Numerical and analytical study on the punching shear capacity prediction for eccentrically loaded flat slabs with openings

• Flat slabs with different depths, opening locations, and loading eccentricity. • Numerical results were also compared to three codes prediction. • Full and detailed structural behavior was provided. • Eccentricity and reinforcement ratio modification parameters were introduced. • The theoretical model was verified using literature data with an R 2 value of 0.98. The punching shear behavior of interior flat slab was examined in this study in the absence of shear reinforcement using numerical and analytical techniques. The effect of sensitive parameters was investigated and their influence was examined and reported including the opening existence and location, loading eccentricity, and slab height. The effect of the reinforcement ratio is neglected in most of the literature models and code provisions with the influence of loading eccentricity being addressed inappropriately. Therefore, this study adopted the nonlinear finite element analysis (NLFEA) method for the numerical part where the flat slab punching shear behavior was studied in detail. Results were compared in their behavior at both cracking and ultimate stages, absorbed energy, elastic and plastic stiffnesses, and general trend lines were provided. The effect of the reinforcement ratio was assessed indirectly with slabs of similar reinforcement area and different slab effective depths (65, 95, 125, and 155) mm where a 25 mm concrete cover was used. In addition, the NLFEA punching shear capacity results were compared with three international codes (American Concrete Institute (ACI318-119), EuroCode (EC2), and Model Code (MC2010)) to highlight their potential predictability and weakness points. It was found that the MC2010 has the most conservative prediction, followed by the EC2 and the ACI318-19 predictions. Therefore, two modification parameters were proposed for the ACI318-19 punching shear capacity calculation with R 2 value of 0.98. The modified version of the ACI318-19 was validated using experimental data from the literature proving a high prediction capability.