Utilizing Metaheuristic Algorithms for Ground Motion Selection and Scaling in Structural Time History Analysis
Description:
This study proposes two Metaheuristic Algorithms for structural time history analysis to optimize the selection and scaling of ground motion (GM) records. The primary goal is to preserve the phase and shape of the response spectra in the selected records. The methodology efficiently navigates through a vast database of earthquake records, proposing a set of 11 record pairs and corresponding scaling factors. The outcome is a mean spectrum that closely aligns with the target spectrum. The application of our research is demonstrated at two distinct sites in the United States: the first in Memphis and the second in San Francisco, following the ASCE 7-22 procedure. Selected ground motions undergo scaling adjustments represented by scalar values within a user-defined range. Additionally, we present error metrics, comparing the target spectrum with the mean spectrum derived from the selected records. To validate the effectiveness of our approach, a comparative analysis is conducted against results obtained from the PEER-NGA web application methodology. The results highlight our model as a robust and reliable approach for acquiring suitable GM records for structural time history analysis.
Session: Numerical Modeling in Seismology: Developments and Applications [Poster Session]
Type: Poster
Date: 5/1/2024
Presentation Time: 08:00 AM (local time)
Presenting Author: Mohsen
Student Presenter: Yes
Invited Presentation:
Authors
Mohsen Akhani Presenting Author Corresponding Author mkhnsnjn@memphis.edu University of Memphis |
Najme Alidadi nalidadi@memphis.edu University of Memphis |
Shahram Pezeshk spezeshk@memphis.edu University of Memphis |
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Utilizing Metaheuristic Algorithms for Ground Motion Selection and Scaling in Structural Time History Analysis
Category
Numerical Modeling in Seismology: Developments and Applications