Search Results (402)

Roof stability plays a crucial role in maintaining the overall stability of surrounding rocks to ensure safety of tunnel construction and operation. In this work, tension cut-off (TC) technique is introduced to modify the Hoek–Brown (HB) criterion to describe the tensile failure of rock strata. Thereafter, stability analysis of anchor bolt-reinforced tunnel roofs in rock strata subjected to a hybrid tensile-shear fracture is performed. The work balance equation is established by equating the external work rates of the falling block and the anchor bolts to the internal energy dissipation rate. Two stability indicators, that is the stability number (N) and the factor of safety (FoS) are proposed to quantitatively analyze the stability of tunnel roofs. Optimization algorithms combining genetic algorithm and particle swarm optimization are programmed to capture the optimal upper bound solutions. The influences of TC, strength criterion parameters, and anchor bolt-reinforcement strength on roof stability are explored in this work. It was found that increasing the anchor tension T improves the FoS of reinforced tunnel roofs, with an increase of up to 68% observed for rectangular tunnel roofs under the selected representative case, while the improvement is relatively less pronounced for circular tunnel roofs. Regarding anchor support, as ξ increases, the N for rectangular tunnels nearly doubles. This work provides a theoretical basis for preliminary designing of tunnels in reinforced rock strata. Full article

Strong seismic waves induced by drill-and-blast tunnel excavation threaten the structural integrity of adjacent existing tunnels; however, prevailing safety evaluation methods mostly simplify tunnel linings as homogeneous continua, failing to accurately characterize the meso-scale uncoordinated dynamic response between rebar and concrete under blast impact. To fill this research gap, a 1:1 full-scale separated three-dimensional finite element model of reinforced concrete composite linings was established using the LS-DYNA explicit dynamic numerical algorithm, which was verified by previous 1:25 scaled physical model tests. This study systematically quantifies the spatiotemporal evolution of lining dynamic responses under two core parameters—tunnel clear distance (10 m to 60 m) and single-delay detonating charge quantity (10.8 kg to 28.8 kg)—to validate the response differences between materials. It is abstracted that the structural failure is dominated by axial tensile stress, with the embedded rebar being significantly more sensitive to internal stress surges (reaching 3.5 times the peak stress of concrete), while the concrete is more sensitive to particle vibration velocity amplification, a mismatch that is particularly acute within a 30 m clear distance. This study highlights the severe interfacial stress gradient between rebar and concrete, providing an indirect but critical indicator for the potential risk of interface debonding under adjacent blasting, and offers a quantitative theoretical basis for extending safety assessments from macro-surface vibration control to refined meso-scale internal stress monitoring. Full article

Sulfate attack is a major cause of deterioration in tunnel lining concrete under aggressive underground conditions. This study investigates the sulfate resistance of fiber-reinforced ferroaluminate cement concrete incorporating steel slag powder through combined experimental and numerical approaches. Specimens with different fiber contents (0, 0.2%, and 0.4%) were subjected to dry–wet cycles in a 5% sodium sulfate solution. The results show that fiber incorporation significantly enhances sulfate resistance, with the optimal performance achieved at 0.2% fiber content. Compared with ordinary Portland cement concrete, ferroaluminate cement-based concrete exhibits improved durability, including lower mass variation, reduced strength degradation, and more stable dynamic elastic modulus. Microstructural analyses indicate that hydration products refine the pore structure, while fibers effectively inhibit crack propagation and expansion damage. Numerical simulation of tunnel lining structures further demonstrates that the optimized material reduces stress concentration, displacement, and crack development. Overall, the proposed material shows superior performance and promising application potential for tunnel linings in sulfate-rich environments. Full article

