Cracks in tunnel linings induce bearing capacity degradation, making the rapid prediction of the damage ratio critical for structural safety assessment. However, quantifying the intrinsic mechanical performance solely from apparent surface cracks remains a challenge. To bridge this gap, this study proposes a physics-informed deep learning framework that maps visual crack features directly to the bearing capacity damage ratio. First, a high-fidelity numerical simulation system is established using the Pseudo-Crack Method implemented on the multi-scale thermodynamic platform. This approach avoids the mesh dependency of traditional fracture mechanics and is rigorously validated against existing physical model tests of lining structures in terms of crack morphology and load-displacement responses. Subsequently, a standardized synthetic dataset is constructed by distilling topological features from in-service hydraulic tunnels and applying a color-coded width visualization strategy. By conducting comparative training across eight state-of-the-art deep learning architectures, the ConvNeXtV1 model is identified as the optimal regressor, achieving a coefficient of determination of 0.89 on the test set. The proposed method effectively acts as a real-time "digital surrogate" for time-consuming non-linear finite element analysis, providing a mechanism-based, efficient solution for structural health monitoring of tunnel infrastructure.

Reinforced concrete (RC) structures are among the most prevalent in the construction industry. However, various in-service conditions such as loading, environmental exposure, and construction practices can lead to the formation of concrete cracks. In extreme cases, these cracks may propagate through the cross-section of structural members, creating section pre-cracks. This study examines the influence of section pre-cracks on the shear failure behavior of RC deep beams (with a shear span-to-depth ratio of 1.57) through three-point bend-loading tests and 3D RBSM analysis. The primary experimental variables include the number of pre-cracks (one or two) and their width (0.5 mm or 1.0 mm). The findings reveal that pre-cracks significantly reduce the initial stiffness and shear strength of deep beams, primarily by disrupting the transmission of axial compressive stress in the concrete, thereby diminishing the contribution of arch action to shear strength. Furthermore, it is observed that the greater the total width and number of pre-cracks, the more significant the reduction in shear strength. In addition, combining both experimental tests and numerical simulations, a total of 48 deep beams were subjected to shear failure tests. Based on the shear strength data, two degradation models for shear strength (one representing the average trend and the other a conservative lower-bound envelope model) were developed in relation to the total crack width.

Assessing the risk of alkali-silica reaction (ASR) in large-scale concrete structures remains a critical challenge, particularly due to the scarcity of field-based data and the long timescales involved. This study proposes a methodology to evaluate ASR risk in concrete containing slowly dissolving aggregates. The approach consists of three steps: (i) identifying material properties such as the dissolution rate and chemical composition of the dissolved phases; (ii) determining the critical reaction degree at which amorphous silica forms, using equilibrium calculations based on GEMS thermodynamic simulations; and (iii) estimating the time required to reach this threshold by solving coupled equations for moisture transport and aggregate dissolution under real structural conditions. The methodology is demonstrated using in-situ data from the aged concrete walls of the Hamaoka nuclear power plant. Key factors that mitigate ASR risk are identified, including low dissolution rates, water depletion over time, and the presence of stabilizing species such as Al₂O₃ and MgO in the dissolved phase. While developed for a specific case, the proposed approach provides an adaptable framework for rational ASR risk evaluation in existing and future concrete structures.

In this study, 1 mm-thick disk samples of hardened cement paste were carbonated under 60% relative humidity (RH) and a 1.0% CO₂ concentration. Uncarbonated and carbonated samples were impregnated with 2-propanol (IPA) and analyzed by ¹H Nuclear Magnetic Resonance (NMR) relaxometry to quantify the full-scale microstructure changes in hardened cement paste during carbonation process. Pore structure changes during drying and carbonation were discussed based on the mineral composition changes, as determined by X-ray diffraction/Rietveld analysis, and volume changes as measured by length and volume change measurements. Furthermore, this water and IPA ¹H NMR technique enabled the evaluation of volume fraction changes in hardened cement pastes during drying and carbonation, combined with changes in pore structure. In the drying process under 60% RH, gel pore water evaporated, increasing the coarse pore volume, and drying shrinkage was induced. During the carbonation process, calcium carbonates precipitated in coarse pores, thereby increasing the solid volume of cement minerals and decreasing the total pore volume. As C-(A)-S-H gel was decomposed due to carbonation, the volume fraction of C-(A)-S-H and silica gel agglomeration decreased, resulting in the macroscopic carbonation shrinkage in hardened cement paste.

Tunnels that cross fault crush zones are subject to local deformation along these zones during earthquakes. Because the tunnel axis and the fault plane generally intersect in a three-dimensional manner, evaluating structural performance by using three-dimensional FEM is reasonable, and to this end selection of an appropriate damage indicator is required. To establish a damage evaluation method for the safety of tunnels subjected to local deformation, three-dimensional FEM analysis was carried out on previous loading experiments, the failure modes were analyzed, and the applicability of several damage evaluation indicators was verified. As a result, the damage to the tunnel in the model experiments was broadly classified into in-plane shear in the longitudinal section and out-of-plane shear in the longitudinal or transverse section. Performance evaluation using compressive damage indicators including minimum principal strain when the limit state of a tunnel is defined as the point at which the resistance to slippage in the crush zone is maximum was found to be feasible. Moreover, the results of the sensitivity analysis showed that evaluation based on the minimum principal strain is broadly applicable. Additionally, a limit value considering element size was proposed.