四川建筑职业技术学院

Settlement prediction for high-fill railway embankments is challenged by monitoring noise and stage-dependent deformation across construction and operation. This paper presents a physics-guided framework integrating multivariate construction information with settlement monitoring data. Monitoring sequences are denoised by a hybrid autoencoder with a signal-to-noise-ratio-based cleaning mechanism. A temporal graph convolutional neural network embeds a modified layer-wise summation formulation to guide variable interactions and settlement prediction. On the analysed dataset, the model achieved a coefficient of determination of 0.99 with the selected parameters. Compared with Informer, MTGNN, and TQNet, it achieved the lowest test-set mean squared error, averaged over ten random seeds, under both working conditions. Ablation experiments supported the effectiveness of the hybrid architecture. Component analyses indicated that the physics-guided module estimated settlement trends, while the data-driven module supplied local residual corrections. It provides a feasible framework for handling complex settlement-pattern transitions that are difficult to capture using conventional approaches.

Structural discontinuities fundamentally control rock mass stability, failure, and movement. This study presents an integrated framework combining three-dimensional (3D) laser scanning-based discontinuity identification with 3D discontinuous deformation analysis (DDA) for quantitative rockfall modeling. The method was applied to a high, steep rock slope near the Dongjiuqu Bridge, Xizang, China. High-resolution point cloud data (2,237,499 points) were acquired using an ILRIS-3D terrestrial laser scanner. After denoising, simplification, and triangulation in PolyWorks, 12 dominant discontinuity sets were identified, with dip directions of 80.958 degrees-187.449 degrees and dip angles of 23.421 degrees-73.065 degrees, demonstrating the proposed workflow's efficiency and accuracy in characterizing complex structural networks. Using the extracted discontinuity data, a 3D DDA numerical model was established to simulate rockfall initiation, movement, and deposition. The failure evolution of the unstable rock mass was divided into four stages: initial sliding and crack formation, collapse and impact, accelerated rolling with high-velocity collision with the riverbed, and postfailure accumulation and stabilization. Simulations captured key kinematic responses, including a velocity increase of block #6 from 0.77 to 1.48 m/s during slope impact and rebound velocity of 1.01 m/s for block #8 following riverbed collision, reflecting complex energy dissipation through block-slope and interblock interactions. The results demonstrate that integrating 3D laser scanning-derived discontinuity data into 3D DDA modeling markedly enhances the realism and reliability of rockfall simulations. The proposed "scanning-identification-simulation" framework provides an effective noncontact tool for rockfall hazard assessment and mitigation design in mountainous regions.

Nigeria faces critical socio-economic challenges due to its dependence on fossil fuels and rapid population growth, leading to economic instability, environmental harm, health crises, and political unrest. These issues have widened the energy demand-supply gap, necessitating a shift to clean energy. Photovoltaic (PV) technology shows significant promises for addressing this gap and achieving Sustainable Development Goal-7 (SDG-7). However, localized challenges in Nigeria hinder PV adoption beyond global efficiency concerns. This study presents a decision methodology in Spherical Fuzzy (SF) environment to address uncertainty and minimize bias in evaluating solar energy (SE) challenges and policies. The approach integrates SF-Stepwise Weight Assessment Ratio Analysis (SWARA), SF-Criteria Importance Through Inter-criteria Correlation (CRITIC), and SF-COmbinative Distance-based Assessment (CODAS) techniques to assess challenges and rank policy alternatives. Based on expert opinions and literature, 12 challenges were identified and categorized, with subjective and objective weights determined using SF-SWARA and SF-CRITIC. The SF-CODAS ranked eight alternative policies to enhance SE potential and penetration. Key challenges include energy company debt, high generation costs, and affordability issues. Prioritized policies involve Research & Development supplementary funding, preventing sub-standard renewable products, and enabling research on PV maintenance. Sensitivity analysis confirms the robustness of the proposed methodology, offering structured solutions to Nigeria's energy challenges.

This study investigates the seismic performance of damaged RC frame beam-column joints reinforced with external angle steel and three different secondary reinforcement methods (thin-walled steel plate shear walls, diagonal braces, and V-shaped buckling-restrained braces) through low-cycle cyclic loading tests. Based on load-displacement hysteresis curves, the energy dissipation capacity, stiffness degradation, ductility, and failure mechanisms of the joints are systematically analyzed. Test results indicate that all reinforced specimens achieved the desired shift in failure mode from "strong beam-weak column" to "strong column-weak beam." Among them, specimens reinforced with V-shaped buckling-restrained braces (RC-4) exhibit the best performance. Their ultimate load capacity increases by 455.0% compared to unreinforced specimens, cumulative energy dissipation rises approximately 20.2 times, displacement ductility coefficient reaches 2.88, and stiffness retention rate remains at 77.9% even after cracking. This reinforcement method, employing V-shaped buckling-restrained braces, possesses multiple energy dissipation capabilities and significantly delays the progression of node damage. It is suitable for seismic retrofitting in high-intensity seismic zones and provides experimental evidence and design references for enhancing the seismic performance of existing RC frames.

The construction of transportation infrastructure in China is advancing into the western plateau, a region where schistose basalt is most concentrated and typifies its distribution. Research on the strength characteristics and failure mechanisms of schistose basalt under high-ground stress remains limited. This study employs rock compression tests and three-dimensional discrete element simulations to investigate the effects of stress conditions and schistosity dip angle on the compressive strength, failure modes, and anisotropic mechanical properties of schistose basalt at both macroscopic and microscopic levels. The results indicate that the compressive strength of schistose basalt increases with confining pressure. The compressive strength exhibits a U-shaped distribution as the schistosity dip angle changes. The difference in compressive strength caused by the change of schistosity dip angle is as high as 75.45 %. When the schistosity dip angle is between 0 degrees and 30 degrees, the failure mode is shear failure through the rock matrix. At dip angles between 45 degrees and 90 degrees, the failure mode under low confining pressure is slip-induced splitting along the schistosity planes, while under high confining pressure, shear failure through the rock matrix occurs. Additionally, the stress conditions significantly influence the anisotropic mechanical behavior of the rock. At low stress levels, the rock's anisotropy is highly pronounced, whereas increasing stress leads to a significant reduction.