In pursuit of a composite coating for tunnel boring machine (TBM) disc cutters that offers both high wear resistance and self-lubricating functionality, we fabricated Fe-based composite coatings reinforced with WC and MoS₂ through laser cladding. Seven coating compositions with systematically tailored MoS₂ contents were prepared to investigate the concentration-dependent effects of MoS₂ on microstructural evolution and tribological properties, and to evaluate their performance under various rock-contact conditions. XPS results reveal that MoS₂ decomposed during laser cladding, leading to the in situ formation of metal sulfides in the Fe-based matrix. These sulfides, characterized by low shear strength, readily form a continuous and stable lubricating tribofilm at the hob–rock interface. The tribofilm effectively lowers the coefficient of friction (COF), curtails friction-induced energy dissipation and surface degradation, and ultimately enhances the wear resistance of the disc cutter. Simultaneously, the rapid non-equilibrium solidification inherent in laser cladding stabilizes metastable phases, which refine the microstructure, improve densification, and bolster phase stability. Among the tested compositions, the coating containing 4 wt.% MoS₂ exhibited the most favorable dry-sliding tribological performance, as evidenced by an average coefficient of friction of 0.409, a hardness of 749.5 HV1, and consistently low wear mass losses below 2.1 × 10⁻³ g under different rock-contact conditions. Mechanistically, XRD and SEM analyses further attributed the superior performance of the 4 wt.% MoS₂ coating to concurrent strengthening mechanisms: grain refinement, dispersion strengthening from uniformly distributed second-phase particles, and increased dislocation density. Collectively, these effects substantially improve the wear resistance of the disc cutter, thereby extending its durability and service life under complex operating conditions. Full article

This study aims to explore a leakage-aware and explainable machine learning framework for predicting tunnel water inrush quantity (WIQ) under small-sample and high-heterogeneity geological conditions. A project-level dataset was compiled at a fixed spatial granularity of 30 m per excavation segment by integrating forward prospecting outputs, construction-face observations, and geological reports, and six hydrogeological–structural indicators were used to predict the water inflow rate in cubic meters per hour. To overcome data scarcity and improve generalization, a tabular generative adversarial network (GAN) was introduced to augment the training distribution while preserving marginal statistics and inter-variable dependence, and a swarm-intelligence optimizer was employed to tune a Categorical Boosting (CatBoost) regressor for stable performance. In addition, six mainstream tree-based learners were benchmarked under a unified protocol, and model transparency was ensured through a multi-level interpretability suite combining SHapley Additive exPlanations (SHAP) attribution, partial dependence with individual conditional expectation (ICE) diagnostics, and interaction surfaces. Results show that, under the present fixed split, training-set augmentation was associated with improved performance for the evaluated baseline learners, and the proposed hybrid model achieved encouraging hold-out accuracy. However, because the dataset contains only 55 real samples and the test set contains only 11 real samples, the reported performance should be interpreted as an initial project-specific indication rather than robust evidence of generalizable reliability. Interpretability analyses further identify lithologic and reflector-related factors as dominant drivers, and reveal nonlinear response patterns and interaction-sensitive high-risk regions. Overall, the proposed framework shows potential to improve predictive performance and engineering interpretability for the studied project, and may provide a useful reference for drainage and reinforcement planning. Further confirmation through repeated data splitting, additional samples, and external validation is still needed before broader application. Full article

Stray-current corrosion from DC-electrified railways drives premature failure of buried metallic infrastructure (pipelines, foundations, tunnel reinforcement), causing resource waste, repair-driven carbon emissions and service disruptions that undermine the sustainability of urban transit corridors. Conventional impressed-current cathodic protection (ICCP) design relies on uniform-anode rules of thumb or closed commercial codes that cannot quantify the trade-off between protection uniformity, energy use and hardware cost. We present an open MATLAB framework that couples a custom 3D finite element method (FEM) solver with multi-objective particle swarm optimisation (MOPSO) and minimises three competing objectives simultaneously: total impressed current, RMS deviation from the protection target, and number of active anodes. A laboratory-calibrated coupling factor ($\mathrm{CF}=1.98$, consistent with the image-method prediction of 2 for a highly conductive pipe inclusion) absorbs the pipe–soil interface kinetics into a single direct FEM solve, and a pre-computed Green’s-function basis accelerates each MOPSO evaluation by more than two orders of magnitude. The solver is validated against an instrumented prototype with RMSE $=14.9$ mV across ten Cu/CuSO₄ saturated reference electrode (CSE) measurements, and applied to a 500 m DC traction line. At an identical total current of 20.30 A across five anodes, the optimised design achieves an RMSE of 86.6 mV against the $-850$ mV NACE target, whereas a conventional uniform layout produces severe over-protection (RMSE $=1107$ mV)—a twelve-fold reduction. The framework is recommended as a transparent, reproducible engineering tool that simultaneously extends pipeline service life and reduces rectifier energy demand, supporting UN Sustainable Development Goals 9 and 11 for sustainable urban-rail infrastructure. Full article

