Implementation of AI for The Prediction of Failures of Reinforced Concrete Frames
Publish place: International Journal of Reliability, Risk and Safety: Theory and Application، Vol: 5، Issue: 2
Publish Year: 1401
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_IJRRS-5-2_001
تاریخ نمایه سازی: 1 بهمن 1401
Abstract:
Reinforced concrete tall building failure, in residual areas, can cause catastrophic disaster if they can’t survive during the destructive earthquakes. Hence, determining the damage of these buildings in the earthquake and detecting the probable mechanism formation are necessary for insurance purposes in urban areas. This paper aims to determine the failure modes of the moment resisting concrete frames (MRFs) according to the damage of the beam and column. To achieve this goal, a ۱۵-storey moment resisting reinforced concrete frame is modeled via IDARC software, and nonlinear dynamic time history analysis is performed through ۶۰ seismic accelerograms. Then the collapse and non-collapse vectors are constructed obtaining the results of dynamic analysis in both modes. The artificial neural network is used for the classification of the obtained modes. The results show good agreement in failures classes. Hence it is possible to introduce the simple weight factor for frame status identification.
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Authors
sasan motaghed
Department of Civil Engineering, Faculty of Engineering, Behbahan Khatam Alanbia University of Technology, Behbahan, Iran
mohammad sadegh Shahid zadeh
Department of Civil Engineering, Faculty of Engineering, Behbahan Khatam Alanbia University of Technology, Behbahan, Iran
ali khooshecharkh
Department of Civil Engineering, Faculty of Engineering, Behbahan Khatam Alanbia University of Technology, Behbahan, Iran
mehdi Askari
Department of Civil Engineering, Faculty of Engineering, Behbahan Khatam Alanbia University of Technology, Behbahan, Iran
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