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Investigation of the Temperature Actions of Bridge Cables Based on Long-Term Measurement and the Gradient Boosted Regression Trees Method
Cable-stayed bridges have been commonly used on high-speed railways. The design, construction, and maintenance of cable-stayed bridges necessitate an accurate assessment of the cable temperature field. However, the temperature fields of cables have not been well established. Therefore, this research...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10302245/ https://www.ncbi.nlm.nih.gov/pubmed/37420840 http://dx.doi.org/10.3390/s23125675 |
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author | Wang, Fen Dai, Gonglian Liu, Yonglu Ge, Hao Rao, Huiming |
author_facet | Wang, Fen Dai, Gonglian Liu, Yonglu Ge, Hao Rao, Huiming |
author_sort | Wang, Fen |
collection | PubMed |
description | Cable-stayed bridges have been commonly used on high-speed railways. The design, construction, and maintenance of cable-stayed bridges necessitate an accurate assessment of the cable temperature field. However, the temperature fields of cables have not been well established. Therefore, this research aims to investigate the distribution of the temperature field, the time variability of temperatures, and the representative value of temperature actions in stayed cables. A cable segment experiment, spanning over one year, is conducted near the bridge site. Based on the monitoring temperatures and meteorological data, the distribution of the temperature field is studied, and the time variability of cable temperatures is investigated. The findings show that the temperature distribution is generally uniform along the cross-section without a significant temperature gradient, while the amplitudes of the annual cycle variation and daily cycle variation in temperatures are significant. To accurately determine the temperature deformation of a cable, it is necessary to consider both the daily temperature fluctuations and the annual cycle of uniform temperatures. Then, using the gradient boosted regression trees method, the relationship between the cable temperature and multiple environmental variables is explored, and representative cable uniform temperatures for design are obtained by the extreme value analysis. The presented data and results provide a good basis for the operation and maintenance of in-service long-span cable-stayed bridges. |
format | Online Article Text |
id | pubmed-10302245 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-103022452023-06-29 Investigation of the Temperature Actions of Bridge Cables Based on Long-Term Measurement and the Gradient Boosted Regression Trees Method Wang, Fen Dai, Gonglian Liu, Yonglu Ge, Hao Rao, Huiming Sensors (Basel) Article Cable-stayed bridges have been commonly used on high-speed railways. The design, construction, and maintenance of cable-stayed bridges necessitate an accurate assessment of the cable temperature field. However, the temperature fields of cables have not been well established. Therefore, this research aims to investigate the distribution of the temperature field, the time variability of temperatures, and the representative value of temperature actions in stayed cables. A cable segment experiment, spanning over one year, is conducted near the bridge site. Based on the monitoring temperatures and meteorological data, the distribution of the temperature field is studied, and the time variability of cable temperatures is investigated. The findings show that the temperature distribution is generally uniform along the cross-section without a significant temperature gradient, while the amplitudes of the annual cycle variation and daily cycle variation in temperatures are significant. To accurately determine the temperature deformation of a cable, it is necessary to consider both the daily temperature fluctuations and the annual cycle of uniform temperatures. Then, using the gradient boosted regression trees method, the relationship between the cable temperature and multiple environmental variables is explored, and representative cable uniform temperatures for design are obtained by the extreme value analysis. The presented data and results provide a good basis for the operation and maintenance of in-service long-span cable-stayed bridges. MDPI 2023-06-17 /pmc/articles/PMC10302245/ /pubmed/37420840 http://dx.doi.org/10.3390/s23125675 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Wang, Fen Dai, Gonglian Liu, Yonglu Ge, Hao Rao, Huiming Investigation of the Temperature Actions of Bridge Cables Based on Long-Term Measurement and the Gradient Boosted Regression Trees Method |
title | Investigation of the Temperature Actions of Bridge Cables Based on Long-Term Measurement and the Gradient Boosted Regression Trees Method |
title_full | Investigation of the Temperature Actions of Bridge Cables Based on Long-Term Measurement and the Gradient Boosted Regression Trees Method |
title_fullStr | Investigation of the Temperature Actions of Bridge Cables Based on Long-Term Measurement and the Gradient Boosted Regression Trees Method |
title_full_unstemmed | Investigation of the Temperature Actions of Bridge Cables Based on Long-Term Measurement and the Gradient Boosted Regression Trees Method |
title_short | Investigation of the Temperature Actions of Bridge Cables Based on Long-Term Measurement and the Gradient Boosted Regression Trees Method |
title_sort | investigation of the temperature actions of bridge cables based on long-term measurement and the gradient boosted regression trees method |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10302245/ https://www.ncbi.nlm.nih.gov/pubmed/37420840 http://dx.doi.org/10.3390/s23125675 |
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