Global Energy Balance-Based Debonding Modeling of NSM FRP-Strengthened Concrete Beam

被引:3
作者
Hoque, N. [1 ,2 ]
Jumaat, M. Z. [2 ]
Sulong, N. H. R. [2 ]
机构
[1] Chittagong Univ Engn & Technol, Dept Civil Engn, Chittagong 4349, Bangladesh
[2] Univ Malaya, Fac Engn, Dept Civil Engn, Kuala Lumpur 50603, Malaysia
关键词
Debonding; Fiber-reinforced polymer; Fracture energy; Global energy balance; Near surface mounted; REINFORCED POLYMER BARS; END COVER SEPARATION; RC BEAMS; FLEXURAL BEHAVIOR; CFRP; FAILURE; PLATE; PERFORMANCE; PREDICTION; BOND;
D O I
10.1061/(ASCE)CC.1943-5614.0000976
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
An important advantage of the near surface mounted (NSM) technique for concrete beam strengthening over the externally bonded reinforcement technique is its higher resistance to debonding failures. Despite the increased resistance, debonding failures do still occur on NSM strengthened beams. The aim of this paper is to investigate the possibility of using a global energy balance based fracture mechanics model for NSM strengthened beams. The methodology includes determining the available energy for the propagation of the interface flaw. Debonding failure occurs when the available energy for interface flaw propagation reaches the Mode I fracture energy of the concrete, as this is the weakest material of the concrete-fiber reinforced plastic (FRP) composite system. The validation using published experimental results demonstrates that the model is capable of predicting possible modes of debonding failure for NSM FRP strengthened reinforced concrete beams and for any material and geometric properties of concrete beams, adhesive, and FRP. Validation against published experimental results yields a satisfactory performance of the model. The mean ratio between simulated to experimental failure loads for NSM strengthened beams is 0.99 with a standard deviation of 0.09. (C) 2019 American Society of Civil Engineers.
引用
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页数:17
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  • [32] Interpretable Machine Learning-Based Prediction Model for Concrete Cover Separation of FRP-Strengthened RC Beams
    Zheng, Sheng
    Hu, Tianyu
    Yu, Yong
    [J]. MATERIALS, 2024, 17 (09)
  • [34] Analysis on end debonding failure of FRP strengthened RC beams based on a 'beam segment' model
    Ye, Su-Rong
    Sun, Yan-Hua
    Xiong, Guang-Jing
    [J]. Gongcheng Lixue/Engineering Mechanics, 2012, 29 (02): : 101 - 106
  • [35] A deformability-based mechanical model for predicting shear strength of FRP-strengthened RC beams failed in concrete cover separation
    Zhou, Binbin
    Gu, Leming
    Wu, Ruo-Yang
    Li, Yao
    Sheng, Jie
    Liu, Yangqing
    Lu, Siqi
    [J]. ENGINEERING FRACTURE MECHANICS, 2024, 311
  • [36] Modeling of Tension Stiffening Behavior in FRP-Strengthened RC Members Based on Rigid Body Spring Networks
    Dai, Jian-Guo
    Ueda, Tamon
    Sato, Yasuhiko
    Nagai, Kohei
    [J]. COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, 2012, 27 (06) : 406 - 418
  • [37] Study of fracture evolution in FRP-strengthened reinforced concrete beam under cyclic load by acoustic emission technique: An integrated mechanical-acoustic energy approach
    Selman, Efe
    Ghiami, Amir
    Alver, Nine
    [J]. CONSTRUCTION AND BUILDING MATERIALS, 2015, 95 : 832 - 841
  • [38] Cohesive Model-Based Approach for Fatigue Life Prediction of Reinforced-Concrete Structures Strengthened with NSM FRP
    Chen, Cheng
    Cheng, Lijuan
    [J]. JOURNAL OF COMPOSITES FOR CONSTRUCTION, 2014, 18 (02)
  • [39] Data-driven prediction of FRP strengthened reinforced concrete beam capacity based on interpretable ensemble learning algorithms
    Zhang, Shu-Ying
    Chen, Shi-Zhi
    Jiang, Xin
    Han, Wan-Shui
    [J]. STRUCTURES, 2022, 43 : 860 - 877