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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 국제구조공학회 Steel and Composite Structures, An International Journal Steel and Composite Structures, An International Journal Vol.33 No.2
- 발행연도
- 2019.1
- 수록면
- 181 - 194 (14page)
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초록· 키워드
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This paper presents an efficient approach to generate a new empirical formula to predict the axial compression capacity (ACC) of circular concrete-filled tube (CCFT) columns using the artificial neural network (ANN). A total of 258 test results extracted from the literature were used to develop the ANN models. The ANN model having the highest correlation coefficient (<i>R</i>) and the lowest mean square error (<i>MSE</i>) was determined as the best model. Stability analysis, sensitivity analysis, and a parametric study were carried out to estimate the stability of the ANN model and to investigate the main contributing factors on the ACC of CCFT columns. Stability analysis revealed that the ANN model was more stable than several existing formulae. Whereas, the sensitivity analysis and parametric study showed that the outer diameter of the steel tube was the most sensitive parameter. Additionally, using the validated ANN model, a new empirical formula was derived for predicting the ACC of CCFT columns. Obviously, a higher accuracy of the proposed empirical formula was achieved compared to the existing formulae.
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참고문헌 (64)
참고문헌 신청
Abed, F. / 2013 / Experimental and numerical investigations of the compressive behavior of concrete filled steel tubes(CFSTs) / J. Constr. Steel Res 80:429~439
2011 / ACI 318-08, Building Code Requirements for Structural Concrete and Commentary (ACI 318-08)
Adeli, H. / 2001 / Neural networks in civil engineering : 1989-2000 / Comput. -Aided Civil Infra. Eng 16(2):126~142
Adeli, H. / 1997 / Neural network model for optimization of cold-formed steel beams / J. Struct. Eng 123(11):1535~1543
AISC Committee / 2010 / Specification for structural steel buildings (ANSI/AISC 360-10) / American Institute of Steel Construction
2011 / ACI 318-08, Building Code Requirements for Structural Concrete and Commentary (ACI 318-08)
Adeli, H. / 2001 / Neural networks in civil engineering : 1989-2000 / Comput. -Aided Civil Infra. Eng 16(2):126~142
Adeli, H. / 1997 / Neural network model for optimization of cold-formed steel beams / J. Struct. Eng 123(11):1535~1543
AISC Committee / 2010 / Specification for structural steel buildings (ANSI/AISC 360-10) / American Institute of Steel Construction
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