Concrete bridges, as a vital component of modern transportation infrastructure, have their structural durability directly tied to safety and service life. In recent years, with the aging of bridge structures and increasingly complex environmental conditions, various durability-related deteriorations have become more prominent, significantly affecting structural performance and maintenance costs. This paper presents a systematic analysis of concrete carbonation as a key chemical process and its impact on durability-related pathologies. Particular attention is given to the formation mechanisms and influencing factors of critical deterioration modes such as cracking, reinforcement corrosion, and freeze–thaw damage. A multi-level prevention and mitigation strategy is proposed, encompassing optimized structural material design, strict construction quality control, and effective maintenance and repair techniques. The study concludes that the durability issues of concrete bridge structures exhibit a strong multi-factor coupling effect and proposes a core durability assurance framework. Finally, the paper briefly outlines emerging trends in intelligent monitoring and digital operation and maintenance, offering insights for future durability management of bridges.

With the continuous improvement in technology, the construction industry is constantly advancing. Traditional concrete can no longer meet modern market demands, making research on new types of concrete imperative. This study reviews the application of common nanomaterials in concrete and their impact on concrete performance. It provides a detailed explanation of the characteristics of three common nanomaterials: nano-silica, nano-calcium carbonate, and carbon nanotubes. This study analyzes how these materials improve the microstructure, accelerate hydration reactions, and enhance interfacial transition zones, thereby enhancing the mechanical properties, durability, and workability of concrete. For conventional engineering projects, nano-calcium carbonate is the preferred choice owing to its low cost and its capacity to improve workability and early-age strength. For high-strength and durable structures, nano-silica is selected due to its high specific surface area (ranging from 100 to 800 m²/g) and its superior compactness and impermeability. In the context of intelligent buildings, carbon nanotubes are the most suitable option because of their exceptional thermal conductivity and electrical conductivity (with axial thermal conductivity reaching 2000–6000 W/m*K and electrical conductivity ranging from 10³ to 10⁶ S/cm). However, it should be noted that carbon nanotubes are the most expensive among the three materials. Additionally, this study discusses the issues and challenges currently faced by the application of nanomaterials in concrete and looks ahead to future research directions, aiming to provide a reference for further research and engineering applications of nanomaterials in the field of concrete.

This paper reviews the applications and performance advantages of ultra-high-performance concrete (UHPC), engineered cementitious composite (ECC), and recycled aggregate concrete (RAC) in composite flexural members. UHPC is characterized by its ultra-high strength, high toughness, excellent durability, and microcrack self-healing capability, albeit with high costs and complex production processes. ECC demonstrates superior tensile, flexural, and compressive strength and durability, yet it exhibits a lower elastic modulus and greater drying shrinkage strain. RAC, as an eco-friendly concrete, offers cost-effectiveness and environmental benefits, although it poses certain performance challenges. The focus of this review is on how to enhance the load-bearing capacity of composite beams or slabs by modifying the interface roughness, adjusting the thickness of the ECC or UHPC layer, and altering the cross-sectional form. The integration of diverse concrete materials improves the performance of beam and slab elements while managing costs. For instance, increasing the thickness of the UHPC or ECC layer typically enhances the load-bearing capacity of composite beams or plates by approximately 10% to 40%. Increasing the roughness of the interface can significantly improve the interfacial bond strength and further augment the ultimate load-bearing capacity of composite components. Moreover, the optimized design of material mix proportions and cross-sectional shapes can also contribute to enhancing the load-bearing capacity, crack resistance, and ductility of composite components. Nevertheless, challenges persist in engineering applications, such as the scarcity of long-term monitoring data on durability, fatigue performance, and creep effects. Additionally, existing design codes inadequately address the nonlinear behavior of multi-material composite structures, necessitating further refinement of design theories.

