Guided Firework Algorithm (GFWA) Optimization Research on Viscoelastic Damper (VED) Structure Based on Vulnerability Evaluation
Author(s): |
Xianjie Wang
Chunyu Lei Mengjie Xiang Donghai Jiang Xin Wang |
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Medium: | journal article |
Language(s): | English |
Published in: | Buildings, 20 February 2025, n. 5, v. 15 |
Page(s): | 712 |
DOI: | 10.3390/buildings15050712 |
Abstract: |
The vulnerability curve serves as a precise evaluation metric for structural seismic performance and a critical component in earthquake loss assessment. In this study, the orthogonal expansion method for random ground motion generation is integrated with the probability density evolution method (PDEM) to address the dynamic reliability and vulnerability of general Multi-Degree of Freedom (MDOF) nonlinear structures. By employing dynamic reliability as a constraint and vulnerability as an evaluation index, the guided firework algorithm (GFWA) is introduced to optimize the design of viscoelastic damper (VED) structure systems. To validate the proposed methods, several examples are presented, including the generation of artificial waves, the vulnerability analysis of a five-story reinforced concrete (RC) structure, and a comparative study of GFWA and genetic algorithm (GA) optimization for VED parameters to assess the optimization efficiency. The results demonstrate that the proposed vulnerability method achieves satisfactory accuracy and is well suited for evaluating damper structure optimization designs. Furthermore, GFWA outperforms GA significantly in terms of efficiency and feasibility, offering a promising approach for optimization design in architectural structures. |
Copyright: | © 2025 by the authors; licensee MDPI, Basel, Switzerland. |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
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data sheet - Reference-ID
10820726 - Published on:
11/03/2025 - Last updated on:
11/03/2025