International Concrete Abstracts Portal

Due to global warming, the temperature of earth surface increased by 0.95 to 1.20℃ in the past 4 decades. The increase in temperature has significant effects on the concrete industry, causing alterations in concrete curing conditions and degradation in strength and durability properties. The understanding of changes in concrete properties due to variations in curing conditions from climate change is an imminent task that has to be resolved. Among the durability properties of concrete, freeze-thaw (FT) resistance is most directly affected by climate change. However, in all of the studies conducted on the FT behavior of concrete, the dramatic changes in environmental conditions due to climate change were not considered. Therefore, the focus of this study is to understand the FT performance of concrete from extreme temperature and relative humidity (RH) changes in curing conditions. To find the relationship between the curing condition change and FT resistance levels as a function of time, a 3-D satisfaction surface graph was developed using the Bayesian probabilistic method. Then, an example of drawing the 3-D satisfaction surface diagrams for FT resistance based on the weather conditions in New York City between 2001 and 2100 was shown. Furthermore, considering the reduction rate of the average annual FT cycle due to climate change, this study confirmed that FT resistance performance increased. This approach contributes to a performance-based evaluation (PBE) strategy for concrete exposed to FT cycles under various environmental conditions. The study details and results are discussed in the paper.

To address the autogenous shrinkage issue of ultra-high-performance concrete (UHPC), internal curing technology has shown great potential in resolving this challenge by providing additional moisture. To further improve its curing efficiency, this study proposes an innovative internal curing technology that can significantly reduce autogenous shrinkage without increasing the amount of internal curing water or compromising mechanical strength. This approach utilizes perforated cenospheres (PCs) as internal curing agents while substituting internal curing water with urea solutions. In addition to replenishing water, urea solutions, once released into the cement paste, can react with portlandite. This reaction generates CaCO₃; owing to the intrinsic properties of CaCO₃, it has a larger macroscopic volume and a much higher elastic modulus than portlandite. This approach effectively reduces chemical shrinkage while concurrently increasing the stiffness of the cement paste, thereby achieving a significant reduction in autogenous shrinkage. As a result, replacing water with 3% urea solution in PCs enhances the autogenous shrinkage of UHPC, reducing it from less than 50% to over 90%.

This study presents a machine learning–driven framework for the sustainable design of ultra-high-performance concrete (UHPC) mixtures with a focus on maximizing flexural strength while minimizing material cost and embodied CO₂ emissions. A curated dataset of 333 UHPC mixtures was developed, incorporating 13 input features including binder composition, steel fiber dosage, and curing parameters. A Bayesian Neural Network (BNN) was trained to predict flexural strength with high accuracy (R² = 0.936, RMSE = 1.37 MPa, MAE = 1.09 MPa), supported by residual analysis confirming minimal prediction bias and robust generalization. SHAP analysis was used to interpret model predictions and identify key drivers of flexural behavior—namely, curing time, steel fiber dosage, and silica fume content. The BNN was coupled with the NSGA-III algorithm to perform multi-objective optimization and generate Pareto-optimal UHPC mixtures. A utility-based scoring method was introduced to select designs aligned with different project priorities—enabling the identification of fiber-rich, high-strength mixtures as well as low-emission, cost-efficient alternatives. The framework supports field-level implementation and is well-suited for integration with sustainability rating systems such as LEED or Envision. It provides a transparent, generalizable, and industry-ready tool for intelligent UHPC mixture optimization, advancing data-driven design practices for green infrastructure applications.

Precast concrete (PC) moment-resisting frame systems with wide beam sections have been increasingly adopted in the construction industry due to their advantages in reducing the span length of PC slabs perpendicular to wide beam members and improving the constructability of precast construction. To further facilitate fast-built construction, this study introduces a novel PC wide beam-column connection system, where the solid panel zone is prefabricated and integrated into the PC column, allowing the upper floor to be quickly constructed without delay due to the curing time of cast-in-place concrete. Meanwhile, the current ACI CODE-318-19 code imposes strict allowable limits on the width of wide beams and complex reinforcement details as part of a seismic force-resisting system to effectively transfer forces into the joint, considering the shear lag effect. To address this, two full-scale PC wide beam-column test specimens were carefully designed, fabricated, and tested to explore the impact of large beam width and simplified reinforcement details beyond the code limit. The seismic performance was evaluated in terms of lateral strength, deformation capacity, stiffness degradation, failure mechanism, and energy dissipation. Based on the evaluation, the proposed PC wide beam-column connections demonstrated equivalent, or even better, seismic performance than the reinforced concrete control specimen. Additionally, it was found that the presence of corbels can mitigate the shear lag effect in PC wide beam-column connections, and that the current effective beam width limit imposed by ACI CODE-318-19 is conservative for PC wide beam-column connections with corbels.

In this work, novel polycarboxylate admixtures were synthesized by two different free radical polymerization systems of methacrylic acid (MAA) and methoxy polyethylene glycol methacrylate (MPEG-MA) for PC-1, and acrylic acid (AA) and iso amyl alcohol polyethylene glycol (IAA-PEG) for PC-2. Thioglycolic acid as a chain transfer agent and ammonium persulphate as an initiator were used. The synthesized carboxylic polymers were characterized using FTIR, H-NMR, gel permeation chromatography (GPC), and thermogravimetric analysis (TGA). The influence of the chemical structure of polycarboxylates on the rheology of the concrete, as well as the prognosis of the superplasticizer’s development, is also presented through measuring water consistency, setting times, flow table, slump test, Zeta potential, and compressive strength. The cementitious products were investigated with X-ray diffraction (XRD) and scanning electron microscope (SEM). The developed superplasticizers have shown good dispersion effects and slump performance in workability and fluidity retention tests, adsorption performance, and scanning electron microscopy performance. Intriguingly, the PC-1 and PC-2 mixes achieved flow table values of 230 and 200 mm, respectively. The compressive strength values at various curing ages up to 28 days exhibited double and triple values compared with the control sample. Additionally, compared to the control ordinary Portland cement paste, a reduction of water-to-cement ratio of about 0.25 and the development of excessive hydration products give PC-1 and PC-2 extensive pastes a more dense and compact structure in XRD and SEM investigation.