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  • 标题:Prediction of punching shear capacities of two-way concrete slabs reinforced with FRP bars
  • 本地全文:下载
  • 作者:Ibrahim M. Metwally
  • 期刊名称:HBRC Journal
  • 印刷版ISSN:1687-4048
  • 出版年度:2013
  • 卷号:9
  • 期号:2
  • 页码:125-133
  • DOI:10.1016/j.hbrcj.2013.05.009
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractWhere corrosion of steel reinforcement is a concern, fiber-reinforced polymer (FRP) reinforcing bar or grid reinforcement provides an alternative reinforcement for concrete flat slabs. The existing provisions for punching of slabs in most international design standards for reinforced concrete are based on tests of steel reinforced slabs. The elastic stiffness and bonding characteristics of FRP reinforcement are sufficiently different from those of steel to affect punching strength [1]. This paper evaluates the punching shear strength of concrete flat slabs reinforced with different types of fiber-reinforced polymer (FRP). A total of 59 full-size slabs were constructed and tested collected from the literature of FRP bars reinforced concrete slabs. The test parameters were the amount of FRP reinforcing bars,Young’s modulusof FRP bars, slab thickness, loaded areas and concrete compressive strength. The experimental punching shear strengths were compared with the available theoretical predictions, including the ACI 318 Code, BS 8110 Code, ACI 440 design guidelines, and a number of models proposed by some researchers in the literature. Two approaches for predicting the punching strength of FRP-reinforced slabs are examined. The first is an empirical new model which is considered as a modification of El-Gamal et al. [2] model. The second is a Neural Networks Technique; which has been developed to predict the punching shear capacity of FRP reinforced concrete slabs. The accuracies of both methods were evaluated against the experimental test data. They attained excellent agreement with available test results compared to the existing design formulas.
  • 关键词:KeywordsPunching shearConcrete slabsFRP barsNeural networks
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