Investigation of the parameters affecting the behavior of RC beams strengthened with FRP


Sengun K., ARSLAN G.

FRONTIERS OF STRUCTURAL AND CIVIL ENGINEERING, vol.16, no.6, pp.729-743, 2022 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 16 Issue: 6
  • Publication Date: 2022
  • Doi Number: 10.1007/s11709-022-0854-9
  • Journal Name: FRONTIERS OF STRUCTURAL AND CIVIL ENGINEERING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, ABI/INFORM, Agricultural & Environmental Science Database, Art Source, Compendex, INSPEC, Civil Engineering Abstracts
  • Page Numbers: pp.729-743
  • Keywords: carbon, glass, strengthening, shear strength, reinforced concrete beam, fiber reinforced polymer, REINFORCED-CONCRETE BEAMS, SHEAR CAPACITY, TRANSVERSE STEEL, T-BEAMS, CFRP, POLYMER, PERFORMANCE, DESIGN, STRAIN, STRIPS
  • Yıldız Technical University Affiliated: Yes

Abstract

Three-point bending tests were carried out on nineteen Reinforced Concrete (RC) beams strengthened with FRP in the form of completely wrapping. The strip width to spacing ratios, FRP type, shear span to effective depth ratios, the number of FRP layers in shear, and the effect of stirrups spacing were the parameters investigated in the experimental study. The FRP contribution to strength on beams having the same strip width to spacing ratios could be affected by the shear span to effective depth ratios and stirrups spacing. The FRP contributions to strength were less on beams with stirrups in comparison to the tested beams without stirrups. Strengthening RC beams using FRP could change the failure modes of the beams compared to the reference beam. In addition to the experimental study, a number of equations used to predict the FRP contribution to the shear strength of the strengthened RC beams were assessed by using a limited number of beams available in the literature. The effective FRP strain is predicted by using test results, and this prediction is used to calculate the FRP contribution to shear strength in ACI 440.2R (2017) equation. Based on the statistical values of the data, the proposed equation has the lowest coefficient of variation (COV) value than the other equations.