5papers in this issue.
Recently, the consecutive shield tunnel boring machine (TBM) has gained attention for its potential to enhance TBM penetration rates. However, its development requires a thorough risk assessment due to the unconventional nature of its equipment and hydraulic systems, coupled with the absence of design or construction precedents. This study investigated the causal relationships between four accidents and eight relevant sources associated with the consecutive shield TBM. Subsequently, risk levels were determined based on expert surveys and a risk matrix technique. The findings highlighted significant impacts associated with collapses or surface settlements and the likelihood of causal combinations leading to misalignment. Specifically, this study emphasized the importance of proactive mitigation measures to address collapses or surface settlements caused by inadequate continuous tail void backfill or damaged thrust jacks. Furthermore, it is recommended to develop advanced non-destructive testing technology capable of comprehensive range detection across helical segments, to design a sequential thrust jack propulsion system, and to determine an optimal pedestal angle.
In this study, the Delphi method and AHP (analytic hierarchy process) were used to evaluate tunnel collapse risk from a comprehensive and multifaceted perspective. Influence factors were established through literature reviews, previous studies, and brainstorming sessions with expert groups, resulting in the construction of five mainclassification systems. A panel of 21 experts was formed, and three rounds of Delphi surveys were conducted to prevent errors and biases in the expert judgment process,thereby enhancing reliability. Ultimately, 14 influence factors were identified through CVR (content validity ratio) and COV (coefficient of variation) analyses of the experts’responses. Subsequently, the AHP method was applied to assess the relative importance of each influence factor and calculate the final composite weights. The timing ofsupport and reinforcement had the highest priority, followed by groundwater inflow, joint conditions, support pattern levels, and auxiliary methods. These findings helpidentify the key factors affecting tunnel collapse risk and provide a foundation for developing strategies to improve tunnel safety.
In general tunnel design and analysis, rock masses are often assumed to be isotropic. Under isotropic conditions, material properties are uniform in all directions, leading to a higher evaluation of tunnel stability. However, actual rock masses exhibit anisotropic characteristics due to discontinuities such as joints, bedding planes, and faults, which cause material properties to vary with direction. This anisotropy significantly affects the stress distribution during tunnel excavation, leading to non-uniform deformation and increased risk of damage. Therefore, thorough pre-analysis is essential. This study analyzes the displacement and stress changes occurring during tunnel excavation based on rock anisotropy. A three-dimensional numerical analysis was performed, selecting anisotropy index and dip angles as variables. The results showed that as the anisotropy index increased, the displacement in the tunnel increased, and stress concentration became more pronounced. The maximum displacement and shear stress were observed where the dip planes met the tunnel.
Steel pipe reinforced grouting method has been widely used to strengthen the crown of tunnel face and prevent groundwater leakage during tunnel excavation. Various injection procedures without sealing have recently been suggested to enhance efficiency. There are two representative injection methods. One is simultaneous injection in segmented batches, and the other is multiple injection using the external packer. The pros and cons of each method were discussed in terms of construction duration and equipment. However, it has yet to be discussed how the injection procedure affects the grout diffusion range in the ground. This study aims to evaluate the grout diffusion range quantitatively by considering the practical grouting sequences. The grout viscosity was measured by laboratory testing. Then, the numerical modeling was structured using the commercial computational fluid dynamics software. Finally, the grout diffusion range affected by the injection procedure and ground conditions was evaluated by performing the numerical parametric study. The results showed that the injection method highly affected the grout diffusion range, especially for inhomogeneous soil. Consequently, it is anticipated that the proper method of steel pipe reinforced grouting will be suggested.
The development of scanning technology is accelerating for safer and more efficient automated inspection than human-based inspection. Research on automatically detecting facility damage from images collected using computer vision technology is also increasing. The pixel size, quality, and quantity of an image can affect the performance of deep learning or image processing for automatic damage detection. This study is a basic to acquire high-quality raw image data and camera performance of a mobile tunnel scanning system for automatic detection of damage based on deep learning, and proposes a method to quantitatively evaluate image quality. A test chart was attached to a panel device capable of simulating a moving speed of 40 km/h, and an indoor test was performed using the international standard ISO 12233 method. Existing image quality evaluation methods were applied to evaluate the quality of images obtained in indoor experiments. It was determined that the shutter speed of the camera is closely related to the motion blur that occurs in the image. Modulation transfer function (MTF), one of the image quality evaluation method, can objectively evaluate image quality and was judged to be consistent with visual observation.