International Concrete Abstracts Portal

Engineered cementitious composites (ECC), a prominent innovation in the realm of concrete materials in recent years, contain a substantial amount of cement in their composition, thereby resulting in a significant environmental impact. To enhance the environmental sustainability of ECC, it is plausible to substitute a large portion of cement in the composition with fly ash, a by-product of coal-fired power plants. In recent years, there has been increased research in ECC containing high-volume fly ash (HVFA) binders and its wider application in construction practices. In this particular context, it becomes imperative to review the role of the HVFA binder in ECC. This review first examines the effects of incorporating an HVFA binder in ECC on fiber dispersion and fiber/matrix interface behavior. Additionally, mechanical properties, including the compressive strength, tensile behavior, and cracking behavior under loading, as well as durability performances of HVFA-based ECC under various exposure conditions, are explored. At last, the review summarizes the research needs pertaining to HVFA-based ECC, providing valuable guidance for future endeavors in this field.

The production of carbonated aggregates from Class F fly ash (FA) is challenging due to its low calcium content, typically less than 10%. This study investigates the production of carbonated alkali-activated aggregates using FA and calcium carbide sludge (CCS). Sodium hydroxide was used as an activator and examined the effects of autoclave treatment on the properties of these aggregates. The optimal mixture, comprising 70% FA and 30% CCS, achieved a single aggregate strength of >5 MPa in autoclave carbonated (AC) aggregates, comparable to the strength obtained after 14 days of water curing in without autoclave carbonated (WAC) aggregates. Both AC and WAC aggregates exhibited a bulk density of 790 to 805 kg/m³ and CO₂ uptake of 12.5% and 13.3% in AC and WAC aggregates, respectively. FE-SEM and FT-IR analysis indicated the formation C-A-S-H gel in noncarbonated aggregates, while calcite and vaterite, along with N-A-S-H gel, formed in carbonated aggregate. Concrete incorporating AC and WAC aggregates exhibit compressive strengths of 39 and 38 MPa, with concrete density of 2065 kg/m³ and 2085 kg/m³, respectively. Furthermore, AC and WAC aggregate concrete showed a reduction in CO₂ emission of 18% and 31%, respectively, compared to autoclave noncarbonate (ANC) aggregate concrete. These findings highlight the potential of producing carbonated alkali-activated aggregates from FA and CCS as sustainable materials for construction applications.

This investigation attempted to analyze the environmental impact of fibers, including their effect on the cost and durability of concrete mixtures, especially given the variety of fibers that are available in the market. Five types of fibers (polypropylene [PP], glass, basalt, polyvinyl alcohol [PVA], and steel) possessing different aspect ratios were considered in this study. The concrete mechanical properties—including the resistance to sorptivity, heat, and freezing- and-thawing cycles—were evaluated. Test results showed that the best environmental/cost/durability indicator was achieved for concrete prepared with 0.25% PVA or PP fibers by volume. This indicator gradually degraded with the use of basalt, glass, and steel fibers because of higher cost and greenhouse gas emissions generated during the fiber manufacturing. The use of PVA fibers significantly enhanced the resistance to heat and freezing-and-thawing cycles, while the least-performing concrete contained basalt fibers with relatively reduced flexural properties and increased sorptivity.

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. Fly ash (FA)-based GPC displays noticeable variability in its mechanical properties due to differences in mixture design ratios and curing methods. To address this challenge, the authors 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 (ANNs) were employed for compressive strength modeling. The developed ANN model underwent rigorous evaluation using statistical metrics such as R-values, R2 values, and mean squared 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 data sets 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 to 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.

Coastal reinforced concrete bridges are critical infrastructures, yet they face significant threats from corrosion due to saline environments and extreme loads like wave-induced forces and seismic events. This state-of-the-art review examines the resilience of corrosion-damaged RC bridges under such conditions. It compiles advanced methodologies and technological innovations to assess and enhance durability and safety. Key highlights include synthesizing loss estimation models with advanced reliability methods for a robust resilience assessment framework. Analyzing catastrophic bridge failures and environmental deterioration, the review underscores the urgent need for innovative materials and protective technologies. It emphasizes advanced analytical models like Performance-Based Earthquake Engineering (PBEE) and Incremental Dynamic Analysis (IDA) to evaluate combined impacts. The findings advocate for engineered cementitious composites (ECC) and advanced sensor systems for improved real-time monitoring and resilience. Future research should focus on developing comprehensive resilience models accounting for corrosion, seismic, and wave-induced loads to enhance infrastructure safety and sustainability.