Search Results (1,300)

The accelerated carbonation of fresh concrete and recycled aggregates is one of the safest methods of CO₂ sequestration as it mineralizes CO₂, preventing its escape into the atmosphere. CO₂ injection during batching of concrete improves its strength and may partially replace Portland cement, as with supplementary cementitious materials (SCMs). The curing of concrete by incorporation of CO₂ also accelerates early strength development, which may enable early stripping of formwork/moulds for precast and in situ construction. The carbonation process may also be used for the beneficiation of recycled aggregates sourced from demolition waste. The CO₂ mineralization technique may also be used for producing low-carbon, carbon-neutral, or carbon-negative concrete constituents via the carbonation of mineral feedstock, including industrial wastes like steel slag, mine tailings, or raw quarried minerals. This research paper analyses various available technologies for CO₂ storage in concrete, CO₂ curing and mixing of concrete, and CO₂ injection for improving the properties of recycled aggregates. Carbon dioxide can be incorporated into concrete both through reaction with hydrating cement and through incorporation in recycled aggregates, giving a product of similar properties to concrete made from virgin materials. In this contribution we explore the various methodologies available to incorporate CO₂ in both hydrating cement and recycled aggregates and develop a protocol for best practice. We find that the loss of concrete strength due to the incorporation of recycled aggregates can be mitigated by CO₂ curing of the aggregates and the hydrating concrete, giving no negative strength consequences and sequestering around 30 kg of CO₂ per cubic metre of concrete. Full article

Electrical curing is a viable alternative to traditional thermal curing for geopolymer materials due to its capability for rapid and internal geopolymerization. In this research, reinforced geopolymer-based composite beams were successfully fabricated at a macroscale using a binary system of fly ash (FA) and granulated blast furnace slag (GBFS). The mixture was activated with a solution of sodium silicate (Na₂SiO₃) and sodium hydroxide (NaOH) with a fixed molar ratio of 2:1 for both, and aggregate-to-binder and activator-to-binder (A/B) ratios of 2.5 and 0.7, respectively. To ensure electrical conductivity, individual fiber systems were employed, including carbon fiber (CF), steel fiber (SF), and waste wire erosion (WWE), each incorporated at a dosage of 0.5 vol.% of the total mix volume. In addition, carbon black (CB) was introduced as a conductive filler at a constant dosage of 2.0 vol.% of the binder content in selected specimens. Each beam specimen contained only one type of conductive reinforcement or filler. A total of twelve reinforced geopolymer-based composite beams with a 150 mm square section and a span of 1300 mm, with a clear span of 1200 mm, were successfully cast and reinforced based on reinforced concrete beam designs and standards, with a dominant goal of enhancing beam behavior under flexure. The beams were cured in ambient curing conditions, or using thermal curing at 80 °C for 24 h, and using electrical curing from the fresh states with a fixed voltage of 25 V. Notwithstanding a common beam size and reinforcement pattern, distinct curing methods significantly influenced beam structure properties. Peak loads were between 20.8 and 31.5 kN, initial stiffness between 1.75 and 6.09 kN/mm, and total energy absorption between 690 and 1550 kN/mm, with a post-peak energy component of between 0.12 and 0.55. Displacement-based ductility measures spanned from 3.2 to 8.1 units with a distinct improvement in electrical curing regimes, especially in the SF-reinforced specimens; this indicates that electrical curing in reinforced geopolymer composite materials works as a governing mechanism in performance rather than simply a method for enhancing the strength of materials. Full article

