Tunneling Characteristics Research Articles

Temperature distribution characteristics of linear fires in utility tunnels under the influence of sealing ratios and vertical positions of the fire source

This study delves into two key factors affecting fire development process and longitudinal ceiling temperature attenuation characteristics in a utility tunnel: the sealing ratios and the vertical positions of the linear fire source. The evolution process of linear fire is typically divided into five stages. In the stable combustion stage, the flame height at the end of the liner fire source is observed to be higher than that at the center. During the rapid loss stage of mass, the mass loss rate peaks and then stabilizes for a period of time, the maximum peak growth rate is 1.35 (the fire source is located at position 02), the duration shortens as the distance between the liner fire source and the ceiling decreases and the sealing ratio increases. When the sealing ratio is 100 %, the maximum temperature growth rate is 2.25 with the change of fire source position. The ceiling temperature in the upper part of the linear fire zone is lower in the center and higher on both sides, however, the distribution is asymmetric. A mathematical model of longitudinal ceiling temperature attenuation is established. The results may provide guidance for the control of linear fires in long-narrow confined spaces.

Electrical circuit approaches to modeling brain chaos: insights into neural dynamics

This paper investigates the simulation of brain chaos dynamics using a combination of the Chua circuit and diode tunnel mechanisms, aiming to examine chaotic behavior in brain networks. Leveraging the inherent chaotic properties of the Chua circuit, Fitzhugh-Nagumo (FHN) function and the nonlinear characteristics of diode tunneling, our model offers a platform to mimic the intricate synaptic interactions observed in the brain. By subjecting the model to various stimuli and perturbations, we analyze the emergence and evolution of chaotic patterns, shedding light on the underlying mechanisms of cerebral chaos. Through numerical simulations and experimental validation, we demonstrate the effectiveness of our approach in replicating key features of brain chaos and highlight its potential implications for understanding neurological disorders and cognitive processes. This research contributes to the broader effort of leveraging computational models to explore the complex dynamics of the brain and their implications for neuroscience and microengineering.

Analytical study on plastic loosening zone of weak surrounding rocks tunnel in high cold areas

AbstractThe analysis of plastic loosening zone of tunnels with cold condition, high in situ stress, and weak stratum is the key scientific problem of tunnel construction in cold areas. Based on the unified strength theory and considering the coupling effect of high in situ stress and low‐temperature field, the analytical model of the plastic loosening zone of tunnel surrounding rocks was proposed, and the influence laws of physical parameters (initial ground stress, freezing temperature, excavation radius, and intermediate principal stress) was explored. The results illustrate that: (1) with the coupling of low temperature and stress fields, the in‐situ stress has a more significant effect on the radius of the plastic loosening zone of the tunnel surrounding rocks, showing a nonlinear correlation. When the in situ stress is small, the influence of the temperature field on the radius of the plastic loosening zone is more obvious. (2) The radius of the plastic loosening zone of the tunnel surrounding rocks increases synchronously with the excavation radius and gradually decreases with the increase of the intermediate principal stress. (3) The greater the temperature difference in the low‐temperature field, the tunnel stability has a more significant response to the intermediate principal stress and is positively correlated with the coefficient of the intermediate principal stress. (4) In the actual project, the proposed model can well describe the mechanical behavior and deformation characteristics of tunnel surrounding rocks in low‐temperature environment, showing applicability. The research results are expected to provide a theoretical basis for the study of tunnel stability in cold areas.

Experimental Study on Fire Characteristics of Urban Rectangular Tunnels Based on Different Slopes

Experimental Study on Fire Characteristics of Urban Rectangular Tunnels Based on Different Slopes

Numerical Study on Large Deformation Characteristics of Tunnels Excavated in Strain-Softening Time-Dependent Rock Masses

Numerical Study on Large Deformation Characteristics of Tunnels Excavated in Strain-Softening Time-Dependent Rock Masses

Effect of Support-Induced Stress on the Failure Characteristics of Deep Tunnels Based on True-Triaxial Compression Tests

Effect of Support-Induced Stress on the Failure Characteristics of Deep Tunnels Based on True-Triaxial Compression Tests

Failure analysis and deformation characteristics of shield tunnel obliquely crossing ground fissure under earthquake

