A novel design model for predicting the shear resistance of reinforced concrete beams strengthened with EBR-CFRP systems

• Autor(a) principal: Mohammadi, Amir Hossein
• Data de Publicação: 2024
• Outros Autores: Barros, Joaquim A. O., Sena-Cruz, José
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: https://hdl.handle.net/1822/88670
• topic: Design model; Shear strengthening; Reinforced concrete beams; Externally bonded reinforcements; FRP; Reliability analysis; Engenharia e Tecnologia::Engenharia Civil

Shear resistance prediction of reinforced concrete (RC) beams strengthened with externally bonded reinforcements (EBR) is a challenging task due to the complex nature of shear resisting mechanisms and their intricate interaction. Existing design models often overlook these dependencies, leading to significant variations in prediction accuracy. In this paper, a design model is proposed by integrating the most relevant shear resisting mechanisms based on the evidence demonstrated by a large database of experimental results from RC beams shear strengthened with wet layup carbon fibre reinforced (CFRP) sheets applied according to the EBR technique. The developed approach integrates the simplified modified compression field theory (SMCFT) with a regressionbased model. A global sensitivity analysis was conducted according to which closed form equations were derived to obtain the tensile stress factor in cracked concrete and the inclination angle of the critical diagonal crack. A reliability analysis is carried out, and resistance reduction factors are achieved for different levels of reliability index. The database, composed of 284 RC beams shear strengthened with EBR-CFRP technique, is utilized to validate the proposed model, and compare its performance against some well-established existing design models. The results show that the proposed model, with an adequate framework for its use on design practice, outperforms the other considered models.