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Title |
Estimation of Time History of Elastic Modulus based on Finite Element Model Updating for Optimal Bridge Maintenance
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Authors |
박지원(Jiwon Park) ; 장민우(Minwoo Chang) |
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DOI |
https://doi.org/10.11112/jksmi.2025.29.6.21 |
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Keywords |
유한 요소 모델 업데이팅; 구조 건전성 모니터링; 유전 알고리즘; 입자 군집 최적화; 교량 유지보수; 동특성 Finite element model updating; Structural health monitoring; Genetic algorithm; Particle swarm optimization; Bridge maintenance; Dynamic properties |
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Abstract |
This study applies finite element (FE) model updating to estimate the material properties of aging bridges and evaluates the performance of optimization algorithms. The Deokpyeong 1 Bridge, for which initial design documents are unavailable, was analyzed using vertical acceleration data to identify its dynamic parameters and update the FE model. The acceleration data measured from 15 sensor locations are divided into every ten minutes, which results in 1152 datasets. The modal parameters were identified for each dataset. Two optimization methods-Genetic Algorithm (GA) and Particle Swarm Optimization (PSO)-were implemented to minimize the error between the modal parameters identified from the measured dataset and those obtained from the FE model. The GA demonstrated approximately 7 seconds faster computation time, whereas the PSO achieved lower frequency errors and MAC values exceeding 0.8, indicating superior estimation accuracy overall. Furthermore, the effect of temperature variation on bridge material properties was investigated. Results showed that both the elastic modulus of the main structural components and the spring stiffness of bridge bearings fluctuated with temperature variations. These findings underscore the importance of FE model updating for structural health monitoring and maintenance of aging infrastructure.
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