Simulating growth of ash deposit in boiler heat exchanger tube based on CFD dynamic mesh technique
•Dynamic CFD simulation method is developed for growth of ash deposit.•Shape variation of ash deposit was simulated by dynamic mesh technique.•Surface temperature variation of ash deposit with time was predicted.•Role of thermophoresis on the formation of ash deposit was studied. Ash deposition on h...
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Veröffentlicht in: | Fuel (Guildford) 2020-01, Vol.259, p.116083, Article 116083 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •Dynamic CFD simulation method is developed for growth of ash deposit.•Shape variation of ash deposit was simulated by dynamic mesh technique.•Surface temperature variation of ash deposit with time was predicted.•Role of thermophoresis on the formation of ash deposit was studied.
Ash deposition on heat transfer surfaces is still a significant problem in existing conventional utility boilers. Understanding the formation of ash deposit is thereby very important, which is helpful to optimize the design and operation procedure of boilers. In this study, a dynamic numerical method based on the commercial software ANSYS FLUENT was developed to predict the growth of ash deposit on the deposition probe in a 300 kW slagging test furnace fired with Zhundong coal. Based on the CFD dynamic mesh technique, both shape variations and surface temperature variations of ash deposit with time were predicted. Time-dependent deposition behaviors on the deposition probe with different initial metal wall temperatures were presented. The simulation results (e.g. thickness, heat flux, surface temperature, and shape of ash deposit) are in good agreement with the experimental data. It shows that increased surface temperature of ash deposit can significantly increase ash deposition mass. It was also determined that the shape variation of ash deposit can obviously reduce the impact mass and deposition mass during ash deposition by the comparative studies. The developed simulation method is proved to be a useful tool to predict ash deposition behavior with more detailed information. |
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ISSN: | 0016-2361 1873-7153 |
DOI: | 10.1016/j.fuel.2019.116083 |