This study presents an innovative approach by combining magnetized water (MW) with Bacillus megaterium to improve the sustainability of concrete under various curing conditions. These enhancements contribute directly to reduced cement use and improved durability, both essential factors in sustainable construction. An experimental program with 27 distinct mixes analyzed variables such as the type of water (tap water/TW and two magnetization sequences/MW1 and MW2), bacterial dosage (0%, 2.5%, and 5% relative to cement weight), and curing methods (traditional water curing/C1, thermal shock/C2, freeze–thaw/C3). The primary discovery is a synergistic relationship between MW and bacteria: the MW1 treatment (1.5 T followed by 0.9 T) paired with a 2.5% bacterial dosage significantly improved the mechanical and self-healing properties of the concrete. This combination led to significant improvements in workability and compressive strength, achieving an increase of as much as 46.5% compared to the control. There was also an impressive recovery of strength in pre-cracked specimens, particularly under thermal shock curing (C2), where some healed cubes exceeded the strength of the uncracked ones. On the other hand, a 5% bacterial dosage was less effective, often resulting in reduced returns due to variations in microstructure. SEM and XRD analyses confirmed a more compact matrix and increased calcite precipitation with 2.5% bacteria, illustrating the combined effects of microbial activity and microwave treatment for sustainable concrete. Full article

Regarding the issues arising from the addition of external curing agents in the application of epoxy resin in cement-based materials, this paper explores the feasibility of endogenous curing of epoxy resin in the alkaline environment of cement-based systems. It further analyzes and investigates the curing characteristics of epoxy resin without external curing agents and their impact on the performance of cement-based materials. Differential scanning calorimetry, mechanical property testing, microstructural observation, and electrochemical impedance spectroscopy were used to study the mechanism of sodium hydroxide (NaOH) catalyzing the process of bisphenol-A epoxy resin (E-51)-based curing, the influence of moisture and temperature on curing kinetics, and the performance of epoxy resins in mortar and self-healing concrete. The results showed that E-51 achieved self-curing under alkaline conditions in the absence of an external hardener. However, moisture significantly inhibited the reaction process. Elevating the temperature and reducing environmental humidity effectively promoted the curing reaction. In cement-based materials, E-51 exhibited endogenous curing by the inherent alkalinity of the system, remarkably enhancing the compressive strength of mortar. At 60 °C, mortar containing 10% E-51 (by cement mass) exhibited a 1.5-fold higher compressive strength than that of the control group without E-51 at 14 days of curing. It demonstrated higher healing efficiency in a microencapsulated self-healing concrete system than the traditional curing agent systems. Concrete specimens with damage induced by loading at 60% of their compressive strength exhibited 100% recovery of ultrasonic pulse velocity after storing indoors for 28 d. The findings of this study can provide theoretical basis and technical support for the application of epoxy resins in cement-based materials without the need for curing agents. Full article

This study investigates the early-age performance of large-area C30 concrete slabs under different curing regimes using a multi-scale approach combining laboratory experiments, field monitoring, and numerical simulation. The experimental results indicated that standard curing (SC7) maximized the mechanical properties. In contrast, the thermal insulation and moisture retention curing (TC) regime significantly reduced temperature gradients and stress mutation amplitudes by 42% compared to wet curing (WC) by leveraging the synergistic effect of aluminum foil and insulating cotton. This makes TC a preferred solution in situations where engineering constraints apply. Field monitoring demonstrated that WC is suitable for humidity-sensitive scenarios with low-temperature control requirements, while TC is more suitable for large-area concrete or low-temperature environments, balancing early strength development and long-term durability. This multi-field coupled model exhibits significant deviations during the early stage (0–7 days) due to complex boundary interactions, but achieves high quantitative accuracy in the long-term steady state (after 14 days), with a maximum error below 8%. The analysis revealed that the key driving factors for stress evolution are early hydration heat–humidity coupling and mid-term boundary transient switching. The study provides a novel, multi-scale validated curing optimization path for crack control in large-area concrete slabs. Full article

The contraction joints within paver runs are important for the design and construction of rigid aircraft pavements. These joints are typically un-doweled and sawn into the pavement to induce a crack. The joints control shrinkage cracking during curing, allow for thermal expansion and contraction, and provide load transfer through aggregate interlock joint stiffness between adjacent slabs. Aggregate interlock joint stiffness is typically modeled by assigning a spring element between two slabs that is indicative of the stiffness of the joint. However, that simplification may not accurately represent the complex interaction of irregularly shaped concrete faces and joint openings. Consequently, previous researchers have recommended modelling aggregate interlock stiffness based on physical crack shape. This research uses a novel approach to characterize crack shape through an idealized two-dimensional sinusoidal shape. Once the crack shape was defined, finite element methods were used to determine the significance of load, sublayer, and crack shape factors on load transfer values. It was determined that joint opening was the most significant factor for aggregate interlock load transfer. Future research is recommended to further validate the model against a larger data set, to confirm if the two-dimensional idealization of crack shape is an appropriate estimation of field conditions. Full article

