Reliable Machine Learning Model for Shear Strength of Reinforced Concrete Beams Strengthened Using FRP Jackets

Abstract

All over the world, externally bonded fiber-reinforced polymer systems used to strengthen concrete elements improve building sustainability. However, reports issued by the American Concrete Institute Committee 440 called for heavy scrutinizing before actual field implementation. The very limited number of proposed equations lacks reliability and accuracy. Thus, further investigation in this area is needed. In addition, machine learning techniques are being implemented successfully in developing strength models for complex problems. This study aims to provide a reliable machine learning model based on an experimental database. The proposed model was developed and validated against the experimental database and the very limited models in the literature. The model showed improved agreement with the experimental results compared to the previous models.

Nuclear Radiation Shielding Capabilities of Fiber-Reinforced Concrete: a case study Hybrid-Polypropylene-Steel

“…Fibers increase the concrete strength and delay the crack propagation [1]- [3]. The mechanical behavior of hybrid concrete using a mix of steel-polypropylene fiber has been investigated in previous studies [1][2][3]. In many applications concretes is exposed to radiation or elevated temperature [4].…”