Effect of Ductility Factor on Structural Response under Earthquake Loading

2009 ◽  
Author(s):  
M. Tehrani-Zadeh
Keyword(s):  
Structural Response ◽  
Earthquake Loading ◽  
Ductility Factor

scholarly journals The Application of Artificial Neural Networks in Predicting Structural Response of Multistory Building in The Region of Sumatra Island

2016 ◽  
Vol 1 ◽  
Author(s):  
Reni Suryanita
Keyword(s):  
Response Spectrum ◽  
Structural Response ◽  
Soil Condition ◽  
Data Sets ◽  
Earthquake Loading ◽  
Sumatra Island ◽  
Story Drift ◽  
Earthquake Load ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

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>

Re-Shaping Semi-Active Structural Response Via Simple Applications of Embedded Computation, Sensors and Valves

2007 ◽  
Author(s):  
J. Geoffrey Chase ◽  
Kerry J. Mulligan ◽  
John B. Mander ◽  
Geoffrey W. Rodgers ◽  
XiaoQi Chen
Keyword(s):  
Control Systems ◽  
First Principles ◽  
Structural Response ◽  
Shake Table ◽  
Earthquake Loading ◽  
Hybrid Testing ◽  
Modeling Analysis ◽  
Supplemental Damping ◽  
And Control ◽  
Novel Devices

Semi-active dampers and actuators hold significant promise for their ability to add supplemental damping and reduce structural response, particularly under earthquake loading. Novel devices utilizing off the shelf components and control systems are used to modify structural response. Devices are presented from design, modeling, analysis and validation via hybrid testing and experimental shake table results. All cases are compared with independent analytical predictions based on first principles analysis.

scholarly journals Dynamic characteristics and structural response of the SWR 1000 under earthquake loading conditions

2001 ◽  
Vol 207 (1) ◽  
pp. 77-93
Author(s):  
E. Bielor ◽  
W. Brettschuh ◽  
N.J. Krutzik ◽  
R. Tropp
Keyword(s):  
Dynamic Characteristics ◽  
Structural Response ◽  
Earthquake Loading ◽  
Loading Conditions

scholarly journals The Application of Artificial Neural Networks in Predicting Structural Response of Multistory Building in The Region of Sumatra Island

2016 ◽  
Vol 1 (1) ◽  
Author(s):  
Reni Suryanita
Keyword(s):  
Response Spectrum ◽  
Structural Response ◽  
Soil Condition ◽  
Data Sets ◽  
Earthquake Loading ◽  
Sumatra Island ◽  
Story Drift ◽  
Earthquake Load ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

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>

scholarly journals Structural Response Prediction for Damage Identification Using Wavelet Spectra in Convolutional Neural Network

Sensors ◽  
2021 ◽  
Vol 21 (20) ◽  
pp. 6795
Author(s):  
Edisson Alberto Moscoso Moscoso Alcantara ◽  
Michelle Diana Bong ◽  
Taiki Saito
Keyword(s):  
Damage Identification ◽  
Structural Response ◽  
Response Prediction ◽  
Wavelet Spectrum ◽  
Structural Safety ◽  
Response Analysis ◽  
Ductility Factor ◽  
Story Drift ◽  
Acceleration Record ◽  
Modern Technologies

If damage to a building caused by an earthquake is not detected immediately, the opportunity to decide on quick action, such as evacuating the building, is lost. For this reason, it is necessary to develop modern technologies that can quickly obtain the structural safety condition of buildings after an earthquake in order to resume economic and social activities and mitigate future damage by aftershocks. A methodology for the prediction of damage identification is proposed in this study. Using the wavelet spectrum of the absolute acceleration record measured by a single accelerometer located on the upper floor of a building as input data, a CNN model is trained to predict the damage information of the building. The maximum ductility factor, inter-story drift ratio, and maximum response acceleration of each floor are predicted as the damage information, and their accuracy is verified by comparing with the results of seismic response analysis using actual earthquakes. Finally, when an earthquake occurs, the proposed methodology enables immediate action by revealing the damage status of the building from the accelerometer observation records.

scholarly journals A Review on using Belt Truss at Different Locations on RCC Building

2021 ◽  
Vol 7 (09) ◽  
pp. 195-200
Author(s):  
Aditya A Chawardol and Dr Bhushan H Shinde
Keyword(s):  
Literature Review ◽  
Structural Component ◽  
Structural Response ◽  
Shear Walls ◽  
Seismic Loading ◽  
Lateral Load ◽  
Truss Structures ◽  
Earthquake Loading ◽  
Earthquake Load ◽  
Alternative Location

In past decades, shear walls and x bracing are one of the most appropriate and important structural component in multi-storied building. Therefore, it is very interesting to study the structural response and their systems in multi-storied structure during lateral load i.e earthquake loading. Shear walls and belt truss contribute the stiffness and strength during earthquakes which are often neglected during design of structure and construction. The scope of present paper is to study the effect of seismic loading on placement of belts truss in building at different alternative location. This study shows the effect of belts truss and bracing belts truss which significantly affect the vulnerability of structures. In order to test this hypothesis, RCC building was considered with and without belts truss at different location. The aim of the paper is to detail and conceptualize the varied configurations of belt truss structures system and to integrate current structures into longer structures by use of belt truss system at different location. Additionally, various advantage and disadvantage associated with outriggers and belt truss system also are discussed in this paper. A close of literature review within the field of Outrigger system is applied and therefore the summary on belts truss and gaps encountered within the study are listed during this paper. This paper introduces belt truss at different location. In which, using the belt truss structural within the RCC building so as to extend the performance of the building under the earthquake load and wind loads is studied. Concept of belt truss as Virtual outrigger is reviewed within the paper.

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