Artificial intelligence techniques for prediction of the capacity of RC beams strengthened in shear with external FRP reinforcement

被引:53
|
作者
Perera, Ricardo [1 ]
Arteaga, Angel [2 ]
De Diego, Ana [2 ]
机构
[1] Tech Univ Madrid, Dept Struct Mech, Madrid 28006, Spain
[2] CSIC, Eduardo Torroja Inst Construct Sci, Madrid 28033, Spain
关键词
Shear strengthening; FRP; Reinforced concrete; Neural networks; Genetic algorithms; BACKPROPAGATION NEURAL NETWORKS; CONCRETE BEAMS; STRUCTURAL SYSTEMS; OPTIMAL-DESIGN;
D O I
10.1016/j.compstruct.2009.10.027
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
The prediction of the shear capacity of reinforced concrete beams retrofitted in shear by means of externally bonded FRP is very complex as demonstrate the studies carried out up to date. As alternative to the conventional methods two approaches based on artificial intelligence are proposed for the first time. Firstly, the use of neural networks as a means of predicting shear capacity without the need of using complex models and, secondly, the use of genetic algorithms as a means of determining suitably how the shear mechanism works. Predictions obtained with both approaches are compared to experimental values. (C) 2009 Elsevier Ltd. All rights reserved.
引用
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页码:1169 / 1175
页数:7
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