Red mud (RM), an industrial byproduct generated during bauxite refining, has accumulated to more than 5 billion tons worldwide, posing serious environmental challenges. In response, substantial research over recent decades has focused on the sustainable utilization of RM, particularly in the field of construction materials. This review first summarizes the generation process and chemical composition of RM, and then systematically examines its potential applications in the production of artificial aggregates, partial replacement of cementitious materials, and synthesis of geopolymers. Existing studies demonstrate that RM exhibits considerable potential in construction applications: when used as an aggregate, it can reduce concrete porosity, enhance compressive strength, and improve overall mechanical performance. Moreover, RM can partially substitute cement or serve as a geopolymer precursor, contributing to the immobilization of toxic elements such as Pb and Cr while simultaneously improving the mechanical properties of both cementitious systems and geopolymers. The reactivity and performance of RM-based materials can be further enhanced through carbonation curing and other modification techniques. Finally, this review highlights the significant sustainability and economic benefits of RM-based concrete, supported by life-cycle assessment and cost–benefit analyses. Full article

Early-age shrinkage in 3D-printed concrete constitutes a critical applied challenge due to the rapid development of deformations and the absence of conventional reinforcement systems. From a scientific standpoint, a clear knowledge gap exists in materials science concerning the reliable quantification of very small, rapidly evolving strains in fresh and early-age cementitious materials produced by additive manufacturing. This study investigates practical and low-cost alternatives to commercial optical systems for monitoring early-age shrinkage in 3D-printed concrete, a key challenge given the rapid deformation of printed elements and their typical lack of reinforcement. The work focuses on identifying both the most precise method for capturing minor, fast-developing strains and affordable tools suitable for laboratories without access to advanced equipment. Three mixtures with different aggregate types were examined to broaden the applicability of the findings and to evaluate how aggregate selection affects fresh properties, hardened performance, and shrinkage behavior. Shrinkage measurements were carried out using a commercial digital image correlation system, which served as the reference method, along with simplified optical setups based on a smartphone camera and a GoPro device. Additional measurements were performed with laser displacement sensors and Linear Variable Differential Transformer LVDT transducers mounted in a dedicated fixture. Results were compared with the standardized linear shrinkage test to assess precision, stability, and the influence of curing conditions. The findings show that early-age shrinkage must be monitored immediately after printing and under controlled environmental conditions. When the results obtained after 12 h of measurement were compared with the values recorded using the commercial reference system, differences of 19%, 13%, 16%, and 14% were observed for the smartphone-based method, the GoPro system, the laser sensors, and the LVDT transducers, respectively. Full article

This study evaluates the performance of single concrete-filled frictional Fibre-Reinforced Polymer (FRP) piles embedded in saturated liquefiable sand and subjected to seismic loading using a shaking table. A unidirectional shaking table equipped with a 1000 mm × 1000 mm × 1000 mm laminar shear box with 27 lamina rings was utilized in the study. FRP tubes manufactured from epoxy-saturated Carbon Fibre-Reinforced Polymer (CFRP) and Glass Fibre-Reinforced Polymer (GFRP) fabrics were filled with 35 MPa concrete and allowed to cure for 28 days, serving as model piles for the experimental programme, with cylindrical concrete prisms employed to represent the behaviour of traditional piles. Pile dimensions and properties based on scaling relationships were selected to account for the nonlinear nature of soil–pile systems under seismic loading. Scaled versions of ground motions from the 2010 Val-des-Bois and 1995 Hyogo-Ken Nambu earthquakes were implemented as input motions in the tests. The results show limited variation in the inertial and kinematic responses of the piles, especially before liquefaction. Head rocking displacements were within 5% of each other during liquefaction. Post liquefaction, the concrete-filled FRP piles showed lower response compared to the traditional concrete pile. The results suggests that concrete-filled FRP piles, especially those made from carbon fibre, provide practical alternatives for use. Full article

