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Ground-penetrating radar (GPR) is a mainstream tool to detect defects behind tunnel linings, but the difficulty in interpreting GPR signals limits its application. This paper proposes an intelligent way to differentiate the defects behind tunnel linings by means of a model test and feature parameter analysis, to achieve an efficient and accurate analysis of GPR signals. The model test reveals the differences between defect and non-defect GPR data in amplitude, signal entropy, standard deviation, and other feature parameters. The amplitude of the defect data was on average six times as large as that of non-defect data, and the signal entropy was about 1.2 times larger. The two feature parameters lay the basis for defect detection by GPR. On this basis, a GPR-based automatic identification method was proposed, and the program was compiled on MATLAB. The program achieved a defect recognition rate as high as 96% through a field test at a rapid speed. The program is highly accurate and feasible for detecting defects behind tunnel linings with the aid of GPR. [ABSTRACT FROM AUTHOR]

Cracks are the most common disease in reinforced concrete structures, which seriously affects the stability of the structure. At present, the evaluation criteria for the degree of crack danger are relatively vague, and there are significant shortcomings in the quantitative evaluation of the stability of concrete structures containing cracks. This article comprehensively utilizes numerical simulation, numerical fitting, and fractal theory to establish a quantitative calculation method for structural bearing performance based on crack characteristic parameters. The main research conclusions are as follows: the influence of crack length, direction, and depth characteristic parameters on the bearing performance of reinforced concrete structures is determined through numerical simulation; A quantitative calculation method for structural bearing performance was established using a step-by-step fitting method, which comprehensively considers crack characteristic parameters. On this basis, the fractal theory was used to describe the complexity of cracks and the calculation results of the combined crack-bearing performance were corrected. Compared with numerical simulation and model experiment results, the average error in calculating the structural bearing coefficient was 5%. The research results have improved the accuracy of crack evaluation and can provide an important reference for the safety analysis of cracks in concrete structures. • Through a reinforced concrete calculation model, crack simulation and bearing capacity analysis were achieved. • Revealed the influence of crack length, direction, and depth on bearing performance. • Established a calculation method for crack characteristics and load-bearing performance. [ABSTRACT FROM AUTHOR]

Diffusion radius is an important construction parameter, because it can significantly influence the grouting effectiveness. Theoretical models in predicting diffusion radius have been practiced, but there are still significant discrepancies between theoretical calculations and realistic results in the practical construction. One of the critical reasons for the misprediction is the time-dependent behavior of the cement grout, which is significantly affected by the water-cement ratio (W/C). Therefore, this paper experimentally and numerically studies the influence of W/C on the viscosity variation of the grout and grouting process. Firstly, the apparent viscosity of the cement grout under different W/C is tested by a rotational viscometer in a laboratory experiment. Subsequently, based on the laboratory tests, numerical models are established to investigate the influence of W/C on the diffusion process of cement grout in sand layers. According to the laboratory results, the apparent viscosity of cement grouts decreases with the increase of W/C. Besides, the apparent viscosity increases with time, while the increasing range of apparent viscosity firstly increases and then decreases as W/C increases. Based on the simulated results, when W/C changes from 0.8 to 1.1, the diffusion radius at 60 min experiences a less and less obvious increase under the given grouting pressure for permeation grouting in the sand layer. When W/C is 0.9, the relative error reaches to 37.65% at 60 min, which is slightly lower than that of 0.8. However, when W/C changes from 0.9 to 1.0, the relative error becomes very narrow (21.36%), and this figure is much lower than that of 0.8 or 0.9. The simulation results are verified by field test, and the relative error is 6%, which proves the effectiveness of the analysis. Therefore, the cement permeation model considering viscosity variation of the grout is a reasonable alternative in the real project. At the same time, the time-dependent behavior of cement grouts should be considered, especially when using cement grouts with a low water-cement ratio in the practical engineering. [ABSTRACT FROM AUTHOR]

