。研究表明：仿真过程中,切削力随贯入度的变化与岩体的跃进破碎特性相一致,岩体破坏服从格里菲斯理论;较小切深下岩体为剪切破坏,较大切深下岩体发生拉应力破坏;切深为10 mm时比能耗有明显拐点,此时刀间距为100 mm;切深为6 mm时,60 mm刀间距下比能耗最小;切深小于2 mm时,实际工况下岩体不能产生贯穿裂纹。     

不同层厚层状岩体对TBM开挖的影响

 TBM的开挖效果在很大程度上受到节理间距的影响,TBM掘进速度随节理间距变小而增大,但节理间距过小,会造成掌子面岩体不稳,不利于TBM开挖。锦屏II级水电站引水隧洞洞段主要以层状大理岩为主,沿洞轴线方向大理岩层层厚变化较大,从几厘米到几米不等,层面是岩体中主要的不连续面,且层面与隧道轴线大角度相交。TBM的破岩过程主要受到高地应力条件和岩体层厚的影响。从TBM破岩机制角度,分析在高地应力条件下TBM在薄层面、中薄层面和厚层面大理岩层状岩体中的开挖表现,研究岩层厚度对TBM开挖的影响。     

Predicting penetration rate of hard rock tunnel boring machine using fuzzy logic

Predicting the penetration rate of a tunnel boring machine (TBM) plays an important role in the economic and time planning of tunneling projects. In the past years, various empirical methods have been developed for the prediction of TBM penetration rates using traditional statistical analysis techniques. Soft computing techniques are now being used as an alternative statistical tool. In this study, a fuzzy logic model was developed to predict the penetration rate based on collected data from one hard rock TBM tunnel (the Queens Water Tunnel # 3, Stage 2) in New York City, USA. The model predicts the penetration rate of the TBM using rock properties such as uniaxial compressive strength, rock brittleness, distance between planes of weakness and the orientation of discontinuities in the rock mass. The results indicated that the fuzzy model can be used as a reliable predictor of TBM penetration rate for the studied tunneling project. The determination coefficient (R ²), the variance account for and the root mean square error indices of the proposed fuzzy model are 0.8930, 89.06 and 0.13, respectively.     

Multifactorial fuzzy approach to the penetrability classification of TBM in hard rock conditions

Rate of penetration of a tunnel boring machine in a hard rock environment is generally a key parameter which expresses the ease or difficulty with which the rock mass can be excavated. In this paper, the penetrability of TBM in hard rock conditions was investigated with the developed fuzzy classification system. TBM penetration rate and rock properties (such as Uniaxial Compressive Strength (UCS), Brazilian Tensile Strength (BTS), rock brittleness/toughness, Average Distance between Planes of Weakness (DPW) and orientation of discontinuities in rock mass) were evaluated by using the multifactorial fuzzy approach which is a special case of multiple objective multifactorial decision making for the penetrability classification of TBM in hard rock conditions. Using the decision function, the penetrating performance of TBM was classified into three categories; Good, Medium and Poor. Eventually, it is possible to evaluate the penetrability and determine the advance rate for new conditions by carrying out the proposed rock properties tests and using the developed fuzzy classification system.     

Study on rock mass boreability by TBM penetration test under different in situ stress conditions

Rock mass boreability is a comprehensive parameter reflecting the interaction between rock mass and a tunnel boring machine (TBM). Many factors including rock mass conditions, TBM specifications and operation parameters influence rock mass boreability. In situ stress, as one of the important properties of rock mass conditions, has not been studied specifically for rock mass boreability in TBM tunneling. In this study, three sets of TBM penetration tests are conducted with different in situ stress conditions in three TBM tunnels of the Jinping II Hydropower Station. The correlation between TBM operation parameters collected during the tests and the rock mass boreability index is analyzed to reveal the influence of in situ stress on rock mass boreability and TBM excavation process. The muck produced by each test step is collected and analyzed by the muck sieve test. The results show that in situ stress not only influences the rock mass boreability but also the rock fragmentation process under TBM cutters. If the in situ stress is high enough to cause the stress-induced failure at the tunnel face, it facilitates rock fragmentation by TBM cutters and the corresponding rock boreability index decreases. Otherwise, the in situ stress restrains rock fragmentation by TBM cutters and the rock mass boreablity index increases. Through comparison of the boreability index predicted by the Rock Mass Characteristics (RMC) prediction model with the boreability index calculated from the penetration test results, the influence degree of different in situ stresses for rock mass boreability is obtained.     

