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논문 기본 정보

자료유형
학술저널
저자정보
Lan Chung (Dankook University) Moo-Won Hur (Dankook University) Taewon Park (Dankook University)
저널정보
한국콘크리트학회 International Journal of Concrete Structures and Materials International Journal of Concrete Structures and Materials Vol.13 No.2
발행연도
2019.2
수록면
183 - 193 (11page)

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초록· 키워드

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Aging and structural deterioration under severe environments are major causes of damage in reinforced concrete (RC) structures, such as buildings and bridges. Degradations 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 the strengthening and rehabilitation of RC structures have been developed over the past several decades. Recently, FRP composite materials have emerged as a cost-effective alternative to 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 the FRP retrofit for circular type concrete columns under the framework of the adaptive neuro-fuzzy inference system (ANFIS). Retrofit ratio, strength of existing concrete, thickness, number of layer, stiffness, ultimate strength of fiber, and size of specimens are used as input parameters to predict strength, strain, and stiffness of the post-yielding modulus. These proposed ANFIS models show reliable increased accuracy in predicting the constitutive properties of concrete retrofitted by FRP, compared to the constitutive models suggested by other researchers.

목차

Abstract
1 Introduction
2 Adaptive Neuro-Fuzzy Inference System
3 Prediction of Retrofitting Effects through the Neuro-Fuzzy System
4 Verification of the Outputs of the Neuro-Fuzzy System
5 Conclusions
References

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