지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국계산역학회 Computers and Concrete, An International Journal Computers and Concrete, An International Journal Vol.19 No.3
- 발행연도
- 2017.1
- 수록면
- 233 - 241 (9page)
이용수
초록· 키워드
오류제보하기
During the last two decades, CFRP have been extensively used for repair and rehabilitation of existing structures as well as in new construction applications. For rehabilitation purposes CFRP are currently used to increase the load and the energy absorption capacities and also the shear strength of concrete columns. Thus, the effect of CFRP confinement on the strength and deformation capacity of concrete columns has been extensively studied. However, the majority of such studies consider empirical relationships based on correlation analysis due to the fact that until today there is no general law describing such a hugely complex phenomenon. Moreover, these studies have been focused on the performance of circular cross section columns and the data available for square or rectangular cross sections are still scarce. Therefore, the existing relationships may not be sufficiently accurate to provide satisfactory results. That is why intelligent models with the ability to learn from examples can and must be tested, trying to evaluate their accuracy for composite compressive strength prediction. In this study the forecasting of wrapped CFRP confined concrete strength was carried out using different Data Mining techniques to predict CFRP confined concrete compressive strength taking into account the specimens’ cross section: circular or rectangular. Based on the results obtained, CFRP confined concrete compressive strength can be accurately predicted for circular cross sections using SVM with five and six input parameters without spending too much time. The results for rectangular sections were not as good as those obtained for circular sections. It seems that the prediction can only be obtained with reasonable accuracy for certain values of the lateral confinement coefficient due to less efficiency of lateral confinement for rectangular cross sections.
목차
등록된 정보가 없습니다.
참고문헌 (62)
참고문헌 신청
Aleksander, I. / 1990 / An Introduction to Neural Computing / Chapman & Hall
Ben-Hur, A. / 2010 / A User’s Guide to Support Vector Machines / Humana Press
Benzaid, R. / 2013 / Circular and square concrete columns externally confined by CFRP composite:Experimental investigation and effective strength models / InTech :167~201
Berk, R. A. / 2008 / Statistical Learning from a Regression Perspective / Springer-Verlag
Berthet, J. F. / 2005 / Compressive behaviour of concrete externally confined by composite jackets / Constr. Build. Mater. 19(3):223~232
Ben-Hur, A. / 2010 / A User’s Guide to Support Vector Machines / Humana Press
Benzaid, R. / 2013 / Circular and square concrete columns externally confined by CFRP composite:Experimental investigation and effective strength models / InTech :167~201
Berk, R. A. / 2008 / Statistical Learning from a Regression Perspective / Springer-Verlag
Berthet, J. F. / 2005 / Compressive behaviour of concrete externally confined by composite jackets / Constr. Build. Mater. 19(3):223~232
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