International Concrete Abstracts Portal

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 costs and embodied CO2 emissions. A curated data set 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, root mean square error [RMSE] = 1.37 MPa, and mean absolute error [MAE] = 1.09 MPa), supported by residual analysis confirming minimal prediction bias and robust generalization. SHapley Additive exPlanations (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 Non-dominated Sorting Genetic Algorithm III (NSGA-III) 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 Leadership in Energy and Environmental Design (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.

In this work, novel polycarboxylate admixtures were synthesized by two different free radical polymerization systems: methacrylic acid (MAA) and methoxy polyethylene glycol methacrylate (MPEG-MA) for PC-1, and acrylic acid (AA) and isoamyl alcohol polyethylene glycol (IAA-PEG) for PC-2. Thioglycolic acid as a chain transfer agent and ammonium persulfate as an initiator were used. The synthesized carboxylic polymers were characterized using Fourier-transform infrared spectroscopy (FTIR), proton nuclear magnetic resonance (1H-NMR), gel permeation chromatography (GPC), and thermogravimetric analysis (TG). 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 of 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 showed good dispersion effects and slump performance in workability and fluidity retention tests, adsorption performance, and SEM performance. Intriguingly, the PC-1 and PC-2 mixtures 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 the water-cement ratio (w/c) of approximately 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.

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 uses perforated cenospheres (PCs) as internal curing agents while substituting internal curing water with urea solution. In addition to replenishing water, urea solution, 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 reduces autogenous shrinkage of UHPC from over 90% to less than 50%.

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 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 318-19 is conservative for PC wide beam-column connections with corbels.

Alkali-silica reaction (ASR) is a destructive phenomenon that may occur due to the use of certain types of siliceous aggregates in concrete with high alkali content. This study examines the performance of ASR-affected reinforced concrete (RC) corbels, which are short cantilevers that transfer concentrated forces to columns. Eighteen full-scale RC double corbels were designed according to ACI CODE-318-19 provisions and fabricated using concrete that contained reactive fine aggregates as well as sodium hydroxide to boost the alkali content up to 1.75%. Variables among the specimens included design methodology, shear spans-to-effective depth ratio, and reinforcement layout. The specimens were tested until failure either in control conditions before noticeable ASR expansions, or after 110, 220, or 300 days of accelerated curing in a relative humidity of 100% and a temperature of 45°C to achieve uniaxial expansion levels of 0.1, 0.15, and 0.2%, which are denoted as E1, E2, and E3 expansion levels. Results showed that ASR caused irregular and relatively small changes in compressive and splitting tensile strength of concrete cylinders, but up to a 58% reduction in their modulus of elasticity. Nevertheless, ASR-affected corbels containing distributed reinforcement exhibited increased stiffness compared to control specimens, likely due to restrained expansions. The ultimate strength of ASR-affected corbels compared to that of the control specimens was greater by up to 44% in the E1 expansion level and 32% in E2 and E3 expansion levels. Both the empirical design method and the strut and tie method (STM) provided conservative estimates of the ultimate capacity of corbels in control or ASR-affected conditions.