page loader
  1. Trang chủ
  2. Bài báo khoa học
  3. Chi tiết bài báo
Moment-rotation-temperature model of semi-rigid cruciform flush endplate connection in fire
Tác giả: Viet-Linh Tran
158    0
Fire Safety Journal
Quyển: 114     Trang: 102992
Đường link/DOI: https://doi.org/10.1016/j.firesaf.2020.102992
Năm xuất bản: 6/2020
Tóm tắt
This paper aims to develop a model for predicting the moment-rotation-temperature (M-R-T) relationship of semi-rigid cruciform flush endplate (CFEP) connections in fire. For this purpose, a nonlinear finite element (FE) analysis was conducted to simulate the CFEP connections in the fire using ABAQUS. The FE model was verified with the experimental results conducted by others. Based on the validated FE model, a parametric study was carried out by considering effect of several parameters, such as the number of bolt rows, column section, beam section, distance of bolt rows, gauge distance, endplate thickness, bolt diameter, yield and ultimate stress of column, yield and ultimate stress of beam, yield and ultimate stress of endplate, yield and ultimate stress of bolt, and moment ratio. Accordingly, the results of the parametric study were used to establish the M-R-T model of CFEP connections at both ambient and elevated temperature. The performance of the M-R-T model was compared with the test results in the literature. The comparative study showed that the proposed model can accurately capture the M-R-T relationship of CFEP connections in fire.
Từ khóa
Cruciform flush endplate connection; Fire; Moment-rotation-temperature model
Cùng tác giả
Ensemble machine learning-based models for estimating the transfer length of strands in PSC beamsInnovative formulas for reinforcing bar bonding failure stress of tension lap splice using ANN and TLBOPrediction of the ultimate axial load of circular concrete-filled stainless steel tubular columns using machine learning approachesPatch loading resistance prediction of steel plate girders using a deep artificial neural network and an interior-point algorithmInvestigating the Behavior of Steel Flush Endplate Connections at Elevated Temperatures Using FEM and ANNNovel hybrid WOA-GBM model for patch loading resistance prediction of longitudinally stiffened steel plate girdersA new framework for damage detection of steel frames using burg autoregressive and stacked autoencoder-based deep neural networkRevealing the nonlinear behavior of steel flush endplate connections using ANN-based hybrid modelsBuckling resistance of axially loaded square concrete-filled double steel tubular columnsRapid prediction of the ultimate moment of flush endplate connections at elevated temperatures through an artificial neural networkComputational analysis of axially loaded thin-walled rectangular concrete-filled stainless steel tubular short columns incorporating local buckling effectsAxial compressive behavior of circular concrete-filled double steel tubular short columnsEvaluation of Seismic Site Amplification Using 1D Site Response Analyses at Ba Dinh Square Area, VietnamMachine Learning Models for Predicting Shear Strength and Identifying Failure Modes of Rectangular RC ColumnsApplication of ANN in predicting ACC of SCFST columnA new empirical formula for prediction of the axial compression capacity of CCFT columnsPractical artificial neural network tool for predicting the axial compression capacity of circular concrete-filled steel tube columns with ultra-high-strength concrete