Issue |
MATEC Web of Conf.
Volume 399, 2024
2024 3rd International Conference on Advanced Electronics, Electrical and Green Energy (AEEGE 2024)
|
|
---|---|---|
Article Number | 00011 | |
Number of page(s) | 6 | |
DOI | https://doi.org/10.1051/matecconf/202439900011 | |
Published online | 24 June 2024 |
Characteristics of Coal Dust Deposition in Boiler Tail Gas Pipelines
1 School of Electrical Engineering, Xinjiang University, 830047 Urumqi, China
2 Laboratory of Energy Carbon Neutrality, School of Electrical Engineering, Xinjiang University, 830047 Urumqi, China
3 Center of New Energy Research, School of Future Technology, Xinjiang University, 830047 Urumqi, China
* Corresponding Author: luhao@xju.edu.cn
Coal dust deposition in boiler tail gas pipelines can significantly affect boilers’ thermal and energy efficiency. This study investigates the deposition characteristics of coal dust particles in boiler tail gas tubes in variable cross-section tubes. Numerical simulations were performed using the Reynolds Stress Model and the Discrete Particle Model. User-defined functions coding is used to construct the particle deposition model in the particle deposition model. The study analyses the distribution of turbulent kinetic energy locations in the gradient tube, compares the distribution of particle deposition on its wall, and concludes that the deposition distribution of coal dust particles in the gradient tube is slightly different for different particle sizes. Smaller particles have a higher deposition efficiency in equal cross-section pipes than larger particles. Particle size also has a significant effect on pipe taper and expansion. The results of this study can provide theoretical guidance for optimising the design of boiler tail gas pipelines, improving energy efficiency, and reducing environmental pollution.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.