This study investigates the effects of agro-waste-based capsules made from grape seeds and cherry pits on the physical, mechanical, thermal and self-healing properties of concrete. Capsule-containing mixtures were compared with a reference concrete after 28 days of water curing using both standardized and non-standardized testing methods. Capsule incorporation reduced workability by up to 91% and altered air content depending on capsule type, increasing it by 47% for grape seed capsules and decreasing it by 65% for cherry pit capsules. Fresh concrete density was reduced by 5.5% and 6.8% for grape seed and cherry pit capsules, respectively, while hardened concrete density decreased by 11% and 9%, implying lighter structures with improved seismic resistance. Compressive strength decreased by 49% for grape seed capsules and 27% for cherry pit capsules. Thermal conductivity was reduced by 32% and 22%, respectively, indicating improved energy efficiency. Concrete with grape seed capsules showed freeze–thaw performance comparable to the reference concrete after 112 cycles, whereas concrete with cherry pit capsules exhibited superior dynamic modulus behavior, suggesting continuous crack healing, despite significant mass loss due to poor capsule–matrix bonding. SEM analysis showed no significant crack reduction, while EDS revealed calcium-rich areas in grape seed capsule concrete, indicating possible crack healing. Overall, agro-waste capsule concrete shows potential for improving seismic resistance and energy efficiency, although further research is required to clarify the self-healing effect. Full article

The deterioration of concrete hydraulic structures caused by chemical factors, seepage, and environmental stress necessitates advanced protective coatings that enhance durability, flexibility, and environmental sustainability. Conventional protective systems often exhibit limited durability under combined hydraulic, thermal, and chemical stress. In this study, a novel polyfluorosilicone-based coating system is presented, which integrates a deep-penetrating nano-primer for substrate reinforcement, a crack-bridging polymer intermediate layer for impermeability, and a polyfluorosilicone topcoat providing UV and weather resistance. The multilayer architecture addresses the inherent trade-offs between adhesion, flexibility, and durability observed in conventional waterproofing systems. Informed by a mechanistic study of interfacial adhesion and failure modes, the coating exhibits outstanding high mechanical and performance characteristics, including a mean pull-off bond strength of 4.56 ± 0.14 MPa for the fully cured triple-layer coating system, with cohesive failure occurring within the concrete substrate, signifying a bond stronger than the material it protects. The system withstood 2.2 MPa water pressure and 200 freeze–thaw cycles with 87.2% modulus retention, demonstrating stable mechanical and environmental durability. The coating demonstrated excellent resilience, showing no evidence of degradation after 1000 h of UV aging, 200 freeze–thaw cycles, and exposure to alkaline solutions. This water-based formulation meets green-material standards, with low volatile organic compound (VOC) levels and minimal harmful chemicals. The results validate that a multi-scale, layered design strategy effectively decouples and addresses the distinct failure mechanisms in hydraulic environments, providing a robust and sustainable solution. Full article

Resistance against water penetration is one of the key indicators of concrete durability in humid and pressurized environments. An intelligent model based on the XGBoost machine-learning algorithm was developed to predict the water penetration depth, using 1512 independent experimental measurements. The influential variables included water pressure, pressure duration, thermal cycles, fiber content, curing, and compressive strength. The investigated concrete specimens and field-tested structures in this study were exposed to arid and hot climatic conditions, and the proposed model was developed within this environmental context. To accurately simulate the water transport behavior, a cylindrical-chamber test was employed, enabling non-destructive and in-situ evaluation of structures. Correlation analysis revealed that compressive strength had the strongest negative influence (r = −0.598), while free curing exhibited the strongest positive influence (r = +0.654) on penetration depth. After hyperparameter optimization, the XGBoost model achieved the best performance (R² = 0.956, RMSE = 1.08 mm, MAE = 0.81 mm). Feature importance analysis indicated that penetration volume, pressure, and curing were the most significant predictors. According to the partial dependence analysis, both pressure and duration exhibited an approximately linear increase in penetration depth, while a W/C ratio below 0.45 and curing markedly reduced permeability. Microstructural interpretation using MIP, XRD, and SEM tests supported the physical interpretation of the trends identified by the machine-learning model. The results demonstrate that machine-learning-models can serve as fast and accurate tools for assessing durability and predicting permeability under severe environmental conditions. Finally, the permeability of several real structures was evaluated using the machine-learning approach, showing excellent prediction accuracy. Full article

