• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.2
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• pp.175-186
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• 2006

Strength method for determining nominal moment capacity of reinforced concrete members is also assumed to be suitable for strengthened members with FRP system. If the internal tensile forces of the strengthened member from steel and FRP is insufficient, the FRP system strain might become greater than its ultimate tensile strain which makes the strength method a contradiction and unapplicable. The experimental results of 27 strengthened beams with carbon fiber sheets which have relatively lower tensile forces from steel and FRP show that not only concrete compressive strain is lower than 0.003 but also measured ultimate moment was lower than nominal moment using the strength method.

• Journal of the Korea Concrete Institute
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• v.22 no.1
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• pp.19-27
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• 2010

Aging and severe environments are major causes of damage in reinforced concrete (RC) structures such as buildings and bridges. Deterioration such as concrete cracks, corrosion of steel, and deformation of structural members can significantly degrade the structural performance and safety. Therefore, effective and easy-to-use methods are desired for repairing and strengthening such concrete structures. Various methods for strengthening and rehabilitation of RC structures have been developed in the past several decades. Recently, FRP composite materials have emerged as a cost-effective alternative to the conventional materials for repairing, strengthening, and retrofitting deteriorating/deficient concrete structures, by externally bonding FRP laminates to concrete structural members. The main purpose of this study is to investigate the effectiveness of adaptive neuro-fuzzy inference system (ANFIS) in predicting behavior of circular type concrete column retrofitted with FRP. To construct training and testing dataset, experiment results for the specimens which have different retrofit profile are used. Retrofit ratio, strength of existing concrete, thickness, number of layer, stiffness, ultimate strength of fiber and size of specimens are selected as input parameters to predict strength, strain, and stiffness of post-yielding modulus. These proposed ANFIS models show reliable increased accuracy in predicting constitutive properties of concrete retrofitted by FRP, compared to the constitutive models suggested by other researchers.