International Concrete Abstracts Portal

Prolonged neutron irradiation can damage concrete biological shields, particularly when nuclear power plants extend reactor lifespans. Retrofitting biological shields with thin and highly efficient neutron shields may limit neutron damage. Portland cement mortars amended with boron carbide and polyethylene powders were assessed for neutron attenuation. Shielding performance was compared to concrete with a similar design and coarse aggregate as a biological shield at an operational nuclear plant. Boron carbide enhanced the shielding performance of specimens under the full energy spectrum of the neutron source. Boron carbide and polyethylene synergistically enhanced neutron attenuation under a purely high-energy neutron flux. Engineered thin composite mortars needed 90% less thickness to achieve similar or better shielding efficiency as the concrete in a typical biological shield under the test conditions. Isothermal calorimetry, compressive strength, and thermal expansion results indicate that mixture design parameters of thin shields can be adjusted to achieve adequate structural properties without diminishing constructability or structural performance.

Engineered cementitious composites (ECC) represent a significant innovation in construction materials due to their exceptional flexibility, tensile strength, and durability, surpassing traditional concrete. This review systematically examines the composition, mechanical behaviour, and real-world applications of ECC, with a focus on how fiber reinforcement, mineral additives, and micromechanical design improve its structural performance. The present study reports on the effects of various factors, including different types of mineral admixtures, aggregate sizes, fiber hybridization, and specimen dimensions. Key topics include ECC’s strain-hardening properties, its sustainability, and its capacity to resist crack development, making it ideal for high-performance infrastructure projects. Additionally, the review discusses recent advancements in ECC technology, such as hybrid fibre reinforcement and the material’s growing use in seismic structures. The paper also addresses the primary obstacles, including high initial costs and the absence of standardized specifications, while proposing future research paths aimed at optimizing ECC’s efficiency and economic viability.

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.

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.

The concrete industry is increasingly adopting the production of environmentally sustainable green concrete. Using recycled coarse aggregate (RCA) produced from demolished concrete infrastructures and waste tire-derived crumb rubber (CR) in the concrete mixture provides a sustainable construction practice and can enhance structural performance. This study investigates the uniaxial compressive behavior of concrete columns composed of RCA, CR, and polypropylene (PP) fiber. A total of 26 columns 150 x 150 x 950 mm in size were tested under uniaxial compression loading. Test parameters included longitudinal reinforcement ratio (0, 1.4, and 2.0%), tie spacing (75 and 150 mm), CR content (0, 5, 10, and 15% of the volume of natural fine aggregate), and percentage of PP fiber (0 and 0.5% of the volume of the total mixture) with 30% RCA replacement (by weight of natural coarse aggregate). The compressive behavior, failure mechanism, influence of longitudinal and transverse reinforcement, dilation, ductility, and toughness were examined. This study demonstrated that incorporating fiber into the concrete made with RCA and CR waste materials improved the axial capacity, resulting in fiber-reinforced rubberized recycled concrete (FRRC) columns with enhanced ductility and toughness. These findings support the development of sustainable concrete for structural columns, justifying their applicability to existing design codes.