This paper focuses on developing reinforced self-healing supramolecular resins that meet both functional and structural needs for industrial use. The formulated advanced nanocomposites are made from compounds that allow for reversible self-healing interactions. The self-healing molecules bond with the toughened epoxy matrix using hydrogen bonding. To enhance the epoxy’s typical insulating properties, electrically conductive carbon nanotubes (CNTs) were added to achieve an electrical percolation threshold (EPT) with a low amount of nanofiller. This study found that self-healing efficiency can reach nearly 99%. The addition of healing compounds significantly raises the glass transition temperature to over 200 °C. Tunneling Atomic Force Microscopy (TUNA), which is an innovative tool for correlating local topography with electrical properties, reveals the structural properties and compatibility of these materials, mapping conductive pathways at the micro- and nanoscale. Full article

Carbon/polymer composites are increasingly designed as microstructure-engineered multifunctional materials that combine mechanical reinforcement with electrical/thermal transport, electromagnetic interference (EMI) shielding, and sensing. Performance is governed less by filler fraction than by the coupled control of network topology, junction resistance, and interfacial thermal boundary resistance under processing-induced shear and thermal histories. Electrical response follows percolation combined with tunneling/contact-controlled junctions, producing nonlinear σ(φ) behavior and high piezoresistive sensitivity near the percolation threshold. In contrast, thermal transport is commonly limited by Kapitza resistance and filler–filler junction resistance, restricting exploitation of the intrinsic conductivity of CNTs and graphene. Recent advances emphasize hybrid and 3D carbon architectures that densify connectivity, reduce junction losses, and enable programmable anisotropy via scalable routes such as masterbatch extrusion and additive manufacturing. However, translation remains constrained by dispersion-driven variability, transport–toughness trade-offs, and incomplete durability assessment under cycling, humidity, and reprocessing. This review consolidates mechanistic structure–processing–property relationships and provides application-driven design rules for sensors, EMI shielding, and thermal management. Full article

The tumor microenvironment (TME) is a highly adaptive and heterogeneous niche in which cancer stem cells (CSCs) promote immune evasion, metastatic dissemination, and therapy resistance. Among the mechanisms that support this phenotype, mitochondrial hijacking has emerged as a central strategy through which CSCs reprogram immune and stromal cells to favor tumor progression. This review synthesizes current evidence on how CSCs exploit mitochondrial transfer, particularly via tunneling nanotubes (TNTs) and extracellular vesicles (EVs), to impair antitumor immunity and remodel the metastatic niche. CSCs display marked metabolic plasticity, shifting between glycolysis and oxidative phosphorylation (OXPHOS) in response to environmental stress. They exploit this adaptability by transferring mitochondria and mitochondrial components to recipient cells, including tumor-associated macrophages (TAMs) and cytotoxic T cells, thereby disrupting ATP production, increasing oxidative stress, and skewing immune polarization. This mitochondrial hijacking contributes to an immunosuppressive milieu, stabilizes HIF-1α, and enhances PD-L1 expression, ultimately weakening T-cell activity and reinforcing CSC survival. EVs add another layer of regulation by transporting bioactive cargo, including oncogenic microRNAs (miRNAs) and mitomiRs such as miR-21, miR-210, and miR-34a. These molecules modulate mitochondrial gene expression, reshape immune signaling, and reinforce CSC phenotypes through autocrine and paracrine loops. Single-cell and spatial transcriptomic approaches have further revealed metabolic heterogeneity within CSC–immune synapses, identifying “metabolic hotspots” associated with profound immune dysfunction. Therapeutic strategies targeting OXPHOS, EV biogenesis, and miRNA activity are therefore being explored. In parallel, mitochondria-associated proteins such as TSGA10 may also contribute to CSC-driven immunometabolism regulation and deserve further investigation. Targeting downstream heterogeneity is like cutting the branches of a weed. Targeting the upstream mechanisms of mitochondrial hijacking and miRNA crosstalk aims to destroy the root (CSC plasticity) that generates the heterogeneity and drives therapy resistance in the first place. This review highlights mitochondrial hijacking and miRNA-mediated reprogramming as central determinants of CSC-driven immune escape and proposes a framework for precision interventions targeting CSC–immune interactions in metastatic cancer. Full article

