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Get Free AccessEmbedded steel column bases are normally idealized as fixed boundary condition in the analysis of steel frameworks. In practice, the embedded column bases sometimes have embedded depth notably smaller than that recommended by the structural design codes. In such a case, the fixed boundary assumption may overestimate the stiffness of the bases to a large extent. In light of this, this paper proposes a theoretical model for the accurate prediction of the rotational stiffness of the shallow embedded steel column bases, with the combined effects of key influencing factors, including the axial load in the column, the shear deformation of the embedded column, the rotational constraint provided by the column end plate, and the stiffness contribution from the anchor bolts. To achieve this, the calculation of the rotational stiffness of the base plate is refined in this paper based on previous study, which can consider the contribution from the anchor bolts, and incorporated in the Winkler foundation beam model, giving the expression of the initial rotational stiffness of the embedded column base. The proposed model is validated by the experimental and finite element simulation results.
X Li, Bing Yang, Ming Zhang, Weiwei Liu, Z Lei, Dangxiao Wang, Jiabin Wang, Li Zhou, Xueming Shu, Cross-Sections Zhang, Leroy Gardner, C Buchanan, Dave Chan, Wei Sun, Yujiang Wang, F. Lu, Bin Luo, Zeyu Zhang, D Ye, Guoqiang Li, Rui Li, Yang Zhang, Shell Reticulated, Yiyi Chen, Fang Huang, X Zhang, Zhiping Yu, Rui Guo, Yang Du, L Zhong, Chengyun Miao, Ping Yan, Cheng Fang, Yiyi Chen, Yan Ding, Mehmet Soy, Min Tang, Zhang We, Yang Xia, Fen Lin, Chao Liu, Lei Wang, Haozhe Liu, H Dong, X Liu High, W Wang, A Sharhan, Erdeng Du, Xiong Hu, Zhenhuan Zhou, Jian Lü, Yankun Tang, A Abdelrahman, M Ghannam, S Lotfy, Mohammad AlHamaydeh, Xi Xiong, F Nkuichou, Ting Wang, Min Ma, K Du Corrosion, N Wang, Jian Hua, Xin Xue, Qindan Huang, F Wang, Haidong Huang, Li Ren, Ke Chen (2022). ROTATIONAL STIFFNESS MODEL FOR SHALLOW EMBEDDED STEEL COLUMN BASES. , DOI: https://doi.org/10.18057/icass2020.p.308.
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Type
Report
Year
2022
Authors
69
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.18057/icass2020.p.308
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