Glass fiber-reinforced polymer (GFRP) reinforcements are useful alternatives to traditional steel bars in concrete structures, particularly in vertical structural elements such as columns, as they are less prone to corrosion, and impart increasing strength and endurance of buildings. There is limited research on the finite element analysis (FEA) of the structural behavior of hollow glass fiber-reinforced polymer reinforced concrete (GFRPRC) columns. The hollow portion can be used for the service duct and for reducing the self-weight of the members. Numerical analysis of the compressive response of circular hollow concrete columns reinforced with GFRP bars and spirals is performed in this study. This article aims to investigate the axial behavior of hollow GFRP concrete columns and compare it with that of solid steel reinforced concrete (RC) columns as well as hollow steel RC columns. The Abaqus software is used to construct finite element models. After calibration of modeling using an experimental test result as a control model, a parametric study is conducted. The columns with the same geometry, loading, and boundary conditions are analyzed in the parametric study. It is resulted that the hollow GFRP concrete columns provide a greater confinement effect than the solid steel RC columns. The average variation in the ultimate axial load-carrying capacities of the experimental results, from that of the FEA values, is noted to be only 3.87%, while the average difference in the corresponding deformations is 7.08%. Moreover, the hollow GFRP concrete columns possess greater axial load and deformation capacities compared with the solid steel RC columns.

This paper presents the results of a deep neural network (DNN) model predicting the axial load-carrying capacity of fire-damaged concrete square and rectangular reinforced concrete columns subsequently repaired using carbon fiber-reinforced polymer (CFRP) composites. An experimental database comprising 143 column specimen samples was collected from the literature. Thirteen parameters were noted, including Length of Columns (mm), Width of Columns (mm), Corner Radius (mm), Height of Column (mm), Initial Compressive Strength of Concrete (MPa), Initial Tensile Strength of Steel (MPa), Longitudinal Reinforcement Ratio (As/Ag, %), Temperature of Fire (°C), Fire Exposure Time (Minutes), Number of Layers of CFRP(Count), Thickness of CFRP (mm), and Tensile Elastic Modulus of CFRP (GPa). These parameters served as inputs for the model, with the final axial compressive strength of the CFRP-repaired column considered as the target/output. DNN models were calibrated for numerous numbers of neurons in the hidden layers to achieve optimization. The proposed DNN model demonstrated strong agreement with the experimental database, exhibiting an overall correlation factor (R) of 0.99946. The predicted outcomes of the proposed model closely align with the experimental findings, as evidenced by a thorough comparison with prior experimental investigations. Consequently, this model holds potential value for engineers seeking speedy assistance in repairing fire-damaged structures using CFRP composites.

In this work, the synergistic effects of mineral admixtures and advanced mixing processes are systematically accounted for steel fibre-reinforced recycled aggregate concrete (SFR-RAC). It studies the improvement of performance optimization in SFR-RAC, inherently weak ITZ by adding 0.5% hooked steel fibres and replacing cement with ground granulated blast furnace slag (25–50%), fly ash (20–40%) and silica fume (7–14%). The efficiency of double-mixing (DM) and triple-mixing (TM) procedures were comprehensively evaluated. Results showed that mineral admixtures could improve mortar-aggregate interface bond, and the triple-mix technique contributed to such improvement. The maximum performance was observed for the combination of 7%SF with triple mixing (7%SF-TM), which presented increased compressive, tensile and flexural strengths by 7–18%, 12–29%, and 16–31% respectively. The durability was significantly improved, and the water resistance could increase by 53% with addition of 7%SF-TM, chloride penetration depth reduced by 86% when incorporated with 25%GGBS-TM, acid attack decreased by 84% with addition of 14%SF-TM. Microstructural analysis (SEM, XRD) confirmed that these enhancements stem from a denser matrix and refined ITZ due to increased C–S–H formation. This study confirms that the strategic integration of fibre reinforcement, pozzolanic admixtures and optimized mixing protocols presents a viable pathway for producing sustainable concrete from construction waste.

This study investigates the mechanical and durability properties of Self-Compacting Concrete (SCC) incorporating bentonite clay and marble dust as partial cement replacements. Bentonite clay, a natural pozzolanic material sourced from Jehengirah (Swabi district), was evaluated for its physical properties, including specific gravity, setting time, and soundness. Results indicate that bentonite has a lower specific gravity and shorter initial setting time compared to Ordinary Portland Cement (OPC), though the final setting time remains similar. A total of nine SCC mix designs were prepared, replacing cement with up to 20% marble dust and 20% bentonite clay by weight. The study focuses on assessing compressive strength, split tensile strength, and durability characteristics compared to conventional SCC. Findings reveal that exceeding 20% cement replacement with pozzolanic materials leads to a notable reduction in compressive strength. However, while the modulus of rupture at 28 days is lower than conventional concrete, the flexural strength relative to compressive strength shows improvement.