Uniform story drift optimization seismic design of steel frame structures
This paper proposes a uniform story drift design method for steel frames. Through the optimization of structural section sizes, story drift ratio distribution was rendered more uniform, strengthening the weak stories. The algorithm used was the optimization criterion method. The uniform story drift...
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Published in | Journal of Building Engineering Vol. 100; p. 111747 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Ltd
15.04.2025
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Subjects | |
Online Access | Get full text |
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Summary: | This paper proposes a uniform story drift design method for steel frames. Through the optimization of structural section sizes, story drift ratio distribution was rendered more uniform, strengthening the weak stories. The algorithm used was the optimization criterion method. The uniform story drift design of steel frames was performed automatically through collaboration between OpenSEES and MATLAB. The proposed optimization method is presented in the form of 5-story, 10-story, 15-story, and 20-story steel frame cases. Elastic-plastic time history analysis, incremental dynamic analysis and seismic fragility analysis were performed to validate the universality of the optimization results. The results indicate that optimizing the section sizes of structural beams and columns using the optimization criterion method can effectively control the story drift ratio distribution. In addition, structural story drift ratio distributions under different seismic records were similar. Optimal section size formulas are therefore effective when a steel frame is subjected to different earthquakes with varying intensities.
•An automatic uniform displacement design method for steel frames is proposed.•The optimization process is presented through four steel frame finite element models.•The effectiveness and universality of the optimization results are validated by numerical simulations. |
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ISSN: | 2352-7102 2352-7102 |
DOI: | 10.1016/j.jobe.2024.111747 |