International Concrete Abstracts Portal

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.

In this study, a chloride adsorption test was performed to depict the chemical evolution of pore solution for cement hydration. It was found that the amount of chloride adsorbed by the AFm phase and the calcium-silicate-hydrate (C-S-H) phase decreased with the increasing pH of the pore solution. The stability of Friedel’s salt tended to decrease with the increasing pH of the pore solution. Notably, in the C-S-H phase, the decrease in the amount of chloride adsorption resulting from an increase in the pH level was larger when the Ca/Si ratio was higher. Based on these works, multiple regression analysis was performed to examine the correlation between the chloride adsorption density of cement hydrates and the experimental variables involved, including the pH of the pore solution and the amount of chloride-ion penetration. The pH of the pore solution was predicted based on cement hydration and pore-chemistry theories, and these results were combined with the experimental results, considering the changing chemical characteristics of the pore solution during each temporal stage of cement hydration. The amount of chloride-ion adsorption in fly ash (FA) and granulated blast-furnace slag (GBFS) was larger than in ordinary portland cement (OPC) due to the decreased pH of the pore solution resulting from the consumption of calcium hydroxide.

Firstly, the proposed static test was carried out on eight fly ash foamed concrete walls with different axial compression ratios μ and steel ratios ρ. Secondly, the quantitative analysis method of wall damage was proposed based on the crack development theory, and the real damage index was proposed. Then, through theoretical analysis and curve fitting, two kinds of seismic damage models— energy method and Park-Ang-W—were proposed, and the damage values were calculated to compare with the real damage values. Finally, the Park-Ang-W model was used to analyze the parameter expansion of 16 Abaqus wall models with different axial compression ratios μ and steel ratios ρ. The results show that the damage evaluation index based on crack development theory can effectively reflect the damage of fly ash foamed concrete walls. The accuracy of the energy method model is not high at the low number of cycles, and the error is less than 20% at the high number of cycles. The Park-Ang-W model has an error of approximately 10% at a high number of cycles, which better reflects the true damage of the specimen. The axial compression ratio μ has little effect on the wall damage, with a maximum effect range of 6.7%. Increasing the reinforcement ratio can effectively reduce the wall damage, with a maximum effect range of 12.6%. The results of the study provide a theoretical basis for the future application of fly ash foamed concrete in construction projects.

The focus of this study is to determine the optimum length of micro (average diameter less than 0.3 mm) and macro (average diameter greater than or equal to 0.3 mm) hemp fibers subjected to tensile loading in a cement paste mixture. Optimizing the length of the fibers to carry tensile loading for concrete members is important to minimize waste of hemp material and to provide the best performance. This study evaluated three water-cement ratios (w/c): 0.66, 0.49, and 0.42 (fc′ = 17.2, 24.1, and 27.6 MPa [2500, 3500, and 4000 psi], respectively). Because of the high cost of cement, replacement of cement with fly ash was also part of the program to determine if the addition of fly ash would have a negative impact on the performance of the hemp fibers. The results show that hemp micro- and macrofibers bonded to the cement matrix and carry higher tensile loads at higher w/c. Statistical analysis (regression modeling) shows that the optimum length for hemp macrofibers is 30 and 20 mm (1.18 and 0.79 in.) for microfibers.

In this study, low-carbon ultra-high-performance concrete (UHPC) was designed by adding fly ash-based mineral admixtures (SD-FA). The improved Andreasen & Andersen model was used to obtain SD-FA, which was then used to replace part of UHPC cement, to achieve the effect of low-carbon emission reduction. The effects of the composition and dosage of cement-based materials, the water-cement ratio, the composition of sand, the steel fiber content, and the lime-sand ratio on the properties of UHPC were studied, and the design of the batches was optimized. On this basis, the performance changes were analyzed at the micro level. The results show that when the 1~3 grade fly ash content after screening treatment is quantitative, the densest stacking is theoretically reached. The SD-FA optimized design improves the bulk density of UHPC and realizes the dense microstructure of UHPC. Under the optimal mixing ratio, its processability is guaranteed and the mechanical properties are enhanced.