In order to study the deformation law and failure characteristics of shield tunnel obliquely crossing ground fissure under earthquake action, taking the shield tunnel of Xi ’an Metro Line 8 crossing f3 ground fissure as the engineering background, the 1: 20 shaking table model test method was used to analyze the strain of shield tunnel, the contact pressure with surrounding rock soil, the dislocation of segment and the axial force of bolt in detail, and the seismic damage mechanism and failure characteristics of shield tunnel obliquely crossing ground fissure were obtained. The test results show that under the action of earthquake, the shield tunnel has complex three-dimensional deformation characteristics, among which the vertical deformation is the most obvious. The deformation is mainly concentrated in the location of the ground fissure. The tensile strain and contact pressure of the hanging wall of the tunnel segment are greater than the strain value and contact pressure of the footwall. Because the vertical deformation of the tunnel is the largest, the bolts at the vault and the arch bottom are most obviously pulled. Excavation after the test, it can be seen that the tunnel appeared the phenomenon of ring joint opening, lining cracking and other damage. Under the action of the earthquake, the shield tunnel across the ground fissure is mainly subjected to tensile failure. The failure area is within 10 m from the ground fissure in the hanging wall and footwall, and the total length is 20 m. The closer to the ground fissure, the more serious the damage. The research results provide a scientific and reasonable reference for the subsequent construction and disaster prevention and mitigation design of Xi ’an Metro.

Fire and smoke transport dynamics in a dead-end tunnel under heavy rainfall

Fire is one of the most common major accidents during tunnel construction and operation. This work conducted scale-model experiments to investigate the pool burning progress and flame characteristics in a dead-end tunnel with one end closed and the other open under heavy rainfall. The results show that, compared to opening both ends, the global burning time of fires is significantly decreased, and the quasi-stable burning phase is advanced under the combined effects of the closed end and heavy rainfall. The reason is that the increase in ceiling temperature, resulting from the accumulation of hot smoke, leads to an increase in radiative feedback of the fuel from the environment and an acceleration in the pool's burning rate. A coefficient (denoted by γ) is defined to evaluate the increase in the burning rate resulting from the dead-end. The enhancement ratio is found to be related to rainfall intensity, raindrop size, and pool size, and a correlation has been established based on the experimental results. The fire has an increased flame height and a reduced tilt angle under the impact of the dead-end. The changes in flame geometry parameters are mainly influenced by thermal buoyancy and the restriction of the dead-end. Prediction formulas for flame height and tilt angle under the combined effects of the dead-end and heavy rainfall have been proposed based on theoretical analysis. Under these combined effects, the tunnel space becomes eroded by dirty air.

Self-Organizing and Routing Approach for Condition Monitoring of Railway Tunnels Based on Linear Wireless Sensor Network.

Real-time status monitoring is crucial in ensuring the safety of railway tunnel traffic. The primary monitoring method currently involves deploying sensors to form a Wireless Sensor Network (WSN). Due to the linear characteristics of railway tunnels, the resulting sensor networks usually have a linear topology known as a thick Linear Wireless Sensor Network (LWSN). In practice, sensors are deployed randomly within the area, and to balance the energy consumption among nodes and extend the network's lifespan, this paper proposes a self-organizing network and routing method based on thick LWSNs. This method can discover the topology, form the network from randomly deployed sensor nodes, establish adjacency relationships, and automatically form clusters using a timing mechanism. In the routing, considering the cluster heads' load, residual energy, and the distance to the sink node, the optimal next-hop cluster head is selected to minimize energy disparity among nodes. Simulation experiments demonstrate that this method has significant advantages in balancing network energy and extending network lifespan for LWSNs.

Machine learning-Based method for gas leakage source term estimation in highway tunnels

Incidents involving the leakage of flammable and explosive chemicals in highway tunnels can lead to disastrous events such as fires and explosions. The distinctive features of highway tunnels, characterized by their confined and elongated structure, intensify the complexity of managing such accidents, potentially resulting in significant casualties and property damage. Rapid detection and acquisition of leakage source information during a flammable gas leak in a highway tunnel are of utmost importance for effective accident management. This study introduces a predictive model developed using a machine learning approach. The model uses time series data from gas concentration sensors and anemometers installed within the tunnel to predict parameters such as gas leakage velocity, source location, and initiation time. A computational fluid dynamics simulation of gas leakage within the tunnel was constructed, and a dataset was generated using sample generation and preprocessing methods. The results demonstrate that this method exhibits robust predictive performance. Furthermore, a prediction strategy is proposed to enhance the model’s predictive accuracy and resilience to data noise. This model offers valuable insights for improving accident management strategies for gas-related incidents in highway tunnels.

