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ZENODO
Software . 2025
Data sources: ZENODO
ZENODO
Software . 2025
Data sources: Datacite
ZENODO
Software . 2025
Data sources: Datacite
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Thermal mechanical analysis on railway brake disc: based on the FEniCSx

Authors: Zhang, Yanjun;

Thermal mechanical analysis on railway brake disc: based on the FEniCSx

Abstract

Overview This repository is designed to model and calculate the temperature of railway brake discs using the Finite Element Method (FEM). The model incorporates heat transfer and elasticity equations to predict both temperature distribution and deformation in the brake disc during operation. Methodology The solution is based on the FEniCSx framework, which enables the efficient computation of coupled thermal and mechanical problems using FEM. This tool provides a powerful platform for solving complex partial differential equations, making it ideal for simulating the thermal and structural response of railway brake discs under operational loads. Acknowledgements Special thanks to the developers of FEniCSx for creating this invaluable tool that enables cutting-edge research in computational mechanics.

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    popularity
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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Top 10%
Average
Average