Cracking and Fiber Debonding Identification of Concrete Deep Beams Reinforced with C-FRP Ropes against Shear Using a Real-Time Monitoring System

A Deep Learning Approach for Autonomous Compression Damage Identification in Fiber-Reinforced Concrete Using Piezoelectric Lead Zirconate Titanate Transducers

Effective damage identification is paramount to evaluating safety conditions and preventing catastrophic failures of concrete structures. Although various methods have been introduced in the literature, developing robust and reliable structural health monitoring (SHM) procedures remains an open research challenge. This study proposes a new approach utilizing a 1-D convolution neural network to identify the formation of cracks from the raw electromechanical impedance (EMI) signature of externally bonded piezoelectric lead zirconate titanate (PZT) transducers. Externally bonded PZT transducers were used to determine the EMI signature of fiber-reinforced concrete specimens subjected to monotonous and repeatable compression loading. A leave-one-specimen-out cross-validation scenario was adopted for the proposed SHM approach for a stricter and more realistic validation procedure. The experimental study and the obtained results clearly demonstrate the capacity of the introduced approach to provide autonomous and reliable damage identification in a PZT-enabled SHM system, with a mean accuracy of 95.24% and a standard deviation of 5.64%.

Behavior of non-prismatic RC beams with conventional steel and green GFRP rebars for sustainable infrastructure

This study presents an experimental and finite element analysis of reinforced concrete beams with solid, hollow, prismatic, or non-prismatic sections. In the first part, a total of six beams were tested under four-point monotonic bending. The test matrix was designed to provide a comparison of structural behavior between prismatic solid and hollow section beams, prismatic solid and non-prismatic solid section beams, and prismatic hollow and non-prismatic hollow section beams. The intensity of shear was maximum in the case of prismatic section beams. The inclusion of a tapered section lowered the demand for shear. In the second part, Nonlinear Finite Element Modeling was performed by using ATENA. The adopted modeling strategy resulted in close agreement with experimental crack patterns at ultimate failure. However, the ultimate failure loads predicted by nonlinear modeling were generally higher than their corresponding experimental results. Whereas in the last part, the developed models were further extended to investigate the effect of the strength of concrete and ratio of longitudinal steel bars on the ultimate load-carrying capacity and cracking behavior of the reinforced concrete beams with solid, hollow, prismatic, or non-prismatic sections. The ultimate loads for each beam predicted by the model were found to be in close agreement with experimental results. Nonlinear modeling was further extended to assess the effects of concrete strength and longitudinal reinforcement ratio on failure patterns and ultimate loads. The parametric study involved beams reinforced with glass fiber-reinforced polymer (GFRP) bars against shear and flexural failure. In terms of ultimate load capacities, diagonal cracking, and flexural cracking, beams strengthened with GFRP bars demonstrated comparable performance to the beams strengthened with steel bars.