To ensure the safety of tunnel construction, it is necessary to accurately and timely measure the deformation of the shotcrete liner during the management of the construction process. The light detection and ranging (LiDAR) technique, known as the reality reproduction technology, provides a new solution for deformation measurement. However, the nonsmooth defects of shotcrete liner and the scattered noise points caused by the nearby dust, as well as a large number of nontunnel structures such as pipes, construction machinery, and vehicles in the obtained tunnel point cloud datasets, hinder the application of point clouds in deformation measurement of shotcrete liner. In this paper, a ring simulation sampling (RSS) method for automatic sampling and deformation measurement of shotcrete liner using the multiepoch LiDAR point clouds is proposed. This method constructs the virtual ring according to shape of the tunnel cross section and emits the rays from the ring to the center of each tunnel cross section. The length difference of the rays arriving at the outer wall of the multiepoch tunnel point clouds is calculated to achieve the analysis of overall and local deformations of the shotcrete liner. The shotcrete liner point clouds generated by the manual modeling and terrestrial laser scanning are tested to validate the effectiveness of the method in extracting the deformation of shotcrete liner. Compared with the conventional total station monitoring, the mean absolute deviation and root mean square error are 1.39 and 1.93 mm, respectively, which indicates that the RSS method could be effectively applied to the deformation measurement of tunnel shotcrete liner. Deformation measurement of tunnel shotcrete liner is crucial to safety of tunnel construction and implementation of dynamic parameter design. This study recommends the light detection and ranging (LiDAR) technique. The main work of this paper is to determine whether the tunnel shotcrete lining has been deformed as a whole or locally by comparing the obtained multiepoch high-precision 3D point clouds. Furthermore, the authors propose a method for automatic sampling and deformation measurement of shotcrete liner using the multiepoch LiDAR point clouds. Compared with conventional deformation measurement methods (i.e., the total station and fiber optics) that capture deformation information from a limited number of monitoring points, LiDAR technology enables the high-precision, omnidirectional, and noncontact acquisition of spatial data within tunnels. This serves as a complementary and enhanced tool to tunnel safety monitoring techniques and methodologies. In addition, the adoption of the method proposed in this paper facilitates the quality check of shotcrete liner, including thickness assessment and smoothness detection. [ABSTRACT FROM AUTHOR]

AbstractVarious diseases such as lining defects, structural cracking, and water leakage are common in tunnel operation. Therefore, this paper considers the research object of the highway tunnel with typical lining defects, namely voids behind the lining. The stress distribution and crack distribution of the void behind the lining were analyzed by numerical simulation based on XFEM, and the cracking mode of the lining was studied by model test. According to the results:(1) The voids behind the tunnel lining change the stress distribution characteristics of the lining, and the lining structure within is stretched, significantly reducing the overall safety of the lining structure. (2) With the expansion of the void range (i.e. the void toroidal range and radial length), the lining area corresponding to the void is easy to crack, and the expansion of the void range leads to the increase of the crack area, which is also verified by the model test results. (3) A safety factor analyzes the bearing capacity of the lining structure. The safety factor of the lining area corresponding to the void is reduced, which is consistent with the results obtained by the XFEM method for the calculation of lining cracking, which proves that the XFEM method can be applied to the safety calculation of tunnel lining structure. [ABSTRACT FROM AUTHOR]

The pavement surface will inevitably develop cracks, subsidence, pits, ruts, and other defects due to the effects of traffic and the environment. In road engineering, vibration-based pavement condition monitoring has been widely adopted. Due to differences in vehicle dynamics, acquisition equipment, and road quality, the application of these techniques to the identification of minor pavement damage is limited. With the widespread adoption of the inertial navigation system (INS) in autonomous vehicles, INS-based pavement evaluation has emerged as a promising new technique. In this paper, the acceleration sensor, gyroscope, GPS, and other INS-integrated devices were used to collect data on vehicle attitude changes. For the detection of pavement apparent millimetre disease, a new method utilising INS data and machine learning was proposed. The method analyses the original vibration signal in time domain, determines the degree of sensing parameter influence, and extracts the index that can characterise the signal change. Multiple machine learning recognition models have been built to effectively classify road conditions, with the best-performing model achieving an F1 score of 99.61% and precision of 99.33%. The recall rate, accuracy rate, and F1 score of disease height classification were all above 0.7 on a macro and micro scale. [ABSTRACT FROM AUTHOR]