Numerical modelling of the effects of joint spacing on rock fragmentation by TBM cutters

The influence of joint spacing on tunnel boring machine (TBM) penetration performance has been extensively observed at TBM site. However, the mechanism of rock mass fragmentation as function of the joint spacing has been scarcely studied. In this study, the rock indentation by a single TBM cutter is simulated by using the discrete element method (DEM), and the rock fragmentation process is highlighted. A series of two-dimensional numerical modelling with different joint spacing in a rock mass have been performed to explore the effect of joint spacing on rock fragmentation by a TBM cutter. Results show that the joint spacing can significantly influence the crack initiation and propagation, as well as the fragmentation pattern, and can hence affect the penetration rate of the TBM. Two crack initiation and propagation modes are found to fragment the rock mass due to the variation of joint spacing. The simulation results are analyzed and compared with in situ measurements.     

Influence of rock mass fracturing on the net penetration rates of hard rock TBMs

Penetration rates during excavation using hard rock tunnel boring machines (TBMs) are significantly influenced by the degree of fracturing of the rock mass. In the NTNU prediction model for hard rock TBM performance and costs, the rock mass fracturing factor (k_s) is used to include the influence of rock mass fractures. The rock mass fracturing factor depends on the degree of fracturing, fracture type, fracture spacing, and the angle between fracture systems and the tunnel axis. In order to validate the relationship between the degree of fracturing and the net penetration rate of hard rock TBMs, field work has been carried out, consisting of geological back-mapping and analysis of performance data from a TBM tunnel. The rock mass influence on hard rock TBM performance prediction is taken into account in the NTNU model. Different correlations between net penetration rate and the fracturing factor (k_s) have been identified for a variety of k_s values.     

TBM performance estimation using rock mass classifications

Three tunnels for hydraulic purposes were excavated by tunnel-boring machines (TBM) in mostly hard metamorphic rocks in Northern Italy. A total of 14 km of tunnel was surveyed almost continually, yielding over 700 sets of data featuring rock mass characteristics and TBM performance. The empirical relations between rock mass rating and penetration rate clearly show that TBM performance reaches a maximum in the rock mass rating (RMR) range 40–70 while slower penetration is experienced in both too bad and too good rock masses. However, as different rocks gives different penetrations for the same RMR, the use of Bieniawski's classification for predictive purpose is only possible provided one uses a normalized RMR index with reference to the basic factors affecting TBM tunneling. Comparison of actual penetrations with those predicted by the Innaurato and Barton models shows poor agreement, thus highlighting the difficulties involved in TBM performance prediction.     

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.     

高地应力作用下大理岩岩体的TBM掘进试验研究

滚刀破岩效率的研究主要集中在室内线性试验机破岩试验和数值分析2个方面,在工地开展TBM掘进试验尚不普遍。锦屏二级水电站采用3台TBM开挖隧道群,3台TBM在不同洞深(不同地应力)条件对大理岩岩体进行TBM掘进试验、岩石渣片筛分试验及大渣片统计分析,研究岩体条件、TBM机器参数、TBM运行参数对TBM掘进速度的影响及高地应力作用下岩体可掘性指数的变化。研究结果表明:在高地应力条件下,尽管TBM掘进速度随推力增加而增大,但推力超过一定值后,TBM并不在优化状态下运行,TBM的运行需与岩体条件及地应力条件相匹配。     

Realtime prediction of hard rock TBM advance rate using temporal convolutional network (TCN) with tunnel construction big data

Real-time dynamic adjustment of the tunnel bore machine (TBM) advance rate according to the rock-machine interaction parameters is of great significance to the adaptability of TBM and its efficiency in construction. This paper proposes a real-time predictive model of TBM advance rate using the temporal convolutional network (TCN), based on TBM construction big data. The prediction model was built using an experimental database, containing 235 data sets, established from the construction data from the Jilin Water-Diversion Tunnel Project in China. The TBM operating parameters, including total thrust, cutterhead rotation, cutterhead torque and penetration rate, are selected as the input parameters of the model. The TCN model is found outperforming the recurrent neural network (RNN) and long short-term memory (LSTM) model in predicting the TBM advance rate with much smaller values of mean absolute percentage error than the latter two. The penetration rate and cutterhead torque of the current moment have significant influence on the TBM advance rate of the next moment. On the contrary, the influence of the cutterhead rotation and total thrust is moderate. The work provides a new concept of real-time prediction of the TBM performance for highly efficient tunnel construction.     