This study presents the aerodynamic design of the wing system for a fixed-wing vertical take-off and landing (VTOL) unmanned aerial vehicle (UAV), developed to enhance energy efficiency and operational performance in agricultural applications. The design responds to the limitations of conventional multirotor drones, which are limited by low endurance and high energy consumption, and crop-dusting aircraft, which are unsuitable for irregular terrain such as that found in Chihuahua, Mexico. A comprehensive methodology was adopted, integrating the selection of airfoils optimized for low-Reynolds-number conditions, computational fluid dynamics (CFD) simulations, winglet incorporation, and experimental validation through wind tunnel testing. The SELIG 1223 airfoil was selected for its superior aerodynamic efficiency, demonstrating a potential reduction of up to 55% in power requirements compared to multirotor configurations. Despite some variability in experimental results, the proposed design demonstrated consistent feasibility and reliability. Future work will focus on field validation and geometric adaptation to diverse operational scenarios, reinforcing its applicability across heterogeneous agricultural landscapes. Full article

To improve construction efficiency for large-section tunnels in sandstone–mudstone strata, this study investigates the applicability of the two-bench method and the three-bench method for grade IV and grade V surrounding rock, respectively. Based on FLAC3D, numerical simulations of excavation and support for the two benching methods were conducted to analyze deformation responses, including ground settlement, crown settlement, haunch convergence, floor uplift, and face extrusion. The simulation results were then compared and validated against field monitoring data to evaluate the applicability and feasibility of the construction methods. The results show that, for grade IV surrounding rock excavated using the two-bench method, crown settlement, floor uplift, and horizontal convergence converge and stabilize on days 17, 15, and 25, with stable values of 14.0 mm, 10.3 mm, and 13.2 mm, respectively. For grade V surrounding rock excavated using the three-bench method, these indices stabilize on days 24, 22, and 32, with stable values of 26.3 mm, 20.3 mm, and 20.8 mm, respectively. The surrounding rock pressures at the crown and spandrel gradually attenuate after excavation and stabilize at 1–4 MPa after approximately 20–26 days, whereas stress release at the haunch lasts longer and the stabilized stress level remains higher. Meanwhile, the anchor bolt axial force at the haunch is significantly greater than that at the spandrel, indicating that the haunch is a critical zone for support load-bearing and deformation control. The benching method can effectively control surrounding rock deformation under grade IV and V surrounding rock conditions in sandstone–mudstone strata; however, in engineering practice, the haunch should be treated as a key monitoring target, and targeted support and reinforcement measures should be implemented. Full article

To investigate the bond performance between reinforcement and tunnel lining concrete under freeze–thaw cycles in plateau regions, pull-out tests were conducted on secondary-lining-reinforced concrete specimens subjected to different numbers of freeze–thaw cycles. The variations in the fundamental properties of the lining concrete, as well as the bond stress and maximum slip between the reinforcement and the concrete, were examined. The results indicate that, with an increasing number of freeze–thaw cycles, the mass of the lining concrete first increases and then decreases, while the compressive strength and splitting strength gradually decrease. The bond stress between the reinforcement and concrete shows a decreasing trend, whereas the maximum slip exhibits an increasing trend. Furthermore, a finite element model of the reinforced concrete pull-out specimen was established using ABAQUS software to simulate the bond performance under different freeze–thaw cycles. The comparison between experimental and simulated results validates the rationality of the finite element model. This study provides a reference for understanding the bond–slip behavior of tunnel lining reinforced concrete subjected to freeze–thaw environments in cold plateau regions. Full article

