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This study is focused on the punching strength of fiber-reinforced polymer (FRP) concrete slabs. The mechanical properties of reinforced concrete slabs are often constrained by their punching shear strength at the column connection regions. Researchers have explored the use of fiber-reinforced polymer reinforcement as an alternative to traditional steel reinforcement to address this limitation. However, current codes poorly calculate the punching shear strength of FRP-reinforced concrete slabs. The aim of this study was to create a robust model that can accurately predict its punching shear strength, thus improving the analysis and design of composite structures with FRP-reinforced concrete slabs. In this study, 189 sets of experimental data were collected, and six machine learning models, including linear regression, support vector machine, BP neural network, decision tree, random forest, and eXtreme Gradient Boosting, were constructed and evaluated based on goodness of fit, standard deviation, and root-mean-square error in order to select the most suitable model for this study. The optimal model obtained was compared with the models proposed by codes and the researchers. Finally, a model explainability study was conducted using SHapley Additive exPlanations (SHAP). The results showed that random forests performed best among all machine learning models and outperformed existing models suggested by codes and researchers. The effective depth of the FRP-reinforced concrete slabs was the most important and proportional to the punching shear strength. This study not only provides guidance on the design of FRP-reinforced concrete slabs but also informs future engineering practice.

In today’s world, concrete structures are exposed to various influences, including explosive actions. With the increasing use of fiber-reinforced concrete (FRC), it is essential to investigate its response to blast effects. As there are few studies on this topic worldwide, this research is dedicated to the question of how blast effects affect the damage and properties of six different types of reinforced concrete (RC) slabs. These samples differ in concrete classes (C30/37 and C50/60) and in the type of fibers added (steel and polypropylene). Visual inspections and non-destructive measurements are carried out before and after blasting. The damaged area of the concrete surface is determined by visual inspection, while non-destructive measurements evaluate parameters such as the rebound value of the Schmidt hammer, the electrical resistivity of the concrete, the velocity of the ultrasonic wave, and the dynamic modulus of elasticity. Equal amounts of explosives are applied to five of the RC slabs to enable a comparative analysis of the resulting damage. Based on the comparison of the measured data from these five RC slabs, conclusions are drawn regarding the effects of the explosive impacts on conventionally reinforced concrete slabs compared to those with added fibers. In addition, one of the RC slabs with steel fibers is exposed to approximately three times the amount of explosives to assess the extent of increased damage and to evaluate the suitability of military standards in the calculation of explosive charges for blasting RC elements with fibers.

In several areas worldwide, the high cost and shortage of natural resources have encouraged researchers and engineers to explore the serviceability and feasibility of using recycled aggregates in concrete mixtures, substituting a normal aggregate percentage. This technique has advantages for the environment by reducing the accumulation of waste materials, while it impacts the fresh and hardened concrete performances, reducing workability, flexural strength, compressive strength, and tensile strength. However, most studies have investigated the influence of replacing normal aggregates with waste aggregates on the concrete mechanical properties without examining the impact of using waste materials on concrete structural performance. The aim of this research is to investigate the effect of replacing 75% of sand volume with polyvinyl chloride (PVC) fine waste aggregates on the performance of reinforced concrete slabs. Different thicknesses of the concrete layer (0%, 25%, 50%, and 100% of slab thickness) containing PVC fine waste aggregates are investigated. Based on the reductions in the toughness and flexural strength capacity due to incorporating 75% PVC fine aggregate dosage, two approaches are used to strengthen the slabs with 75% PVC fine aggregates. The first approach is adding polyvinyl alcohol (PVA) to the PVC fine aggregate concrete mix to improve the mechanical properties of the concrete. The PVA increases the water viscosity in the concrete, which reduces the dry out phenomenon. With that said, the PVA modified fresh concrete does enable the use of the limits of the PVC fine aggregate dosage for high dosage plastic aggregate concrete. The second approach uses two fiber wire mesh layers as an additional reinforcement in the tested slab. Results show that the PVC-30 slab exhibits an 8% decrease in total area toughness compared to the control (Con) slab, while for PVC-60 slab toughness, the total area shows 26% less. Additionally, the inclusion of PVA in the concrete with 75% PVC plastic waste fine aggregate replacement greatly influences the pre-and post-cracking ductile performance among other slabs, representing that using PVA with higher contents might increase the flexural performance. Therefore, due to the substantial effect of PVA material on the concrete flexural performance, it is proposed to utilize PVA with an optimum PCV fine aggregate dosage in the concrete mix.