A Long Short Term Memory Model for Character-based Analysis of DNS Tunneling Detection

DNS tunneling is the attempt to create a hidden tunnel through a domain name service. Such a tunnel would jeopardize the targeted network and open the door for illegal access, control, and data exfiltration. The information security research community showed the variety of techniques that have been proposed to detect the tunnel. The majority of these efforts were relying on machine learning techniques where features of tunneling are considered such as length of DNS query, size, and entropy of the query. However, an additional analysis of the lexical information of the DNS query has been depicted recently and showed remarkable performance. This paper aims to examine the role of Long Short Term Memory (LSTM) model in terms of DNS lexical analysis. Two benchmark datasets related to DNS have been used. In addition, a character mapping mechanism has been used to replace every possible character with an integer number. Consequentially, the mapped representation has been fed into an LSTM model for DNS tunneling detection. Results showed that the proposed method was able to obtain a weighted average F1-score of 98% for both datasets respectively. Such results are competitive in the context of the state of the art and demonstrate the efficacy of the lexical analysis within the DNS tunneling detection task.

Ground motion amplification by twin circular tunnels for obliquely incident seismic waves: Effects of saturated poroelastic soil parameters

Underground structures can significantly affect the ground motion and further influence the seismic design of aboveground structures around them. Although this issue has been well recognised and studied, it is not thoroughly addressed as a large number of factors are involved. This paper focuses on ground motion amplification induced by twin circular tunnels embedded in saturated poroelastic soil. The saturated poroelastic soil is modelled as a two-phase medium to consider parameters characterising the fluid phase. Three-dimensional scattering features of the twin tunnels for obliquely incident seismic waves are numerically investigated by a 2.5D finite element and boundary element hybrid model. It is shown that the presence of the twin tunnels can lead to significant modifications of the free-field motion, in terms of its magnitude and distribution. The three-dimensional oblique incidence scenario presents a more general perspective on the ground motion amplification. Moreover, the effects of saturated poroelastic soil parameters on the ground motion amplification, including soil permeability, groundwater levels, and the degree of saturation, are parametrically investigated. The differences in ground motion amplification patterns between the saturated poroelastic and dry poroelastic soil scenarios are notable, highlighting the effects of parameters characterising the fluid phase.

Experimental study on the influence of extremely broken surrounding rock grade on the mechanical characteristics of tunnels

To study the significant deformation and distortion issues in certain sections of the Qinyu tunnel extremely fragmented surrounding rock under identical conditions, six tunnel sections with the same depth of burial and lithology were selected for on-site monitoring of stress. The experimental data were then used to explore the impact of gradation on the mechanical characteristics of the extremely fragmented surrounding rock tunnels. The results indicate that the tunnel experiences larger stresses at the crown and smaller stresses at the side walls and invert, showing the influence of gradation on the stress behavior of extremely fractured surrounding rock. A dual-fractal structure model was employed to quantitatively describe the gradation of the surrounding rock, yielding fitting coefficients above 0.9. The model demonstrated good applicability for extremely fractured rock with significant particle size differences. Additionally, the relationship between fractal model parameters and the maximum rock pressure at various tunnel sections was discussed, revealing an exponential correlation between the absolute difference in fractal dimensions of coarse and fine particles and the maximum rock pressure. To further understand the factors and the influence of gradation on tunnel rock pressure, indoor model tests were conducted using six different gradations. The experimental results once again confirmed the importance of gradation on the stress behavior of highly fragmented rock tunnels and validated the functional relationship between the absolute difference in fractal dimensions and rock pressure. The results can provide guidance for the design of tunnels with extremely fractured surrounding rocks in the future.

