Train-Induced Vibration Predictions Based on Data-Driven Cascaded State-Space Model
Auteur(s): |
Ziyu Tao
Zihao Hu Ganming Wu Conghui Huang Chao Zou Zhiyun Ying |
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Médium: | article de revue |
Langue(s): | anglais |
Publié dans: | Buildings, 18 janvier 2022, n. 2, v. 12 |
Page(s): | 114 |
DOI: | 10.3390/buildings12020114 |
Abstrait: |
Over-track buildings above metro depots have become common in megacities due to urban land shortages. The transmission of vibrations into the over-track buildings during routine train operations has the potential to adversely impact the occupants in terms of perceptible vibration and noise. There is a need to quantify the potential impacts before construction for planning and design purposes. Train-induced vibration measurements were carried out on a six-story over-track building at the Luogang metro depot in Guangzhou, China, which is located adjacent to the tracks. The measurements were used to develop a data-driven cascaded state-space model, which can be applied to planned over-track buildings located in track areas to predict and assess whether train-induced vibrations would adversely affect the buildings’ future occupants. Vibration levels in the platform of the building’s columns were used as inputs to the models, thereby avoiding the complexity of modeling the transfer behavior of the platform. The predicted vibration levels corresponded with measurements in the existing building. This comparison validated the use of the model for future residential buildings where the predictions indicate that the impacts on its occupants will be within the applicable criteria. |
Copyright: | © 2022 by the authors; licensee MDPI, Basel, Switzerland. |
License: | Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original. |
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10657763 - Publié(e) le:
17.02.2022 - Modifié(e) le:
01.06.2022