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.

The interfacial shear performance between ultra-high-performance concrete (UHPC) and normal concrete (NC) is a critical factor in determining the overall performance of composite structures. This paper systematically reviews the research progress on the interfacial shear performance of UHPC-NC, revealing the core mechanisms of bond strength (dominated by mechanical interlocking with chemical bonding as a supplementary factor). It compares the advantages and disadvantages of single-shear, Z-shaped shear, double-shear, and inclined shear tests, clarifying the influence patterns of key parameters such as interface roughness, matrix wetness, curing conditions, and fiber content. This study found that interface treatment is the most significant factor in improving shear strength. Roughening or grooving treatments can increase the strength by more than 40%~80%, while the combination of rebar planting and grooving can further enhance ductility. The matrix wetness (saturated and moist) and UHPC age (within 7 days) need to be strictly controlled to avoid differences in shrinkage stress. Prediction models based on mechanics, finite element analysis, and experimental data each have their advantages and disadvantages and should be selected based on actual working conditions. To address common issues in practical engineering, such as insufficient interface roughness, shrinkage cracking, and fatigue degradation under cyclic loading, it is recommended to adopt composite interface treatment techniques (such as roughening + rebar planting), prestressing design, and optimized fiber distribution (with a steel fiber content of 1.5%~2.5%). This paper provides the theoretical basis and practical guidance for the design optimization and construction control of UHPC reinforcement projects and composite structures.

Straw fibers are renowned for their cost-effectiveness, sustainability, and durability. They represent a promising natural reinforcement option for reactive powder concrete (RPC). This paper investigated the impact of straw fibers on RPC’s workability, mechanical performance (mechanical strength and flexural toughness), and electrical properties (electrical resistance and AC impedance spectroscopy curves). The straw fiber volumes ranged from 1% to 4.0% of the total RPC volume. Specimens were cured under standard curing conditions for 3, 7, 14, and 28 days. Mechanical and electrical properties of the specimens were tested before chloride salt erosion. The mass loss and ultrasonic velocity loss of the samples were measured under NaCl freeze–thaw cycles (F-Cs). The mass loss, ultrasonic velocity loss, and mechanical strengths loss of the samples were measured under NaCl dry–wet alternations (D-As). The findings indicated that incorporating straw fibers enhanced RPC’s flexural strength, compressive strength, and flexural toughness by 21.3% to 45.76%, −7.16% to 11.62%, and 2.4% to 32.7%, respectively, following a 28-day curing period. The addition of straw fibers could augment the AC electrical resistance of the RPC by 10.17% to 58.1%. The electrical characteristics of the RPC adhered to series conduction models. A power function relationship existed between the electrical resistance and mechanical strengths of the RPC. After 10 NaCl D-As, the mass loss rate, ultrasonic velocity loss rate, flexural strength, and compressive strength loss rates of the RPC decreased by 0.42% to 1.68%, 2.69% to 6.73%, 9.6% to 35.65%, and 5.41% to 34.88%, respectively, compared to blank samples. After undergoing 200 NaCl F-Cs, the rates of mass loss and ultrasonic velocity loss of the RPC decreased by 0.89% to 1.01% and 6.68% to 8.9%, respectively.

Ultra-High-Performance Concrete (UHPC) is increasingly used in various engineering projects due to its exceptional mechanical properties. This work conducts a literature review of research on the shear performance of UHPC beams in recent decades, with a focus on summarizing the formulas for calculating shear capacity and the main factors influencing shear performance. Firstly, this work reviews the calculation methods for the shear capacity of UHPC beams in different countries, along with their respective advantages and limitations. Subsequently, it provides a detailed analysis of various factors influencing the shear performance of UHPC beams, including longitudinal and stirrup reinforcement, steel fiber content, aggregates, admixtures, the shear-span ratio, shear keys, bolts, shear-reinforcement techniques, and environmental impacts. Through horizontal comparisons, the performance of UHPC beams and ordinary concrete beams under similar experimental conditions is examined to reveal the optimal shear working conditions for UHPC beams. Additionally, it is found that UHPC performs exceptionally well in composite beams, being compatible with numerous materials and significantly enhancing the shear strength of these beams. Lastly, the paper proposes suggestions for maximizing the shear performance of UHPC beams within a safe and reliable operating range and outlines future research directions.

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 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.