Seismic characteristics of segmental tunnels considering seal roof blocks arrangement

The position of seal roof block may greatly affect the overall performance of the segmental tunnel. However, a few investigations have been dedicated to evaluating this effect. In the present study, finite element models are established to simulate the ring structure-soil model in order to evaluate the capacity curve of the universal ring structure during progressive failure. Nineteen universal ring structures configurations were analyzed considering different locations of the adjacent seal roof blocks. The models accurately simulated the structural details of the typical handhole for curved bolt in the circumferential and longitudinal joints. The seismic performance of the universal ring structure with different configurations is evaluated and discussed in terms of the moment curve, plastic zone distribution, joint opening angle curve and capacity curve of the universal ring. The results indicate that there are significant differences in the maximum positive and negative moment, plastic zone, and tensile angle of the universal ring structure when the seal roof block is in different positions. At the same time, the development of the performance curve of the ring will also show significant differences, especially in the elastic stage. The structure exhibits best seismic performance when the seal roof block is located at arch shoulder and waist (−67.5° ± 22.5°) because it is less likely to reach the normal function, immediate operational, rectifiable or irreparable damage stages compared to other configurations.

An innovative model for electrical conductivity of MXene polymer nanocomposites by interphase and tunneling characteristics

The endeavor to forecast the electrical conductivity in composites constituted of MXene nanosheets and polymers presents a significant challenge due to the absence of a simplistic model. The present investigation introduces a comprehensive model that anticipates the electrical conductivity of specimens filled with MXene. The proposed methodology incorporates a multitude of variables that determine the total conductivity of the specimens. These variables encompass the size parameters of MXene, the percolation onset, the volumetric fraction of MXene, the tunneling distance, the interphase thickness, and the network fraction. The reliability of this methodology is rigorously tested using experimental data derived from several specimens. Moreover, a comprehensive examination of the relationship between the estimated conductivity and the variables is carried out to verify the trustworthiness of the suggested approach. The outcomes derived from the suggested model demonstrate a significant alignment with the results from the experiments. Factors such as slender and larger nanosheets, thicker interphase, smaller tunneling distance, and higher portion of percolated nanosheets in the network can significantly enhance the conductivity of nanocomposite. The maximum electrical conductivity of 14 S/m is attained with the lowest tunneling distance of 1.4 nm and the lowest percolation onset of 0.01. Additionally, with the maximum interphase thickness of 41 nm and the highest MXene conductivity of 3 ×106 S/m, the nanocomposite achieves an optimal conductivity of 2 S/m.

Centrifuge modelling of the dynamic response of twin tunnels under train-induced vibration load

The impact of train-induced vibrations originating from underground tunnels has emerged as a significant environmental issue within urban areas. A multitude of studies, encompassing both numerical analyses and experimental investigations, have been undertaken to explore and address this concern. In the experimental tests, the dynamic characteristics of tunnels and soil has generally been studied using physical models with a single tunnel under a 1 g (gravity) environment. However, twin tunnels are commonly constructed in the field, and the stress of the soil is unrealistically simulated in 1 g models. In this paper, the dynamic characteristics of twin tunnels were studied by centrifuge testing. In this paper, results are presented from scaled model tunnel tests conducted at 50 g for four different conditions: a single tunnel, vertical twin tunnels with 60 mm spacing, horizontal twin tunnels with 60 mm and 120 mm spacing. Train load and sweep load were applied by a parallel pre-stressed actuator at the tunnel invert. Accelerometers were employed to gauge the dynamic response of both the tunnels and the surrounding soil. The experimental results illustrate that the interaction between twin tunnels has a clear amplification effect on the dynamic response of the loading tunnel, with the maximum peak particle acceleration (PPA) increasing by up to 43 %. This amplification phenomenon is reduced as the space between the twin tunnels is increased. The experimental results also indicate that the interaction between twin tunnels has a comparatively lower impact on the dynamic response of the surrounding soil when contrasted with the dynamic response of the tunnels themselves.

Morphological characteristics of the cubital tunnel as indication for anterior interosseous nerve supercharge end-to-side transfer in treating advanced cubital tunnel syndrome

