Tunnel Geometry Research Articles

Assessing the tunnel stability in brittle rocks based on strain bursting assessment

Strain bursting is a phenomenon associated with deep underground excavations and tunnelling in brittle hard rocks that result in a sudden and violent failure, posing high risks and damage. This work aims to assess the strain bursting and the energy response characteristics and develop a guideline that can be utilized in the preliminary investigation stage. The obtained results are intended to enable predicting different brittle behaviours in deep geological environments. Elastic stress analysis using the DISL approach based on boundary element method is established (EX3-software) for the assessment of two tunnel geometries (circular, horseshoe) in granitic rock mass. Two different stress states are modelled to simulate the potential stress regime. The analysis’ results demonstrate that different geometries affect the energy storage capacity and result in different behaviour regarding the bursting potential of the rock mass.

Wave Propagation Modeling Techniques in Tunnel Environments: A Survey

The prediction of radio signal transmission in tunnels is important for wireless communication link design as it enables the delivery of optimum power to the intended receiver inside the tunnel. Several techniques have been proposed to estimate path loss for wireless communication inside tunnels. The radio coverage range and where base stations need to be installed can be figured out with the help of propagation models. At the time of developing these models, modeling complexity and environmental attributes, such as the tunnel geometry and the electrical and magnetic properties of its walls and interior materials are considered. A limited amount of literature currently overviews how waves transmits through tunnels and how electromagnetic wave transmission has recently changed. This survey, which examines current advancements in the propagation of waves in tunnels, aims to address this gap. In this review, thirty wave propagation models were analyzed and grouped into distinct categories for the first time. The detailed specifications of each model were omitted to make the survey easy to comprehend. This comparative research will help service providers adopt an appropriate propagation model and plan efficient transmitter and receiver placement and link management for a specific tunnel environment.

Simulation Analysis of CO Concentration Distribution in Beijing Yuntong Tunnel

In this paper, the concentration distribution of CO emitted by motor vehicles in Beijing Yuntong Tunnel is simulated and analyzed based on Fluent numerical simulation software. Firstly, the physical model of tunnel geometry is established. Secondly, the suitable control equations and boundary conditions are selected to describe the diffusion distribution of pollutants in the tunnel. At the same time, the reliability of the model is verified according to the measured data, and the distribution law of CO concentration in the tunnel is observed through the simulation results. The tunnel is unorganized at the entrance of the tunnel. In the simulation results, the CO concentration at the entrance of the tunnel is far more than the CO unorganized emission limit in Beijing. The CO emission of the tunnel should be purified to prevent pollution of the urban environment.

Computing Aspects of Simulation Based on Conservation Laws Conducted on HPC Cluster

The large amount of computing resources required for the simulation of complex natural processes demands a thorough analysis of the efficiency of the calculations and the conditions that influence it. This study investigates computing aspects of fire simulation conducted on a compute cluster. Current fire simulators based on principles of computational fluid dynamics are capable to realistically model majority of complex phenomena related to fire. Fire simulations are highly computationally demanding itself, however, they often lead to extensive parametrical studies requiring high performance computing systems. Smoke stratification and visibility during fire in a road tunnel with two emergency lay-bys are investigated by parametrical study comprising of 24 fire scenarios with the tunnel geometry modifications and various heat release rates and fire locations. Main tendencies of smoke spread in the downstream lay-by are identified and their mutual interactions are analysed. The simulation efficiency of particular simulations is analysed and the reasons of their varied elapsed times are investigated. The analysis indicates that the main reason of this variability are different jet fans velocities influenced by simulation scenario settings.

