Experimental and numerical analysis of beam to column joints in steel structures

doi:10.1007/s11709-017-0457-z

Front. Struct. Civ. Eng.

2018, Vol. 12

Issue (4) : 642-661 https://doi.org/10.1007/s11709-017-0457-z

RESEARCH ARTICLE

Experimental and numerical analysis of beam to column joints in steel structures

Gholamreza ABDOLLAHZADEH(

), Seyed Mostafa SHABANIAN

Faculty of Civil Engineering, Babol Noshirvani University of Technology, Babol, Iran

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Abstract

The behaviors such as extreme non-elastic response, constant changes in roughness and resistance, as well as formability under extreme loads such as earthquakes are the primary challenges in the modeling of beam-to-column connections. In this research, two modeling methods including mechanical and neural network methods have been presented in order to model the complex hysteresis behavior of beam-to-column connections with flange plate. First, the component-based mechanical model will be introduced in which every source of transformation has been shown only with geometrical and material properties. This is followed by the investigation of a neural network method for direct extraction of information out of experimental data. For the validation of behavioral curves as well as training of the neural network, the experiments were carried out on samples with real dimensions of beam-to-column connections with flange plate in the laboratory. At the end, the combinational modeling framework is presented. The comparisons reveal that the combinational modeling is able to display the complex narrowed hysteresis behavior of the beam-to-column connections with flange plate. This model has also been successfully employed for the prediction of the behavior of a newly designed connection.

Keywords beam to column connections experiments component method neural network model combinational modeling

Corresponding Author(s): Gholamreza ABDOLLAHZADEH

Online First Date: 26 February 2018 Issue Date: 20 November 2018

Cite this article:

Gholamreza ABDOLLAHZADEH,Seyed Mostafa SHABANIAN. Experimental and numerical analysis of beam to column joints in steel structures[J]. Front. Struct. Civ. Eng., 2018, 12(4): 642-661.

URL:

https://academic.hep.com.cn/fsce/EN/10.1007/s11709-017-0457-z
https://academic.hep.com.cn/fsce/EN/Y2018/V12/I4/642

Fig.1 The position of elements on the connection with flange plate

Fig.2 The force–displacement curve for the elements under tension and pressure [³⁰]

Tab.1 Nomenclature of the different elements applied in the mechanical model

Fig.3 The neural network model proposed by Yun et al. [⁴⁹]

Fig.4 A neural network in its returning state

Fig.5 Different steel beam to column connection with flange plate

Fig.6 The geometrical specifications of flange plate of the experimental sample connection

Section	Dimensions (mm)
Beam	IPE180	1250
Column	IPB160	1300
Upper sheet	A	45
	B	30
	C	45
	D	40
	$E$	35
Lower sheet	F	45
	G	40
	H	45
	I	40
	K	35
column web hardener	One at each side of the column	PL1701358
Continuity sheet	Two at each side of the column	PL140708
Beam web hardener	Two at each side of the beam	PL160424
Bolts	6 strong bolts	M16

Tab.2 The specifications of the components employed in the experimental sample

Tab.3 The specifications of the materials of the components employed in the experimental sample

Fig.7 The position of laboratory equipment

Fig.8 Enerpac hydraulic jack (ZE5)

Fig.9 Load cell device with a capacity of 1MN

Fig.10 The position of displacement transducers in the overall geometry of the experimental sample

Fig.11 A schematic view of the loading and the sample launching

Fig.12 Standard periodic load of SAC and its application to the samples according to FAMA350 proposal [⁵²]

The loading step	Rotation angle $θ$	The number of cycles	Displacement of the control
1	0.00375	6	0.251
2	0.005	6	0.335
3	0.0075	6	0.502
4	0.01	4	0.670
5	0.015	2	1.005
6	0.02	2	1.340
7	0.03	2	2.010

Tab.4 The details of the periodic load applied to the samples according to SAC Standard [⁵²]

Fig.13 The moment–rotation curve of the experimental sample

Fig.14 Comparison of the component method and the experimental results

Fig.15 Comparison of the experimental and neural network model results

Tab.5 Error indices results of the ANN model

Fig.16 The combination model of beam-to-column connection with flange plate

$N o C y c l e$	$6$	$N o E p o c h C y c l e$	$80$
$N o S t e p$	$340$	$N o E p o c h P a s s$	$2200$
$N o P a s s$	$10$	$S t i f f M a x$	$900000$
$N o A G D$	$356.2$	$S t i f f M i n$	$100000$
The Neural Network Structure	$f n = F N N [{d n, d n − 1, f n − 1, ξ n, Δ η n, E n − 1} : {6 − 30 − 30 − 1}]$

Tab.6 The parameters of the self-learning simulation of the connection

Fig.17 Evolution of the moment-rotation curves with the combinational model

Fig.18 The beam to column connection with flange plate of the new plan

Section	Dimensions (mm)
Beam	IPE200	1255
Column	IPB180	1310
Upper sheet	A	50
	B	35
	C	50
	D	40
	$E$	40
Lower sheet	F	50
	G	45
	H	48
	I	42
	K	38
column web hardener	One at each side of the column	PL19015010
Continuity sheet	Two at each side of the column	PL150808
Beam web hardener	Two at each side of the beam	PL165455
Bolts	6 strong bolts	M18

Tab.7 The specifications of the components with new design employed in the experimental sample

Fig.19 The experimental sample for validation of the combinational model

Fig.20 Comparison of the moment–rotation curves of the experimental and combinational model of the connection with the new design

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