The pavement surface will inevitably develop cracks, subsidence, pits, ruts, and other defects due to the effects of traffic and the environment. In road engineering, vibration-based pavement condition monitoring has been widely adopted. Due to differences in vehicle dynamics, acquisition equipment, and road quality, the application of these techniques to the identification of minor pavement damage is limited. With the widespread adoption of the inertial navigation system (INS) in autonomous vehicles, INS-based pavement evaluation has emerged as a promising new technique. In this paper, the acceleration sensor, gyroscope, GPS, and other INS-integrated devices were used to collect data on vehicle attitude changes. For the detection of pavement apparent millimetre disease, a new method utilising INS data and machine learning was proposed. The method analyses the original vibration signal in time domain, determines the degree of sensing parameter influence, and extracts the index that can characterise the signal change. Multiple machine learning recognition models have been built to effectively classify road conditions, with the best-performing model achieving an F1 score of 99.61% and precision of 99.33%. The recall rate, accuracy rate, and F1 score of disease height classification were all above 0.7 on a macro and micro scale. [ABSTRACT FROM AUTHOR]

• The main innovative achievements are as follows: • A mechanical model of the tunnel lining was established to simulate cavities behind the tunnel lining and their effects on the cracking and stability of the lining structure. • Conducting mechanical model tests revealed the damage and failure characteristics of lining under different cavity conditions, as well as the variation law of bearing performance. • Through numerical simulation, the distribution characteristics of the safety factor of the lining section under three different spans and four different positions of voids were clarified, providing quantitative reference for tunnel safety evaluation. In highway tunnels, the presence of a cavity behind the lining can affect the contact between the lining and surrounding rock, leading to the concentration of pressure from the surrounding rock and acceleration of cracking in the tunnel structure. Thus, such cavities pose significant safety hazards. However, due to the complexity of the interaction between the cavity behind the lining and the surrounding rock, it is challenging to clarify the mechanism of damage caused by the cavity. In this study, we developed a mechanical model for testing the linings of highway tunnels and conducted numerical simulations of the bearing capacity of the lining in the presence of cavities. The results showed that the presence of a cavity behind the arch crown significantly affected the overall lining structure along with the stress state and deformation of the lining, leading to cracking at the arch crown of the lining. In contrast, the effects of single voids at the arch shoulder and arch waist were relatively small. When the cavity is located on one side of the lining, the effect of the deviation angle of the cavity center on the overall safety factor of the lining becomes more significant, with a maximum decrease of 62% in the safety factor. This study provides an essential reference for detecting and evaluating tunnels during operation when voids are present behind the lining. [ABSTRACT FROM AUTHOR]

The most common structural defect of a tunnel in the operation period is the cracking of concrete lining. The insufficient thickness of tunnel lining is one of the main reasons for its cracking. This study studied the cracking behavior of standard concrete specimens and the failure behavior of tunnel structures caused by insufficient lining thickness using Cohesive Zone Model (CZM). Firstly, zero-thickness cohesive elements were globally inserted between solid elements of the standard concrete specimen model, and the crack development process of different concrete grades was compared. On this basis, a three-dimensional numerical model of the tunnel in the operation period was established. The mechanism and characteristics of crack propagation under different lining thicknesses were discussed. In addition, the statistics of cracks were made to discuss the development rules of lining cracks quantitatively. The results show that the CZM can reasonably simulate the fracture behavior of concrete. With the increase in concrete strength grade, the number of cohesive damaged elements and crack area increases. The insufficient lining thickness changes the lining stress distribution characteristics, reduces the lining structure's overall safety, and leads to the cracking of the diseased area more easily. When surrounding rock does not contact the insufficient lining thickness, its influence on the structure is more evident than when surrounding rock fills the entire lining thickness. The number of cohesive damaged elements and the size of the crack area increases significantly. [ABSTRACT FROM AUTHOR]