To enable early detection of microdamage in tunnel linings, this study presents a field-oriented, color-based extension of the contact sponge–fluorescence tracing technique for the qualitative identification of shallow microdamage in reinforced concrete cover zones. Unlike the previous fluorescence-enhanced visualization of individual microcracks, the present strategy uses humidity-dependent fluorescence-color differences generated by spatial variations in moisture absorption and evaporation to distinguish relatively high- and low-damage regions. Under 365 nm UV illumination, these regions can be differentiated by their green and yellow-green fluorescence responses, respectively, without fluorescence microscopy or mandatory image post-processing. This mechanism may be advantageous under relatively dry inspection conditions, such as those potentially encountered in some mountain tunnels. Under the dry laboratory conditions examined in this study, readable contrast was obtained within 3–5 min. Under outdoor conditions, the development time was more variable and depended strongly on ambient humidity. The feasibility of the approach is examined through laboratory four-point bending tests, linear-elastic stress-state analysis, and a proof-of-concept demonstration on a building exterior wall. The latter is intended to assess operational feasibility outside the laboratory and should not be interpreted as validation on an actual tunnel lining.
Railway transport is emerging as a flexible solution for the distribution of liquid hydrogen (LH2). However, LH2 might cause safety concerns in railway tunnels, especially when passenger and freight trains are allowed to transit simultaneously in the same tube. Since the issue is relevant, 3D computational fluid dynamics models were developed to simulate the hydrogen dispersion and explosion in a long single bore, double-track railway tunnel. The scenario considers a freight train transporting LH2 experiencing a loss of containment and to stop in a 5 km long tunnel, while a passenger train queues and stops upstream on the same rail track at different distances from the freight one. The natural and mechanical ventilation conditions were investigated. A probabilistic assessment based on probit models was then performed to estimate the consequences for the passengers. The results indicate that a fatality probability less than 1 % might be achieved when the passenger train stopped at a safety distance from the freight train ≥ 2000 m in the case of the tunnel naturally ventilated, while a shorter distance (i.e., ≥ 1700 m) might be sufficient when the mechanical ventilation, which pushed the airflow in the same travel direction of the two trains, was considered. In the case in which the two trains moved on opposite tracks, the safety distances between the front of the passenger train and the point of LH2 release were found to be ≥ 1600 m or ≥ 2100 m when the tunnel tube was naturally or mechanically ventilated, respectively. In this last case of the mechanically ventilated tunnel, however, the possibility of reversing the fan direction is also recommended as a mitigation strategy.
Accurate prediction of rockburst intensity levels is critical for the safety of deep underground engineering construction. This paper develops a Fuzzy-Regularized Graph Convolutional Network (FR-GCN) for long-term rockburst intensity assessment at the design or pre-construction stage. First, by integrating feature similarity and the correlation of engineering criteria, a multi-branch GCN structure was employed to effectively capture the physical characteristics of nodes, local neighborhood relationships, and topology patterns dominated by engineering criteria. To overcome the information loss and instability caused by hard threshold division, a fuzzy regularization mechanism was introduced, mapping discrete criterion features to continuous membership degree vectors and enhancing prediction consistency through a smoothing regularization term. Subsequently, the proposed model was validated using 197 real underground engineering cases collected globally. The five-fold cross-validation yields an average accuracy of 94.42%, demonstrating the superior predictive performance of the FR-GCN model. Further comparisons with traditional empirical criteria and existing machine learning models confirm the model’s accuracy and stability. Additionally, preliminary engineering verification using 15 samples from two gold mines achieved 100% classification accuracy, providing preliminary evidence of the model’s engineering application potential. Finally, an ablation study was conducted to analyze the contribution of each component to the model performance, indicating that the fuzzy regularization mechanism contributes to improving the model’s stability and accuracy.
With the increasing application of prefabricated structures in underground utility tunnels, developing reliable and construction-friendly connections has become critical for seismic safety. This study investigates the out-of-plane seismic performance of precast composite sidewalls with spiral stirrup sleeve grouted lap-splice connections at the bottom joint. Full-scale cyclic tests were conducted on three precast composite sidewalls with axial compression ratios of 0.05, 0.10, and 0.15, and the results were compared with those of a monolithic cast-in-place sidewall. It was found that the failure modes of the precast composite sidewall and the cast-in-place sidewall were different. The precast and cast-in-place sidewalls exhibited different damage patterns because the horizontal joint altered the stress transfer and damage development in the connection region. Nevertheless, under the same axial compression ratio, the precast composite sidewall exhibited seismic performance comparable to that of the cast-in-place specimen in terms of load-carrying capacity, ductility, stiffness, and energy dissipation. Increasing the axial compression ratio reduced concrete spalling and horizontal joint opening while significantly enhancing the load-carrying capacity. Compared with the specimen with an axial compression ratio of 0.05, the peak loads of the specimens with axial compression ratios of 0.10 and 0.15 increased by 18.42% and 29.60%, and the cumulative energy dissipation increased by 3.14% and 10.55%, respectively, whereas the ductility factors decreased by 0.37% and 15.02%. This indicates that increasing axial compression enhances strength by improving the resistance of the compression zone but reduces deformation capacity at higher compression levels. A tri-linear restoring-force model was further established based on the characteristic response points, and the predicted backbone and hysteresis curves agreed well with the experimental results. The proposed connection and restoring-force model provide experimental evidence and a simplified analytical approach for the seismic design and nonlinear analysis of precast composite sidewalls in underground utility tunnels.
Shield tunnel excavation can induce ground loss and lateral soil movement, which may cause lateral deformation and additional internal forces in adjacent pile groups. This study proposes an analytical solution for the lateral response of an adjacent two-pile group induced by shield tunnel excavation while considering the shielding effect between piles. A lateral equilibrium equation for a single pile is first established based on the Pasternak shear-layer foundation model. The additional lateral load induced by tunnel excavation is then formulated using the Sagaseta ground loss solution. The model is extended to a two-pile group by introducing an exponential attenuation coefficient to describe the shielding effect of Pile 1 on Pile 2. Closed-form solutions for the lateral deformation of both piles are derived, and the corresponding bending moment and shear force are obtained from displacement derivatives. The proposed solution is validated against centrifuge test results and compared with a Winkler-based solution. The results show that the Pasternak-based model better captures the shear transfer effect of the surrounding soil and provides predictions that agree better with centrifuge test results. Parametric analyses indicate that the lateral deformation of the two piles generally exhibits a bulging profile, with the peak response occurring near the tunnel axis depth. Pile 1 shows larger lateral deformation, bending moment, and shear force than Pile 2, although both piles exhibit similar distribution patterns. Among the investigated factors, the geometric ground loss associated with the excavation radius produces the largest variation in pile response, followed by soil type and tunnel–pile spacing, whereas tunnel burial depth mainly controls the location of the peak response along the pile shaft.