Investigation of the Effect of Tunnel Geometry on Deformations in Shallow and Stratified Rock Formation

Tünel içindeki deformasyonlar, üst yapıdan gelen sürşarj yükü, aşırı yükleme, kayaç veya zemin biriminde oluşan içsel gerilmeler ile diğer faktörlerin bir sonucu olarak ortaya çıkar. Tünel içi deformasyon ölçümü, tüneldeki plastik şekil değiştirmenin büyüklüğünü belirleyebilmek için önemlidir ve tünel güvenliğinin izlenmesinde önemli bir safhayı oluşturur. Bu çalışmada, dört tabakalı bir kaya formasyonunda ve yeraltı suyu etkisinde bulunan, at nalı veya yumurta şeklinde tasarlanan, NATM (Yeni Avusturya Tünel Açma Metodu) tekniği ile kademeli olarak açılacak olan tünellerin üç boyutlu ve doğrusal olmayan davranışları sonlu elemanlar yöntemi ile analiz edilmiştir. Kazı adımlarına göre farklı yükleme koşullarına maruz kalan taç ve tünel çevresinde meydana gelen kalıcı deformasyonlar ayrıntılı olarak incelenmiştir. Ayrıca her iki tünel geometrisinde, bütün kazı aşamalarında tünelin kritik kesitleri boyunca oluşacak olan kalıcı şekil değiştirmeler, deformasyon eğrileri sayesinde göreli olarak karşılaştırılmıştır. Sığ ve tabakalı kaya ortamında tasman ve konverjans miktarının azaltılmasında, tünel geometrisinin at nalı tipi yerine yumurta şeklinde seçilmesinin daha avantajlı olduğu tespit edilmiştir.

Life-saving problems during fire in road tunnels

One of the main risk factors for the safe operation of tunnels, according to the design solutions of Georgian road tunnels, is the possibility of fire initiation with relevant negative consequences. The report will discuss the fire development scenarios under the ground based on the results of numerical modeling, as well as the recommendations for training and raising awareness of fire service personnel and rescuers depending on fire capacity, tunnel geometry, location and other factors, which will be applicable to the safe operation of transport tunnels and the survival of fire in the event of a fire.

Propagation of carbon monoxide in road tunnels in case of fire by considering the critical velocity, backlayering and gradient factor

The optimal use of transit potential is viewed as one of the basic means under the Economic Development Strategic Plan for Georgia with a primary emphasis on the modernization and development of the transport infrastructure. In this regard, the construction and improvement projects for the main and auxiliary highway structures are planned and carried out successfully across the country, with the construction of over 50 road tunnels in the country being one of the components. The sustainability and safe operation of the tunnels is the criterion for the successful implementation of such complex projects. As a result, it is critical to evaluate all risk factors for the safe operation of road tunnels as objectively as possible [1]. One of the major risk factors for the safe operation of a road tunnel is fires that start and spread for a variety of reasons, with the released carbon monoxide threatening the lives of people in emergency and the excess heat capable of inflicting the catastrophic damage to infrastructure. Thus, fires during the operation of road tunnels are one of the major threats to safety, with the level of risk determined by the likelihood of fire initiation in the tunnel and the severity of the potential damage caused by such a fire.  The likelihood of fire initiation in the tunnel, as well as the severity of potential damage from such a fire, are largely determined by the development, planning, and implementation of preventive measures, which will, first and foremost, prevent the initiation and development of fire, and, in the event of fire, will minimize the severity of potential consequences [2, 3]. At the same time, we must keep in mind that saving human lives and health during an emergency is priority number one. In the event of a tunnel fire, one of the primary preventive measures to save the lives of people in emergency situations is the selection and operation of flexible ventilation systems, correct and efficient modes of operation, taking into account the impact of actual processes during the fire. With this in mind, tunnel ventilation systems equipped with modern technologies enable people in the life-threatening situations to evacuate in a timely and organized manner and escape the danger zone. The report presents the outcomes of digital and physical road tunnel modeling. The former is full-scale, whereas the latter is 1:10 scale. Carbon monoxide propagation is determined by the nature of the ventilation flow motion, its critical velocity, backlayering distance, gradient factor, and fire strength. The findings are presented in the form of graphs and tables, which can be used to develop life-saving and emergency control projects in the event of a fire, taking into account the specific tunnel geographical conditions, geometry, and other relevant data.

