Steel and Composite Structures

  • 제39권3호
  • /
  • Pages.319-335
  • /
  • 2021
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  • 1229-9367(pISSN)
  • /
  • 1598-6233(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Improving the axial compression capacity prediction of elliptical CFST columns using a hybrid ANN-IP model

  • Tran, Viet-Linh (Department of Civil and Environmental Engineering, Sejong University) ;
  • Jang, Yun (Department of Computer Engineering, Sejong University) ;
  • Kim, Seung-Eock (Department of Civil and Environmental Engineering, Sejong University)
  • 투고 : 2020.12.09
  • 심사 : 2021.04.09
  • 발행 : 2021.05.10
⟨ 이전 논문 다음 논문 ⟩

초록

This study proposes a new and highly-accurate artificial intelligence model, namely ANN-IP, which combines an interior-point (IP) algorithm and artificial neural network (ANN), to improve the axial compression capacity prediction of elliptical concrete-filled steel tubular (CFST) columns. For this purpose, 145 tests of elliptical CFST columns extracted from the literature are used to develop the ANN-IP model. In this regard, axial compression capacity is considered as a function of the column length, the major axis diameter, the minor axis diameter, the thickness of the steel tube, the yield strength of the steel tube, and the compressive strength of concrete. The performance of the ANN-IP model is compared with the ANN-LM model, which uses the robust Levenberg-Marquardt (LM) algorithm to train the ANN model. The comparative results show that the ANN-IP model obtains more magnificent precision (R2 = 0.983, RMSE = 59.963 kN, a20 - index = 0.979) than the ANN-LM model (R2 = 0.938, RMSE = 116.634 kN, a20 - index = 0.890). Finally, a new Graphical User Interface (GUI) tool is developed to use the ANN-IP model for the practical design. In conclusion, this study reveals that the proposed ANN-IP model can properly predict the axial compression capacity of elliptical CFST columns and eliminate the need for conducting costly experiments to some extent.

키워드

과제정보

This research was supported by the National Research Foundation of Korea (NRF) funded by the Korean government (MSIT) (No. 2018R1A2A2A05018524 and No. 2019R1A4A1021702).

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피인용 문헌

  1. Axial compressive behavior of circular concrete-filled double steel tubular short columns vol.25, pp.2, 2021, https://doi.org/10.1177/13694332211046345