Presenting a neural network-based hybrid method for ADAS damper optimization in absorption of earthquake energy

Nejati, Faezeh; Jiyan, Milad

doi:10.22105/cand.2023.404325.1072

Document Type : Original Article

Authors

Faezeh Nejati ¹
Milad Jiyan ²

¹ Department of Civil, Ayandegan Institute of Higher Education, Tonekabon, Iran.

² Project Engineering, Toronto, Ontario, Canada.

https://doi.org/10.22105/cand.2023.404325.1072

Abstract

Improving buildings' behaviour by reducing lateral loads' effect is a new topic in earthquake engineering. It is based on reducing the energy applied to the structure through its depreciation. Structures can consume much energy in an earthquake due to their ductility. The use of energy-consuming systems in buildings allows structural members to remain resilient. Therefore, this research investigates a combined neural network-based method for optimizing Added Damper and Stiffness (ADAS) dampers in steel buildings. Thus, the seismic behaviour of each is addressed by modelling a 15-story steel structure with steel bracing in at least four reinforcement modes with ADAS damper. The selection criterion of these structures is the study of high-rise structures, and the study of finding the optimal state of reinforcement with dampers is discussed. Incremental Dynamic Analysis (IDA) using at least ten accelerograms is used in this regard. In this regard, Etabs software is used for the initial design of structures, nonlinear analysis, and optimization of OpenSees and Matlab software. It was observed that in different types of dampers arrangement, different behaviour is observed in structures. Also, the type of mirrors if due to the different hardness and performance of each damper, also led to a change in the behaviour of the structures modelled in this study. Of course, what was observed so that it is not possible to say with certainty which mode leads to better performance in structures because the performance of all four types of attenuators is very close to each other. Still, it can be said that all dampers can be considered suitable improvement options according to the employer's conditions in terms of executive capability. Dampers increase the relative displacement of the floors by improving the structure's stiffness, thereby reducing structural and non-structural damage. Triangular Added Damper and Stiffness (TADAS) and ADAS dampers have good seismic behaviour, can withstand a large number of cycles, and can absorb a large amount of earthquake energy without loss of stiffness and resistance. The use of dampers in determining the overall and local response of the sample structures under the earthquake record will positively affect the reinforcement of the structures.

Keywords

References

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Computational Algorithms and Numerical Dimensions

Presenting a neural network-based hybrid method for ADAS damper optimization in absorption of earthquake energy

References

References

Volume 2, Issue 2
June 2023
Pages 87-101

Presenting a neural network-based hybrid method for ADAS damper optimization in absorption of earthquake energy

References

References

Volume 2, Issue 2June 2023Pages 87-101

Volume 2, Issue 2
June 2023
Pages 87-101