Geometric differences in the ribosome exit tunnel impact the escape of small nascent proteins

The exit tunnel is the subcompartment of the ribosome that contains the nascent polypeptide chain and, as such, is involved in various vital functions, including regulation of translation and protein folding. As the geometry of the tunnel shows important differences across species, we focus on key geometrical features of eukaryote and prokaryote tunnels. We used a simple coarse-grained molecular dynamics model to study the role of the tunnel geometry in the post-translational escape of short proteins (short open reading frames [sORFs]) with lengths ranging from 6 to 56 amino acids. We found that the probability of escape for prokaryotes is one for all but the 12-mer chains. Moreover, proteins of this length have an extremely low escape probability in eukaryotes. A detailed examination of the associated single trajectories and energy profiles showed that these variations can be explained by the interplay between the protein configurational space and the confinement effects introduced by the constriction sites of the ribosome exit tunnel. For certain lengths, either one or both of the constriction sites can lead to the trapping of the protein in the “pocket” regions preceding these sites. As the distribution of existing sORFs indicates some bias in length that is consistent with our findings, we finally suggest that the constraints imposed by the tunnel geometry have impacted the evolution of sORFs.

Amplification effect of near-field ground motion around deep tunnels based on finite fracturing seismic source model

Dynamic failure of rock masses around deep tunnels, such as fault-slip rockburst and seismic-induced collapse, can pose a significant threat to tunnel construction safety. One of the most significant factors that control the accuracy of its risk assessment is the estimation of the ground motion around a tunnel caused by seismicity events. In general, the characteristic parameters of ground motion are estimated in terms of empirical scaling laws. However, these scaling laws make it difficult to accurately estimate the near-field ground motion parameters because the roles of control factors, such as tunnel geometry, damage zone distribution, and seismic source parameters, are not considered. For this, the finite fracturing seismic source model (FFSSM) proposed in this study is used to simulate the near-field ground motion characteristics around deep tunnels. Then, the amplification effects of ground motion caused by the interaction between seismic waves and deep tunnels and corresponding control factors are studied. The control effects of four factors on the near-field ground motion amplification effect are analyzed, including the main seismic source wavelength, tunnel span, tunnel shape, and range of damage zones. An empirical formula for the maximum amplification factor ( α m ) of the near-field ground motion around deep tunnels is proposed, which consists of four control factors, i.e. the wavelength control factor ( F λ ), tunnel span factor ( F D ), tunnel shape factor ( F s ) and excavation damage factor ( F d ). This empirical formula provides an easy approach for accurately estimating the ground motion parameters in seismicity-prone regimes and the rock support design of deep tunnels under dynamic loads.

Predictive Models to Evaluate the Interaction Effect of Soil-Tunnel Interaction Parameters on Surface and Subsurface Settlement

Nowadays, the need for subway tunnels has increased considerably with urbanization and population growth in order to facilitate movements. In urban areas, subway tunnels are excavated in shallow depths under densely populated areas and soft ground. Its associated hazards include poor ground conditions and surface settlement induced by tunneling. Various sophisticated variables influence the settlement of the ground surface caused by tunneling. The shield machine's operational parameters are critical due to the complexity of shield-soil interactions, tunnel geometry, and local geological parameters. Since all elements appear to have some effect on tunneling-induced settlement, none stand out as particularly significant; it might be challenging to identify the most important ones. This paper presents a new model of an artificial neural network (ANN) based on the partial dependency approach (PDA) to optimize the lack of explainability of ANN models and evaluate the sensitivity of the model response to tunneling parameters for the prediction of ground surface and subsurface settlement. For this purpose, 239 and 104 points for monitoring surface and subsurface settlement, respectively, were obtained from line Y, the west bond of Crossrail tunnels in London. The parameters of the ground surface, the trough, and the tunnel boring machine (TBM) were used to categorize the 12 potential input parameters that could impact the maximum settlement induced by tunneling. An ANN model and a standard statistical model of multiple linear regression (MLR) were also used to show the capabilities of the ANN model based on PDA in displaying the parameter's interaction impact. Performance indicators such as the correlation coefficient (R2), root mean square error (RMSE), and t-test were generated to measure the prediction performance of the described models. According to the results, geotechnical engineers in general practice should attend closely to index properties to reduce the geotechnical risks related to tunneling-induced ground settlement. The results revealed that the interaction of two parameters that have different effects on the target parameter could change the overall impact of the entire model. Remarkably, the interaction between tunneling parameters was observed more precisely in the subsurface zone than in the surface zone. The comparison results also indicated that the proposed PDA-ANN model is more reliable than the ANN and MLR models in presenting the parameter interaction impact. It can be further applied to establish multivariate models that consider multiple parameters in a single model, better capturing the correlation among different parameters, leading to more realistic demand and reliable ground settlement assessments. This study will benefit underground excavation projects; the experts could make recommendations on the criteria for settlement control and controlling the tunneling parameters based on predicted results. Doi: 10.28991/CEJ-2022-08-11-05 Full Text: PDF

