International Concrete Abstracts Portal

This study investigates the impact of air-entraining admixtures (AEA) on mortar performance, focusing on fresh-state and hardened-state properties critical to durability and engineering applications. Ten distinct mortar mixtures were analyzed, following guidelines established by EFNARC (European Federation of National Associations Representing Producers and Applicators of Specialist Building Products for Concrete). AEAs were introduced at varying proportions (0.01–0.5% of cement weight) to evaluate their effects on intrinsic properties (density, void ratio, water absorption), rheological parameters (plastic viscosity, yield stress), and mechanical characteristics (compressive strength, ultrasonic velocity, modulus of elasticity).

Regression models were developed, yielding high predictive accuracy with R² values exceeding 0.98. Notably, ultrasonic velocity and modulus of elasticity demonstrated strong correlations with intrinsic properties across all curing ages. Similarly, compressive strength showed significant associations with rheological parameters, highlighting the influence of air content and flow behavior on structural performance. These findings offer precise quantitative models for predicting mortar behavior and optimizing formulations for enhanced performance.

Geopolymer concrete (GPC) is a progressive material with the capability to significantly reduce global industrial waste. The combination of industrial by-products with alkaline solutions initiates an exothermic reaction, termed geopolymerization, resulting in a carbon-negative concrete that lessens environmental impact. The fly ash-based GPC (FA-based GPC) displays noticeable variability in its mechanical properties due to differences in mix design ratios and curing methods. To address this challenge, we optimized the constituent proportions of GPC through a meticulous selection of nine independent variables. A thorough experimental database of 1242 experimental observations was assembled from the available literature, and artificial neural networks (ANN) were employed for compressive strength modeling. The developed ANN model underwent rigorous evaluation using statistical metrics such as R-values, R₂ values, and mean square error (MSE). The statistical analysis revealed an absence of a direct correlation between compressive strength and independent variables, as well as a lack of correlation among the independent variables. However, the predicted compressive strength by the developed ANN model aligns well with experimental observations from the compiled database, with R₂ values for the training, validation, and testing datasets determined to be 0.84, 0.74, and 0.77, respectively. Sensitivity analysis identified curing temperature and silica-to-alumina ratio as the most crucial independent variables. Furthermore, the research introduced a novel method for deriving a mathematical expression from the trained model. The developed mathematical expressions accurately predict compressive strength, demonstrating minimal errors when using the tan-sigmoid activation function. Prediction errors were within the range of (-0.79 – 0.77) MPa, demonstrating high accuracy. These equations offer a practical alternative in engineering design, bypassing the intricacies of the internal processes within the ANN.

Compared to external curing, internal curing enables the judicious use of available water to provide additional moisture in concrete for more effective hydration and improvement in the performance of concrete structures. However, certain challenges with the incorporation of internal curing materials (ICMs) still need to be addressed, as their effectiveness depends on several factors. Furthermore, sustainable construction demands the use of recycled materials, and this paper discusses the comparative evaluation of recycled aggregate (RA) as an ICM, along with two other types of ICMs, on various properties of high-performance concrete in the hardened state under two curing conditions. Concrete mixtures were prepared with pre-wetted RAs, superabsorbent polymers (SAPs), and pre-wetted lightweight volcanic aggregates (LWVAs) as ICMs. Concrete performance was compared through the investigation of the strength development, shrinkage, mass loss, and volumetric water absorption. In addition, the change in internal humidity of concrete with time at different stages of hardening was determined. The compressive strength results showed that RA and LWVA are more efficient in early days, and the performance of SAP is better in the later age due to its slow water releasing capabilities. Compared to the control mixture, the least reduction in strength of 4% and 8% at 28 days and 90 days, respectively, could be observed for the mixtures containing RA under both air and water curing.

Lightweight concrete (LWC) finds wide-ranging applications inthe construction industry due to its reduced dead load, good fireresistance, and low thermal and acoustic conductivity. Lightweightgeopolymer concrete (LWGC) is an emerging type ofconcrete that is garnering attention in the construction industryfor its sustainable and eco-friendly properties. LWGC is producedusing geopolymer binders instead of cement, thereby reducing thecarbon footprint associated with conventional concrete production.However, the absence of standard codes for geopolymer concreterestricts its widespread application. To address this limitation,an investigation focused on developing a new mixture design forLWGC by modifying the existing ACI 211.2-98 provisions has beencarried out. In this study, crucial parameters of LWGC, such asalkaline-binder ratio (A/B), molarity, silicate/hydroxide ratio, andcuring temperature, were established using machine learning techniques. As a result, a simple and efficient method for determining the mixture proportions for LWGC has been proposed.

This study examines the impact of deicers on the compressivestrength and microstructure of concrete at ambient temperaturein sub-zero areas. In this study, after 7 days of curing in plainwater, concrete specimens were exposed to four deicer chemicalsolutions—sodium chloride, sodium acetate, calcium nitrate, andurea—at 3, 6, and 9% concentrations. The specimens were testedfor compressive strength after 14, 28, and 90 days of exposure. Alltested deicers, except calcium nitrate, have a propensity to decreasethe compressive strength of concrete. Exposure to sodium acetate,which appears to have the most detrimental effect, decreased thecompressive strength of concrete by a maximum of 30.79% at aconcentration of 9%, whereas exposure to calcium nitrate increasedthe compressive strength of concrete by 17% at a concentration of3%. Deicers changed the microstructure of concrete, which wasinvestigated using field-emission scanning electron microscopy(FE-SEM). This was followed by X-ray diffraction (XRD) for qualitative analysis of phases present in deicer-treated concrete specimens. The desirability function was used to determine the optimal exposure period and calcium nitrate concentration for concrete in sub-zero environments, which were 10 to 11 days and 8.8% to 9%, respectively.