Effect of inter-module connection stiffness on structural response of a modular steel building subjected to wind and earthquake load

2020 ◽  
Vol 213 ◽  
pp. 110628 ◽  
Author(s):  
Andrew William Lacey ◽  
Wensu Chen ◽  
Hong Hao ◽  
Kaiming Bi
2021 ◽  
Vol 236 ◽  
pp. 112103
Author(s):  
Andrew William Lacey ◽  
Wensu Chen ◽  
Hong Hao ◽  
Kaiming Bi

2021 ◽  
Vol 234 ◽  
pp. 111986
Author(s):  
Rafaela Sanches ◽  
Junjie Tao ◽  
Amirahmad Fathieh ◽  
Oya Mercan

2017 ◽  
Vol 139 ◽  
pp. 69-82 ◽  
Author(s):  
Zhihua Chen ◽  
Jiadi Liu ◽  
Yujie Yu ◽  
Chenhua Zhou ◽  
Rengjing Yan

2019 ◽  
Vol 8 (4) ◽  
pp. 3236-3243

Communication towers have been traditionally designed for wind load. The earthquake load has not been observed in the analysis of the communication tower. Recent earthquakes, there have been indications of collapse to the communication tower. Due to the complex nature of the problem, there is a lack of research work in the area of analysis of the communication tower. The purpose of this research is to test the communication tower's response to earthquake ground movement to determine the current design software methodology. The effect of earthquake ground motion spatial variation on multi-support structures dynamic response may be necessary. The aim of this project is to use the traveling wave assumption to investigate the seismic response of high antenna-supporting guyed towers. The horizontal component of the Bhuj earthquake is considered as excitation. Elements of response analyzed are cable tension, base shear, mast axial force and lateral displacement of the tower tip. Parametric analyses show that the structural response tends to increase as the amplitude of the wave decreases and can become much larger than the reaction from synchronous excitation.


2021 ◽  
Vol 1200 (1) ◽  
pp. 012014
Author(s):  
M A Gapar ◽  
M F Razali ◽  
H Mansor ◽  
Y S Hamid ◽  
N E A Subki

Abstract Modular Steel Building (MSB) provide benefits towards green building technology such as minimum wastage, faster build time and cost-efficiency. The intra-module connection is the most important aspect of MSB construction since it has a significant impact on overall structural stability and robustness. A novel intra-module connection was proposed for the MSB. The proposal was designed to suit the illustrative five-storey hexagon shape modular steel building that possibly imagines by Architect. Two analyses phases are being presented, namely the Macro and Microanalysis model. The former is the stage for global analysis design of the proposed five-storey hexagon shape modular steel building via SAP2000. The latter is the local intra-module connection behaviour analysis using ABAQUS software. Linear and nonlinear static analyses were carried out on the proposed intra-module connection under the vertical applied load. In this work, the failure of the connection under the given load was governed by the hexagon diaphragm, while the fin plate demonstrates the least affected constitutive component. It anticipates that the suggested unique intra-module connection will encourage architects to employ modular steel construction designs with greater flexibility. Future research will concentrate on the parametric study to improve the performance of the diaphragm and the connection’s limitations.


2016 ◽  
Vol 1 ◽  
Author(s):  
Reni Suryanita

Artificial Neural Network (ANN) method is a prediction tool which is widely used in various fields of application. This study utilizes ANN to predict structural response (story drift) of multi-story reinforced concrete building under earthquake load in the region of Sumatera Island. Modal response spectrum analysis is performed to simulate earthquake loading and produce structural response data for further use in the ANN. The ANN architecture comprises of 3 layers: an input layer, a hidden layer, and an output layer. Earthquake load parameters from 11 locations in Sumatra Island, soil condition, and building geometry are selected as input parameters, whereas story drift is selected as output parameter for the ANN. As many as 1080 data sets are used to train the ANN and 405 data sets for testing. The trained ANN is capable of predicting story drift under earthquake loading at 95% rate of prediction and the calculated Mean-Squared Errors (MSE) as low as 1.6.10<sup>-4</sup>. The high accuracy of story drift prediction is more than 90% can greatly assist the engineer to identify the building condition rapidly due to earthquake loads and plan the building maintenance routinely.<strong></strong>


Structures ◽  
2021 ◽  
Vol 33 ◽  
pp. 1659-1676
Author(s):  
Jun-Yi Lian ◽  
En-Feng Deng ◽  
Jin-Ming He ◽  
Li-Ming Cai ◽  
Shu-Cai Gao ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document