Evaluation of rockburst energy capacity for the design of rock support systems for different tunnel geometries at El Teniente copper mine

Rockburst events have been a serious problem for many years in many mines worldwide, and in particular at El Teniente mine in Chile. El Teniente is the largest copper mine in the world, located in the Andes Cordillera where high stress levels are present due to intensing mining activity in addition to complex geology. Consequently, the study and management of the rockburst threat are necessary. In this work, the case of the Diablo Regimiento (DR) mine within El Teniente is studied. The energy capacity of dynamic support systems is determined for different tunnel geometries based on two kinetic methodologies, using data from DR. Initially, rockburst potential is determined by means of a stress analysis around different tunnel geometries through the boundary elements method. In the first methodology a yielding zone (YZ) is estimated for each excavation geometry using the finite element method FEM. The second methodology involves the definition and determination of a critical strain energy (SE) around each excavation geometry using a FEM numerical analysis. In both cases, peak particle velocity PPV is estimated by a scaling law, which is subsequently adjusted due to tunnel amplification effects. According to the results, and knowing the working energy capacity applied in DR mine, it was found that the values of energy capacity for the rock dynamic supports were better estimated by the YZ-PPV approach than by the SE approach.

A Method for Large Underground Structures Geometry Evaluation Based on Multivariate Parameterization and Multidimensional Analysis of Point Cloud Data

In underground mining, new workings (tunnels) are constructed by blasting or mechanical excavation. The blasting technique used in underground mines is supported by economic aspects, especially for deposits characterized by hard rocks. Unfortunately, the quality of the result may be different than expected in terms of the general geometry of work or the roughness of excavation surfaces. The blasting technique is also a source of vibrations that may affect other existing structures, affecting their stability. Therefore, it is of great importance to monitor both the quality of the new tunnels and changes in existing tunnels that may cause rockfall from the sidewalls and ceilings of both new and existing tunnels. The length of mining tunnels and support structures in underground mines is massive. Even if one would like to limit monitoring of tunnel geometry to those used every day for major technological processes such as transport, it is a vast amount of work. What is more, any stationary monitoring system is hard to utilize both due to everyday blasting procedures and mobile machine operation. The method proposed here is based on quick LiDAR/Terrestrial Laser Scanner measurements to obtain a cloud of points, which allows generating the spatial model of a mine’s geometry. Data processing procedures are proposed to extract several parameters describing the geometry of the tunnels. Firstly, the model is re-sampled to obtain its uniform structure. Next, a segmentation technique is applied to separate the cross sections with a specific resolution. Statistical parameters are selected to describe each cross section for final 1D feature analysis along the tunnel length. Such a set of parameters may serve as a basis for blasting evaluation, as well as long-term deformation monitoring. The methodology was tested and validated for the data obtained in a former gold and arsenic mine Zloty Stok, Poland.

Investigation of feature contribution to shield tunneling-induced settlement using Shapley additive explanations method

Accurate prediction of shield tunneling-induced settlement is a complex problem that requires consideration of many influential parameters. Recent studies reveal that machine learning (ML) algorithms can predict the settlement caused by tunneling. However, well-performing ML models are usually less interpretable. Irrelevant input features decrease the performance and interpretability of an ML model. Nonetheless, feature selection, a critical step in the ML pipeline, is usually ignored in most studies that focused on predicting tunneling-induced settlement. This study applies four techniques, i.e. Pearson correlation method, sequential forward selection (SFS), sequential backward selection (SBS) and Boruta algorithm, to investigate the effect of feature selection on the model's performance when predicting the tunneling-induced maximum surface settlement ( S max ). The data set used in this study was compiled from two metro tunnel projects excavated in Hangzhou, China using earth pressure balance (EPB) shields and consists of 14 input features and a single output (i.e. S max ). The ML model that is trained on features selected from the Boruta algorithm demonstrates the best performance in both the training and testing phases. The relevant features chosen from the Boruta algorithm further indicate that tunneling-induced settlement is affected by parameters related to tunnel geometry, geological conditions and shield operation. The recently proposed Shapley additive explanations (SHAP) method explores how the input features contribute to the output of a complex ML model. It is observed that the larger settlements are induced during shield tunneling in silty clay. Moreover, the SHAP analysis reveals that the low magnitudes of face pressure at the top of the shield increase the model's output. • Application of SHAP method for investigating the tunneling-induced settlement. • Feature selection using the Boruta algorithm and the Pearson correlation method. • The soil type predominantly influences the tunneling-induced settlement. • Low face pressure at the top of the shield boosts the settlement during tunneling.

