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Direct Prediction Method for Semi-Rigid Behavior of K-Joint in Transmission Towers Based on Surrogate Model.

Authors :
Tang, Zhengqi
Li, Zhengliang
Wang, Tao
Source :
International Journal of Structural Stability & Dynamics; Feb2023, Vol. 23 Issue 3, p1-24, 24p
Publication Year :
2023

Abstract

The assembled tube-gusset K-joint by bolts is a commonly used connection form in steel tubular transmission towers. At present, main existing research or design codes for steel tubular transmission towers regard this K-joint as either rigid or pinned connections, which do not consider the semi-rigid behavior of K-joint. In this paper, the semi-rigid behavior of K-joint in steel tubular transmission towers is investigated and a direct prediction (DP) method is proposed to evaluate the semi-rigid behavior of K-joints based on the support vector regression (SVR) model, especially to predict the moment–rotation curve of semi-rigid K-joints. First, the establishment and validation of the finite element (FE) model of semi-rigid K-joints are conducted. Second, a dataset of 144 samples generated by the FE model is used to train and test the SVR model. Finally, the accuracy assessment of the proposed DP method and comparison with other existing methods, including the Kishi–Chen model, EC3 model and ANN-based two-step prediction method, are presented. The accuracy assessment shows that predicted values of the proposed DP method based on the SVR model exhibit good agreement with the numerical analysis values, which indicates the quite high accuracy of this method. Additionally, the comparison reveals that the proposed DP method based on the SVR model for predicting moment–rotation curves is rather more accurate than other aforementioned methods. Therefore, the proposed DP method based on the SVR model is of high reliability in predicting the semi-rigid behavior of K-joints in steel tubular transmission towers, which affords an alternative way for further engineering analysis and initial design purposes. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02194554
Volume :
23
Issue :
3
Database :
Complementary Index
Journal :
International Journal of Structural Stability & Dynamics
Publication Type :
Academic Journal
Accession number :
161546558
Full Text :
https://doi.org/10.1142/S021945542350027X