Presenting a neural network-based hybrid method for ADAS damper optimization in absorption of earthquake energy
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-con...
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REA Press
2023-06-01
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| Series: | Computational Algorithms and Numerical Dimensions |
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| Online Access: | https://www.journal-cand.com/article_175421_f449c5a3743d18c39c609b848739ae73.pdf |
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| author | Faezeh Nejati Milad Jiyan |
| author_facet | Faezeh Nejati Milad Jiyan |
| author_sort | Faezeh Nejati |
| collection | DOAJ |
| description | 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. |
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| id | doaj-art-4338461bbdb24655a4be567f4d3bfbe1 |
| institution | Kabale University |
| issn | 2980-7646 2980-9320 |
| language | English |
| publishDate | 2023-06-01 |
| publisher | REA Press |
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| series | Computational Algorithms and Numerical Dimensions |
| spelling | doaj-art-4338461bbdb24655a4be567f4d3bfbe12025-01-30T11:22:05ZengREA PressComputational Algorithms and Numerical Dimensions2980-76462980-93202023-06-01228710110.22105/cand.2023.404325.1072175421Presenting a neural network-based hybrid method for ADAS damper optimization in absorption of earthquake energyFaezeh Nejati0Milad Jiyan1Department of Civil, Ayandegan Institute of Higher Education, Tonekabon, Iran.Project Engineering, Toronto, Ontario, Canada.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.https://www.journal-cand.com/article_175421_f449c5a3743d18c39c609b848739ae73.pdfneural networkoptimizationadas dampertadas damperabsorbing energy |
| spellingShingle | Faezeh Nejati Milad Jiyan Presenting a neural network-based hybrid method for ADAS damper optimization in absorption of earthquake energy Computational Algorithms and Numerical Dimensions neural network optimization adas damper tadas damper absorbing energy |
| title | Presenting a neural network-based hybrid method for ADAS damper optimization in absorption of earthquake energy |
| title_full | Presenting a neural network-based hybrid method for ADAS damper optimization in absorption of earthquake energy |
| title_fullStr | Presenting a neural network-based hybrid method for ADAS damper optimization in absorption of earthquake energy |
| title_full_unstemmed | Presenting a neural network-based hybrid method for ADAS damper optimization in absorption of earthquake energy |
| title_short | Presenting a neural network-based hybrid method for ADAS damper optimization in absorption of earthquake energy |
| title_sort | presenting a neural network based hybrid method for adas damper optimization in absorption of earthquake energy |
| topic | neural network optimization adas damper tadas damper absorbing energy |
| url | https://www.journal-cand.com/article_175421_f449c5a3743d18c39c609b848739ae73.pdf |
| work_keys_str_mv | AT faezehnejati presentinganeuralnetworkbasedhybridmethodforadasdamperoptimizationinabsorptionofearthquakeenergy AT miladjiyan presentinganeuralnetworkbasedhybridmethodforadasdamperoptimizationinabsorptionofearthquakeenergy |