This study aims to develop a green composite cementitious material (GCCM) by partially replacing cement with multiple industrial solid wastes and to further enhance its toughness by incorporating basalt fibers (BF) for the effective disposal of shield tunnel spoil (STS). The deterioration behavior of STS synergistically improved by GCCM and BF was systematically investigated under drying–wetting (D-W) cycles using unconfined compressive strength (UCS) tests, mass loss and P-wave velocity measurements, as well as industrial computed tomography (CT) and scanning electron microscopy (SEM). The results show that BF significantly improves the early-age strength and deformation toughness of STS, with an optimal UCS increase of about 13% at 0.45% BF. Although the mechanical properties of the specimens deteriorated with an increasing number of D-W cycles, the “bridging effect” of BF effectively inhibited the propagation and coalescence of cracks. Quantitative CT analysis further revealed that the addition of 1.00% BF reduced the pore volume (V_k) and crack volume (V_l) by 54.3% and 63.2%, respectively, after eight D-W cycles. The damage mechanism is primarily attributed to the loss of cementitious materials caused by water migration and the swelling–shrinkage stress of clay minerals. The three-dimensional (3D) network structure formed by BF, through its pull-out energy dissipation mechanism, effectively maintained the macro- and microstructural integrity of the material. This study highlights the novelty of combining GCCM with BF to enhance the long-term durability of STS, providing a theoretical basis and technical support for its green disposal and engineering application in complex environments. Full article

The durability and serviceability of steel-fiber-reinforced concrete (SFRC) tunnel linings in cold regions are significantly challenged by repeated freeze–thaw actions, making the accurate prediction of frost resistance a critical engineering problem. Although extensive research has been conducted on the freeze–thaw characteristics of concrete, the existing empirical and mechanism-based models remain limited in capturing the complex nonlinear interactions among mixture proportions, steel fiber characteristics, and environmental conditions. Therefore, a data-driven prediction framework based on machine learning was developed in this study. A database containing 277 groups of standardized SFRC freeze–thaw test results was established, incorporating key variables including mixture design parameters, fiber properties, and freeze–thaw cycle conditions. Four machine-learning models, namely, support vector regression, back-propagation neural network, gradient boosting, and extreme gradient boosting (XGB), were constructed and systematically compared. Model accuracy was assessed using MAE, MAPE, MSE, RMSE, and R². The results demonstrate that all models can reflect the nonlinear relationship between the input variables and mass loss rate, while the XGB model exhibits superior predictive performance with a testing R² of 0.91, representing an improvement of approximately 3–28% compared with other models. Meanwhile, the prediction errors are reduced significantly, with RMSE and MAE decreased by about 19–58% and 22–65%, respectively. The proposed approach provides an improved and reliable tool for predicting frost resistance and supports the durability design and optimization of SFRC tunnel linings in severe cold-region environments. Full article

To study the influence of polyoxymethylene (POM) fibers on the mechanical properties of shotcrete for tunnel support, this research conducted four-point bending tests on concrete with different POM fiber dosages (0, 5, 7, and 9 kg/m³) and lengths (30 mm, 36 mm, and 42 mm). The mechanical properties are analyzed in terms of failure modes, flexural strength, and the toughness index. The results show that, with the increase fiber length and dosage, the incorporation of POM fibers can enhance the toughness of concrete and significantly improve the flexural performance of shotcrete, with the peak flexural strength increasing by 15.31% to 89.46%. Additionally, through scanning electron microscopy (SEM) image analysis, the reinforcing mechanism of POM fibers is revealed: when shotcrete with POM fibers is subjected to flexural loading, it undergoes four stages: elastic, elastic–plastic, yield, and failure. The addition of POM fibers increases the density and uniformity of concrete, and the flexural strength is indirectly enhanced by increasing frictional energy dissipation through the formation of fiber–matrix interfaces between fibers and concrete. The research findings provide a theoretical basis and design reference for the application of POM fiber-reinforced shotcrete in tunnel support. Full article