To investigate the fracture behavior of super-absorbent polymer (SAP) internally cured polyvinyl alcohol (PVA) fiber-reinforced concrete (SAP-PVAC), three-point bending tests were carried out. This study systematically examined the effects of (1) PVA fiber content and (2) initial crack-depth-to-beam-height ratios (a₀/D) on the failure modes, fracture toughness (K_IC), and residual flexural tensile strength (f_R,1) of SAP-PVAC beams. The test results demonstrate that SAP particles have a weakening effect on concrete strength (reduce about 6%). Still, the addition of PVA fibers can effectively improve the crack-resistance performance of SAP-PVAC and significantly increase the residual flexural tensile strength by 4.5–42%. The softening performance of the concrete is affected by the initial crack-height ratio. An increase in a₀/D leads to an obvious increase in the crack opening displacement but has little impact on the fracture toughness, while the fracture energy shows a downward trend. SEM microscopic analysis reveals that the synergistic effect of SAP and PVA fibers exhibits a positive promoting effect on the toughening and crack resistance of SAP-PVAC specimens. These results establish a theoretical framework for SAP-PVAC fracture assessment and provide actionable guidelines for its shrinkage-crack mitigation structure engineering applications. Full article

For massive monolithic foundation slabs, the risk of early cracking during construction is a pressing issue. This problem is primarily caused by thermal stresses arising from uneven heating of the structure during concrete curing and cooling. The most common approach to assessing thermal stresses is to express them through the temperature difference between the center and surface of the structure. However, this approach fails to take into account that heat transfer conditions on the upper and lower surfaces of the slab may differ. The purpose of this article is to derive calculation relationships that allow thermal stresses to be expressed through temperatures at three characteristic points on the slab: at the lower surface, in the middle of the slab, and at the upper surface. The resulting formulas were validated by comparison with the results of finite element analysis and an experiment presented in the work of other authors. Compared to the results of finite element analysis, the error in determining the maximum tensile stresses at the center of the slab is 0.4%. To assess the applicability limits of the resulting formulas, a series of finite element calculations were also performed for various slab thicknesses. It was established that for a slab thickness of up to 2 m, the error in determining stresses at three characteristic points using the authors’ formulas does not exceed 10%. Full article

The construction industry significantly contributes to global sustainability challenges, producing 30–40 percent of global carbon dioxide emissions and consuming large amounts of natural resources. Pervious concrete has emerged as a sustainable alternative to conventional pavements due to its ability to promote stormwater infiltration and groundwater recharge. However, the absence of fine aggregates creates a highly porous structure that results in reduced compressive strength, limiting its broader structural use. Determining compressive strength traditionally requires destructive laboratory testing of concrete specimens, which demands considerable material, energy, and curing time, often up to 28 days—before results can be obtained. This makes iterative mix design and optimization both slow and resource intensive. To address this practical limitation, this study applies Machine Learning (ML) as a rapid, preliminary estimation tool capable of providing early predictions of compressive strength based on mix composition and curing parameters. Rather than replacing laboratory testing, the developed ML models serve as supportive decision-making tools, enabling engineers to assess potential strength outcomes before casting and curing physical specimens. This can reduce the number of trial batches produced, lower material consumption, and minimize the environmental footprint associated with repeated destructive testing. Multiple ML algorithms were trained and evaluated using data from existing literature and validated through laboratory testing. The results indicate that ML can provide reliable preliminary strength estimates, offering a faster and more resource-efficient approach to guiding mix design adjustments. By reducing the reliance on repeated 28-day test cycles, the integration of ML into previous concrete research supports more sustainable, cost-effective, and time-efficient material development practices. Full article