Prediction of temperature gradient in slab ballastless track structure considering meteorological data

Determining temperature load values for slab ballastless tracks in cold-temperate climates is essential for assessing track performance. Using historical meteorological data from the Shenyang-Baicheng high-speed railway and heat transfer principles, a thermal model for the CRTS III slab ballastless track was developed to analyse temperature field distribution under extreme conditions. A predictive formula for maximum positive and negative temperature gradients was derived and validated through numerical simulation and scaled model tests. Results indicate that in north-eastern China’s cold-temperate zone, the CRTS III track’s temperature gradient ranges from −43.5°C/m to 104.5°C/m. The maximum positive gradient occurs under large temperature differences, while the maximum negative gradient appears in low-temperature conditions. Solar radiation, wind speed, and daily temperature variation were used to fit the gradients by way of multiple linear regression. The maximum positive gradient is directly proportional to temperature difference and solar radiation but inversely proportional to wind speed. Conversely, the maximum negative gradient is directly proportional to temperature difference but inversely proportional to wind speed and solar radiation. These findings provide guidance for evaluating temperature effects on track structures and offer a reference for ballastless track temperature gradients in different regions.

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Publication Details

Journal
Proceedings of the Institution of Civil Engineers - Engineering and Computational Mechanics
Published
2025-05-10
DOI
https://doi.org/10.1680/jencm.24.00080
Primary Topic
Railway Engineering and Dynamics
Type
article
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article

Prediction of temperature gradient in slab ballastless track structure considering meteorological data

F. Yu, Lihua Zhao, Jichao Zhu, Anguo Hu et al.
1 links
Proceedings of the Institution of Civil Engineers - Engineering and Computational Mechanics
Railway Engineering and Dynamics
article

Prediction of temperature gradient in slab ballastless track structure considering meteorological data

F. Yu, Lihua Zhao, Jichao Zhu, Anguo Hu, Zaw Han, Rihong Zhu
article en

Abstract

Determining temperature load values for slab ballastless tracks in cold-temperate climates is essential for assessing track performance. Using historical meteorological data from the Shenyang-Baicheng high-speed railway and heat transfer principles, a thermal model for the CRTS III slab ballastless track was developed to analyse temperature field distribution under extreme conditions. A predictive formula for maximum positive and negative temperature gradients was derived and validated through numerical simulation and scaled model tests. Results indicate that in north-eastern China’s cold-temperate zone, the CRTS III track’s temperature gradient ranges from −43.5°C/m to 104.5°C/m. The maximum positive gradient occurs under large temperature differences, while the maximum negative gradient appears in low-temperature conditions. Solar radiation, wind speed, and daily temperature variation were used to fit the gradients by way of multiple linear regression. The maximum positive gradient is directly proportional to temperature difference and solar radiation but inversely proportional to wind speed. Conversely, the maximum negative gradient is directly proportional to temperature difference but inversely proportional to wind speed and solar radiation. These findings provide guidance for evaluating temperature effects on track structures and offer a reference for ballastless track temperature gradients in different regions.

Proceedings of the Institution of Civil Engineers - Engineering and Computational MechanicsVol. 178(2)
Dalian Jiaotong University (CN)
Openalex Percentile: Top 90%
Railway Engineering and Dynamics
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Prediction of temperature gradient in slab ballastless track structure considering meteorological data — F. Yu, Lihua Zhao, et al. · Proceedings of the Institution of Civil Engineers - Engineering and Computational Mechanics (2025) | TGRS Research Map | TGRS