Comparison and discussion on fragmentation behavior of soft rock in multi-indentation tests by a single TBM disc cutter

This paper is to investigate the mechanical responses and failure characteristics of soft rock in multi-indentation tests by a single TBM constant cross section (CCS) disc cutter. Different pre-set penetration depths and totally three cycles of indentation processes were employed in the repeated indentation tests conducted on the cubic cement mortar specimens. The load-penetration depth curve, penetration load, peak-load penetration depth, rock breakage work and compacted zone depth for the three indentation processes were analyzed. The strength and deformation properties and failure behavior of soft rock under different indentation conditions were revealed. The rock breakage behavior after several indentation processes still presents brittle failure characteristic with small pre-set penetration depths, but the specimens with large pre-set penetration depths appear obvious plastic failure mode. Approximately equal leap loads are obtained from both the intact specimen in direct indentation failure test and the weakened specimens after several indentation processes with different pre-set penetration depths, but the peak-load penetration depths for specimens with different pre-set penetration depths are varying. Curves of the cumulative penetration depth and cumulative rock breakage work both reach the corresponding peak values for one certain pre-set penetration depth. Along with this most unfavourable pre-set penetration depth, rock breakage efficiency is the lowest and energy consumption is the highest.     

Study on the influence of joint spacing on rock fragmentation under TBM cutter by linear cutting test

Joint spacing is one of the most important geological factors influencing rock fragmentation by TBM cutters and TBM performance. In order to study the influence of joint spacing, full-scale linear cutting tests have been conducted for the Beishan granite samples with different joint spacing (i.e. one intact sample, two jointed samples with joint spacing of 100 mm and 400 mm). For different joint spacing, the influence of penetration depth on rock fragmentation was also explored by varying the penetration depth with an interval of 0.5 mm. During the test process, the three directional forces acting on the TBM cutter were recorded, and the rock chips formed by each cutting pass were weighed, respectively. By analysing the cutting force, crack initiation/propagation and rock chips, the influences of joint spacing on rock fragmentation process by TBM cutter were investigated. The test results showed that the increase of penetration depth cannot improve the TBM breakage efficiency after reaching a certain value for the intact rock sample, and the normal force for intruding the intact rock is larger than that for intruding the rock jointed samples. It is also found that the sample part below the joint plane is intact, thus joint can restrain the crack propagating cross the joint plane and facilitates the chips formation on the cutting surface. For the rock sample with joint spacing of 100 mm, two rock fragmentation modes were found during the cutting process. One mode is that the cracks initiate from the crushed zone under TBM cutter, and the cracks propagate to the joint plane, consequently form large rock chips. The other one is that the cracks initiate from the joint plane and then propagate to the rock cutting surface, and the cracks initiate before the formation of the crushed zone under the cutter. For the rock sample with joint spacing of 400 mm, there are two rock fragmentation stages, i.e., the normal rock fragmentation stage and the joint-controlled rock fragmentation stage. There is a transitional process between these two stages, and also the median crack can be promoted to propagate vertically to joint plane due to the joint existence. This study can provide useful guidance for operation optimization and performance prediction for TBM operating in jointed rock masses.     

Correlation of tunnel convergence with TBM operational parameters and chip size in the Ghomroud tunnel, Iran

Evaluating the impact of rock mass properties on a tunneling operation is crucial, especially when using a tunnel boring machine (TBM). It is an integral part of machine selection and performance prediction in the design and bidding stage. Monitoring and analysis of ground conditions during the construction is also essential to allow the operator to take precautionary measures in adverse geological conditions. This involves adjusting TBM operational parameters such as machine thrust and penetration to avoid potential problems caused by face collapse or excessive convergence and subsequent machine seizure that can cause long delays. Tunnel wall convergence is a function of rock mass characteristics, in situ stresses, size of excavation, and rate of penetration (ROP). It is one of the main factors in determining the use of shielded machines in deep rock tunnel projects. The case study of the Ghomroud water conveyance tunnel project, under construction by a double shield TBM, is used to examine the effect of rock mass parameters on tunnel convergence and hence on the need for over excavation and shield lubrication to avoid problems such as shield seizure. Results of a preliminary analysis of field observations show that the amount of the tunnel convergence can have a direct relationship with the percentage of powder and large rock fragments in the muck. In addition, tunnel convergence has shown a strong relationship with the TBM thrust/torque and rate of penetration (ROP). These relationships have been examined and the results of the analysis as well as the resulting formulas will be explained in this paper.