Research Article

Reliability Prediction of SMRF Based on the Combination of Neural Network And Incremental Dynamic Analysis

Volume: 5 Number: 2 December 31, 2023
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Reliability Prediction of SMRF Based on the Combination of Neural Network And Incremental Dynamic Analysis

Abstract

This paper conducts a comprehensive vulnerability analysis of steel structures, taking into account the stringent HAZUS restrictions. The demand distribution for each mode of failure takes the form of a normal logarithm after extracting the fragility chart. Thus, the two parameters of mean and standard deviation can be used to construct the fragility chart. A total of five modes of failure were used in this paper. Therefore, 10 unknown values were used to derive the fragility curves. Afterward, Incremental Dynamic Analysis (IDA) was used under 40 natural records to obtain the fragility curve. To save time in the analysis and prediction of structural responses, a neural network method was used to select records more efficiently. It was observed that this method is better than the analytical method in considering random uncertainty in steel structures when several acceleration values are used.

Keywords

References

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  8. Karimi Ghaleh Jough F, Ghasemzadeh B. (2023). Uncertainty Interval Analysis of Steel Moment Frame by Development of 3D-Fragility Curves Towards Optimized Fuzzy Method. Arab J Sci Eng https://doi.org/10.1007/s13369-023-08223-8.

Details

Primary Language

English

Subjects

Earthquake Engineering

Journal Section

Research Article

Authors

Borhan Ghasemzadeh
0000-0002-7960-3503
Kuzey Kıbrıs Türk Cumhuriyeti

Early Pub Date

December 31, 2023

Publication Date

December 31, 2023

Submission Date

June 21, 2023

Acceptance Date

December 28, 2023

Published in Issue

Year 2023 Volume: 5 Number: 2

APA
Karımı Ghaleh Jough, F., & Ghasemzadeh, B. (2023). Reliability Prediction of SMRF Based on the Combination of Neural Network And Incremental Dynamic Analysis. Journal of Innovations in Civil Engineering and Technology, 5(2), 91-105. https://doi.org/10.60093/jiciviltech.1317804

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