The accurate real-time delineation of overburden failure zones, specifically the caved and water-conducted fracture zones, remains a significant challenge in longwall mining, as conventional monitoring methods often lack the spatial continuity and resolution for precise, full-profile strain measurement. Based on the hydrogeological data of the E9103 working face in Hengjin Coal Mine, a numerical calculation model for the overburden strata of the E9103 working face was established to simulate and analyze the stress distribution, failure characteristics, and development height of the water-conducting fracture zones in the overburden strata of the working face. To address this problem, this study presents the application of a distributed optical fiber sensing (DOFS) system, centering on an innovative fiber installation technology. The methodology involves embedding the sensing fiber into boreholes within the overlying strata and employing grouting to achieve effective coupling with the rock mass, a critical step that restores the in situ geological environment and ensures measurement reliability. Field validation at the E9103 longwall face successfully captured the dynamic evolution of the strain field during mining. The results quantitatively identified the caved zone at a height of 13.1–16.33 m and the water-conducted fracture zone at 58–60.6 m. By detecting abrupt strain changes, the system enables the back-analysis of fracture propagation paths and the identification of potential seepage channels. This work demonstrates that the proposed DOFS-based monitoring system, with its precise spatial resolution and real-time capability, provides a robust scientific basis for the early warning of roof hazards, such as water inrushes, thereby contributing to the advancement of intelligent and safe mining practices.

The performance degradation of concrete structures directly impacts their safety. As such, accurately predicting their remaining service life is critical for effective operation and maintenance management. This paper reviews the key factors influencing the degradation of concrete structures, providing a comprehensive summary of current research on deterioration mechanisms, steel corrosion, crack propagation, and chloride ion penetration. It also compares the advantages and limitations of physical, empirical, statistical, and machine learning models used for life prediction. A critical aspect highlighted in this paper is the importance of model validation based on real-world field data, which can more effectively determine the applicability of prediction models in actual engineering practice. Model validation incorporates evaluation metrics like sensitivity analysis to gauge how fluctuations in input parameters, such as temperature, influence life prediction models and thereby reveal the uncertainties inherent in complex engineering environments. Currently, life prediction models are widely applied to infrastructure projects like bridges and tunnels. By incorporating environmental factors such as chloride ion concentration, temperature, and humidity, as well as real-time monitoring data, these models effectively predict the remaining service life, aiding engineers in developing optimized maintenance strategies. However, current models still face challenges in terms of data requirements and accuracy. Future research should focus on the integration of hybrid models and intelligent technologies. By leveraging the combined strengths of physical and data-driven approaches, hybrid models can enhance prediction accuracy. Additionally, intelligent technologies and real-time monitoring will help dynamically update and optimize models, resulting in more precise and efficient life predictions.

To utilize garbage fly ash (GFA) as a resource, this research proposes a method for preparing GFA with higher reactivity through carbonation and applies it to the production of foamed concrete. The effects of CO₂-cured GFA substitution rate and foam volume on slump flow, rheological properties, mechanical strength, thermal conductivity, water absorption rate, and water resistance coefficient of foam concrete are clarified. The results show that an increase in the CO₂-cured GFA substitution rate from 0 to 100% improves the slump flow by 10.8%~34.5% and decreases the plastic viscosity by 4.8%~36.4% and yield stress by 5.6%~28.1%. The higher carbonized GFA substitution rate can prolong the initial setting time with the largest amplitude of 30.4%. In addition, increasing the CO₂-cured GFA substitution rate improves the mechanical strengths, water resistance, thermal conductivity, and solidification of heavy metals. When the CO₂-cured GFA substitution rate is 100%, the 28-day compressive strength, 28-day flexural strength, water absorption rate, water resistance coefficient, thermal conductivity, leached Zn, and leached Cr of foam concrete are 18 MPa, 3.6 MPa, 20.7%, 0.46, 0.69 W·m⁻¹·K⁻¹, 9.4 × 10⁻⁵ mg/mL, and 8.6 × 10⁻⁵ mg/mL, respectively. Moreover, more foam volume improves the fresh-mixed performance of foam concrete while reducing the mechanical strength, water resistance property, thermal conductivity, and solidification of heavy metals. It is found that the technical approach for preparing foamed concrete containing CO₂-cured GFA with 40% foam volume can achieve its large-scale use.