Development of a 3D Finite-Element Modelling Generation System Based on Data Processing Platform and Fatigue Analysis of Full-Scale Reinforced-Concrete Bridge
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Détails bibliographiques
| Auteur(s): |
Taiju Yoneda
(MAEDA CORPORATION, ICI General Center, ICI Lab, Tokyo, Japan.)
Jie Fang (The University of Tokyo, Department of Civil Engineering, Tokyo, Japan.) Hideyuki Otani (RIKEN, Computational Disaster Mitigation and Reduction Research Team, Kobe, Japan.) Satoshi Tsuchiya (COMS Engineering Corporation, Tokyo, Japan.) Satoru Oishi (RIKEN, Computational Disaster Mitigation and Reduction Research Team, Kobe, Japan.) Tetsuya Ishida (The University of Tokyo, Department of Civil Engineering, Tokyo, Japan.) |
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| Médium: | papier de conférence | ||||
| Langue(s): | anglais | ||||
| Conférence: | IABSE Symposium: Challenges for Existing and Oncoming Structures, Prague, Czech Republic, 25-27 May 2022 | ||||
| Publié dans: | IABSE Symposium Prague 2022 | ||||
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| Page(s): | 415-422 | ||||
| Nombre total de pages (du PDF): | 8 | ||||
| DOI: | 10.2749/prague.2022.0415 | ||||
| Abstrait: |
This study presents a technology development for creating 3D finite-element full-scale bridge models based on a data processing platform (DPP) and explores the trial fatigue analysis to serve as an important reference for future practical applications. Until now, the model generation, validation and calculation for a large-scale model of conventional method consume huge time and money. Currently, developments in High- Performance Computing (HPC) and preparation for large parallel computers make numerical simulation operation more efficient. Moreover, through the grouping structure technique, different types of data can be linked together. In this research, a 3D finite-element full-scale bridge superstructure model was created using the DPP. A trial fatigue analysis was performed using a high-performance computer. By considering the details such as the position of each reinforcing bar, prestressed tendon, the slope, etc., the DPP model more closely captures the real structure. Therefore, it could be said that the model made by the DPP has higher analytical accuracy. This research paved the way for the implementation of large-scale fatigue analysis, which has significant engineering applications prospects. |
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| Copyright: | © 2022 International Association for Bridge and Structural Engineering (IABSE) | ||||
| License: | Cette oeuvre ne peut être utilisée sans la permission de l'auteur ou détenteur des droits. |
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