Applications Of Thermographic Particle Image Velocimetry To Film Cooling Flow Experiments In A Closed Loop Wind Tunnel

A laser-imaging method based on thermographic phosphor tracer particles (thermographic particle image velocimetry) is used to simultaneously measure temperature and velocity fields in film cooling flows in wind tunnels, in order to compare novel film cooling configurations under conditions of realistic mainstream turbulence. Several important experimental factors that affect the measurement precision, accuracy, and ultimately the success of the technique in its application in these practical environments are identified: (1) the choice of phosphor particles, which affects the inherent temperature sensitivity and flow tracing accuracy; (2) the particle seeding and management of particle deposition, which affects control of the overall particle number density and seeding uniformity and temporal stability; (3) the setup of the excitation laser/detection cameras and the wind tunnel geometry, which influences background interference from deposited particles and potential influence of multiple scattering. This paper discusses these three factors, gathering and adding to information in prior journal publications, to provide guidance and future research directions for experimental researchers wishing to use these optical diagnostics in film cooling studies and similar enclosed geometries.

Life-saving problems during fire in road tunnels

One of the main risk factors for the safe operation of tunnels, according to the design solutions of Georgian road tunnels, is the possibility of fire initiation with relevant negative consequences. The report will discuss the fire development scenarios under the ground based on the results of numerical modeling, as well as the recommendations for training and raising awareness of fire service personnel and rescuers depending on fire capacity, tunnel geometry, location and other factors, which will be applicable to the safe operation of transport tunnels and the survival of fire in the event of a fire.

Predicting earth pressure balance (EPB) shield tunneling-induced ground settlement in compound strata using random forest

The prediction and control of the ground settlement induced by shield tunneling in compound strata is a crucial challenge for tunnel excavation. In this regard, a finite element model for the analyses of ground surface settlement induced by earth pressure balance (EPB) tunneling was established and validated by the field test. The influence of single influence factors, such as rock proportion in the face, support pressure, and tunneling angle, on the surface settlement above the tunnel face was systematically studied. To investigate the joint influence of different factors on ground deformation mechanism, the multi-factor analysis based on field data and the multiple regression (MR) method was conducted. However, the prediction accuracy of the MR method was limited. Therefore, a prediction approach of shield tunneling-induced settlement in compound strata based on a random forest (RF) was developed. Tunnel geometry, geological features, and operation parameters were investigated as input variables in the RF model to achieve this goal. The applicability effect of the RF-based method was proved by utilizing two data sets (i.e., the settlement ahead of tunnel face and final settlement). The results indicated that the prediction accuracy of shield tunneling-induced settlement in compound strata by the RF-based model is higher than the MR method. The relative importance analysis of variables indicates that advance rate, the cover depth of the tunnel ring, and pressure in the chamber were the most influential features for the settlement ahead of the tunnel face, while the thrust of the cutter head and the grout quantity were the most significant variables for the settlement after the segment assembling is completed. Overall, the conducted study could provide a helpful reference for the efficient excavation of EPB tunnels across compound strata.

