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 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.

This study comprehensively investigates the development of ambient-cured self-consolidating geopolymer concrete (SCGC) based on the chemical composition of binders and alkaline activators. Five factors of the chemical composition of binders and alkaline activators, each with four levels, are used to evaluate and optimize the workability and compressive strength of the high-strength SCGC. The designed SCGC mixtures provided sufficient workability properties and compressive strength between 28 and 70.3 MPa (4061 and 10,196 psi). It was found that the SCGC mixture with a binder content of 600 kg/m3 (37.4 lb/ft3), a CaO/(SiO2 + Al2O3) mass ratio of 0.55, an Na2O/binder mass ratio of 0.11, an SiO2/Na2O mass ratio of 1.2, and an Na2O/H2O mass ratio of 0.35 was the optimum mixture, which achieved a slump flow of 770 mm (30.3 in.), 28-day compressive strength of 70.3 MPa (10,196 psi), and final setting time of 80 minutes. The CaO/(SiO2 + Al2O3) ratio in binders, binder content, and Na2O/binder mass ratio have been found to be the most influential factors on the workability and compressive strength of ambient-cured SCGC. Microstructural analysis of SCGC mixtures showed that the increase in the CaO/(SiO2 + Al2O3) ratio promoted the formation of calcium- aluminate-silicate-hydrate (C-A-S-H) gels and enhanced the compressive strength by filling voids and creating a compact and dense microstructure.

Crack densities obtained from on-site surveys of 74 bridge deck placements containing concrete mixtures with paste contents between 22.8% and 29.4% are evaluated. Twenty of the placements were constructed with a crack-reducing technology (shrinkage-reducing admixtures, internal curing, or fiber reinforcement) and 54 without; three of the decks with fiber reinforcement and nine of the decks without crack-reducing technologies involved poor construction practices. The results indicate that using a concrete mixture with a low paste content is the most effective way to reduce bridge deck cracking. Bridge decks with paste contents exceeding 27.3% had a significantly higher crack density than decks with lower paste contents. Crack-reducing technologies can play a role in reducing cracking in bridge decks, but they must be used in conjunction with a low paste content concrete and good construction practices to achieve minimal cracking in a deck. Failure to follow proper procedures to consolidate, finish, or cure concrete will result in bridge decks that exhibit increased cracking, even when low paste contents are used.