BackgroundCubital tunnel syndrome (CuTS) is a prevalent compressive neuropathy addressed through various treatments, including the anterior interosseous nerve (AIN) supercharge end-to-side (SETS) transfer for advanced CuTS. Decision to add AIN-SETS is based on various indicators and protocols, but deciding on the appropriate method for borderline cases can be challenging. Therefore, this study aims to non-invasively examine the cubital tunnel anatomy of patients using CT scans and compare the findings with existing indicators and measurements, to determine if they can serve as supplementary indicators to aid in treatment decisions. HypothesisThe bony cubital tunnel volume is correlated to other traditional indicators and can be used as an additional indication for deciding whether to perform AIN-SETS in treating advanced CuTS. Patients and MethodsThis is a single-center retrospective cohort study from South Korea, including 91 patients aged 20–70 years with CuTS. Participants were classified into Group A (n = 43), who underwent both cubital tunnel release (CuTR) and AIN-SETS, and Group B (n = 48), who underwent only CuTR. Preoperative elbow CT data were analyzed for cubital tunnel morphology analysis, with follow-up assessments such as grip strength and electromyography/ nerve conduction velocity (EMG/NCV) tests at 3, 6, and 12 months postoperatively. ResultsGroup A and B showed no significant differences in demographic parameters, except for a longer disease duration in Group A (p = 0.032). Group A had a smaller cubital tunnel volume (CTV) compared to Group B (1150.6 ± 52.8 mm3 vs. 1173.5 ± 56.2 mm3, p = 0.014) and a smaller cross-sectional area (40.9 ± 10.2 mm2 vs. 45.1 ± 11.7 mm2, p = 0.033). Pearson correlation analysis revealed statistically significant positive correlations between CTV measurements and pre-operative grip strength, as well as EMG results, a key indicator for AIN-SETS (R2 = 0.48, 0.23, p = 0.01). DiscussionMeasuring the cubital tunnel anatomy using CT can aid in determining the treatment approach for advanced CuTS patients and assist in deciding whether to perform AIN-SETS surgery, serving as a supplementary indicator for cases at the borderline limits of other indicators. Future research may be necessary to establish control groups without symptoms and determine appropriate cut-off values. Level of evidenceIV.

A Study on Deformation Characteristics and Stability of Soft Surrounding Rock for a Shallow-Buried Tunnel

The Heimaguan Tunnel in China serves as a case study to exemplify the variation laws related to surface settlement, deformation, and stress characteristics in a shallow-buried soft-rock tunnel, while emphasizing in the tunnel support requirements. The first stage of this study begins with monitoring the time-varying characteristics of surface settlement, vault subsidence, and the horizontal convergence of Grade V rock. In the second stage, Peck theory is used to calculate the distribution characteristics of surface settlement. The results of both stages are compared to create a vault settlement model, thus establishing the horizontal convergence based on exponential function, logarithmic function and hyperbolic function, and determining the optimal time of secondary lining construction. On this basis, the time-dependent variation laws and characteristics of vertical and horizontal displacement and principal stress of surrounding rock are studied. After this, using simulation and analysis, the proper support is recommended. The study reveals that the surface settlement, vault subsidence, and horizontal convergence of the shallow-buried soft-rock tunnel stabilize within 25–30 days. Peck theory closely aligns with predictions based on exponential functions, with only a 0.72% difference. The recommended time for secondary lining application is 26–27 days.

Advanced modeling of conductivity in graphene–polymer nanocomposites: insights into interface and tunneling characteristics

Advanced modeling of conductivity in graphene–polymer nanocomposites: insights into interface and tunneling characteristics

FSDC: Flow Samples and Dimensions Compression for Efficient Detection of DNS-over-HTTPS Tunnels

This paper proposes an innovative approach capitalized on the distinctive characteristics of command and control (C&C) beacons, namely, time intervals and frequency between consecutive unique connections, to compress the network flow dataset. While previous studies on the same matter used single technique, we propose a multi-technique approach for efficient detection of DoH tunnels. We use a baseline public dataset, CIRA-CIC-DoHBrw-2020, containing over a million network flow properties and statistical features of DoH, tunnels, benign DoH and normal browsing (HTTPS) traffic. Each sample is represented by 33 features with a timestamp. Our methodology combines star graph and bar plot visualizations with supervised and unsupervised learning techniques. The approach underscores the importance of C&C beacon characteristic features in compressing a dataset and reducing a flow dimension while enabling efficient detection of DoH tunnels. Through compression, the original dataset size and dimensions are reduced by approximately 95% and 94% respectively. For supervised learning, RF emerges as the top-performing algorithm, attaining precision and recall scores of 100% each, with speed increase of ≈6796 times faster in training and ≈55 in testing. For anomaly detection models, OCSVM emerges as the most suitable choice for this purpose, with precision (88.89) and recall (100). Star graph and bar graph models also show a clear difference between normal traffic and DoH tunnels. The reduction in flow sample size and dimension, while maintaining accuracy, holds promise for edge networks with constrained resources and aids security analysts in interpreting complex ML models to identify Indicators of Compromise (IoC).