Explosion Characteristics of Hydrogen Gas in Varying Ship Ventilation Tunnel Geometries: An Experimental Study

Hydrogen is widely regarded as a key element of prospective energy solutions for alleviating environmental emission problems. However, hydrogen is classified as a high-risk gas because of its wide explosive range, high overpressure, low ignition energy, and fast flame propagation speed compared with those of hydrocarbon-based gases. In addition, deflagration can develop into detonation in ventilation or explosion guide tunnels if explosion overpressure occurs, leading to the explosion of all combustible gases. However, quantitative evidence of an increase in the explosion overpressure of ventilation tunnels is unavailable because the explosive characteristics of hydrogen gas are insufficiently understood. Therefore, this study investigated an explosion chamber with the shape of a ventilation pipe in a ship compartment. The effect of tunnel length on explosion overpressure was examined experimentally. For quantitative verification, the size of the hydrogen gas explosion overpressure was analyzed and compared with experimental values of hydrocarbon-based combustible gases (butane and LPG (propane 98%)). The experimental database can be used for explosion risk analyses of ships when designing ventilation holes and piping systems and developing new safety guidelines for hydrogen carriers and hydrogen-fueled ships.

Intelligent Prediction of Multi-Factor-Oriented Ground Settlement During TBM Tunneling in Soft Soil

Tunneling-induced ground surface settlement is associated with many complex influencing factors. Beyond factors related to tunnel geometry and surrounding geological conditions, operational factors related to the shield machine are highly significant because of the complexity of shield-soil interactions. Distinguishing the most relevant factors can be very difficult, for all factors seem to affect tunneling-induced settlement to some degree, with none clearly the most influential. In this research, a machine learning method is adopted to intelligently select features related to tunneling-induced ground settlement based on measured data and form a robust non-parametric model with which to make a prediction. The recorded data from a real construction site were compiled and 12 features related to the operational factors were summarized. Using the intelligent method, two other features in addition to cover depth–pitching angle and rolling angle–were distinguished from among the 12 feature candidates as those most influencing the settlement trough. Another new finding is that advance rate does not emerge in the top 10 selected models from the observational data used. The generated non-parametric model was validated by comparing the measured data from the testing dataset and performance on a new dataset. Sensitivity analysis was conducted to evaluate the contribution of each factor. According to the results, engineers in general practice should attend closely to pitching angle during tunnel excavation in soft soil conditions.

Wind Tunnel Installation Effects on Japan Aerospace Exploration Agency’s Standard Model

This paper investigates the interference effects of wind tunnel floor and walls on the Japan Aerospace Exploration Agency’s High-Lift Configuration Standard Model (JSM) as an extension to a paper published in the Journal of Aircraft, Vol. 56, No. 3, May–June 2019, pp. 1080–1098. An unstructured hybrid grid generator, MEGG3D, was applied to JSM wing–body and wing–body–nacelle–pylon configurations to generate grids for free-air flow conditions. These grids were then reused in an investigation of the interference effects of Japan Aerospace Exploration Agency’s low-speed wind tunnel walls to better compare the computational results, both with each other and with experiment. The geometry of the wind tunnel used in our computational simulations is described in detail so that they can be reproduced. A Reynolds-averaged Navier–Stokes flow solver for unstructured hybrid grids, the Tohoku University Aerodynamic Simulation (TAS) code, was used for the simulations. The computational results indicated that the standoff and test section floor boundary layer significantly affected the aerodynamics of the JSM at high angles of attack. Better agreement with experiment was observed for the wing–body configuration in the aerodynamic characteristics near maximum lift if the effects of the standoff and floor boundary layer were considered.

An Improved Updatable Backpropagation Neural Network for Temperature Prognosis in Tunnel Fires

Because it is impossible to predict the temperature in advance, specific fire scenes (fire type, fire location, tunnel geometry, etc.) are unknown in traditional tunnel fire research. To address this difficulty, this work developed a novel algorithm to achieve temperature prognosis in tunnel fires that includes an updatable backpropagation (BP) neural network and a smoothing procedure. The data-driven algorithm is not limited to a specific fire scene, which makes it easy to fit real complex tunnel fire disasters. In addition, a full-scale fire test was conducted and utilized to verify the algorithm. Two innovations, including the updatable BP neural network and the smoothing procedure, made the predicted results match well with the experimental results. We can achieve a real-time precise temperature prediction 20 s in advance at a high accuracy of about 85.6%. If there is no sudden external factor intervention, the accuracy is about 99.4%. The algorithm provides an effective numerical tool for early fire warning and firefighting decision making that can address the temperature prognosis of tunnel fires.