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A validation of computational fluid dynamics temperature distribution prediction in a pulverized coal boiler with acoustic temperature measurement

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  • Modliński, Norbert
  • Madejski, Pawel
  • Janda, Tomasz
  • Szczepanek, Krzysztof
  • Kordylewski, Wlodzimierz

Abstract

The main objective of this work was to examine the capability of CFD (Computational Fluid Dynamics) on properly predicting temperature distribution in the combustion chamber. Numerous approaches were employed to verify CFD models of large-scale utility boilers. Furnace Exit Gas Temperature is one of the key values used for verification studies. Harsh environment and large dimensions inside the furnace make temperature measurement a complex task. Traditionally used suction pyrometry provides only local information. With this technique, while extremely accurate, it is practically impossible to obtain a representative temperature distribution at the furnace exit as measurements in different locations are not taken at the same time. Acoustic Pyrometry technique is the most appropriate for comprehensive CFD flame shape prediction verification. Not only average temperature value in a certain boiler cross-section can be continuously measured but also its complete two-dimensional distribution. CFD code was used to simulate the OP-650 front-fired boiler operation. The boiler is equipped with Acoustic Gas Temperature Measuring system located in a horizontal plane approximately 4 m under the furnace exit. Comparison of simulation results with measurements proves good accuracy of CFD results.

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  • Modliński, Norbert & Madejski, Pawel & Janda, Tomasz & Szczepanek, Krzysztof & Kordylewski, Wlodzimierz, 2015. "A validation of computational fluid dynamics temperature distribution prediction in a pulverized coal boiler with acoustic temperature measurement," Energy, Elsevier, vol. 92(P1), pages 77-86.
    • Handle: RePEc:eee:energy:v:92:y:2015:i:p1:p:77-86
    DOI: 10.1016/j.energy.2015.05.124
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    References listed on IDEAS

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    1. Karampinis, E. & Nikolopoulos, N. & Nikolopoulos, A. & Grammelis, P. & Kakaras, E., 2012. "Numerical investigation Greek lignite/cardoon co-firing in a tangentially fired furnace," Applied Energy, Elsevier, vol. 97(C), pages 514-524.
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    2. Yin, Linfei & Xie, Jiaxing, 2022. "Multi-feature-scale fusion temporal convolution networks for metal temperature forecasting of ultra-supercritical coal-fired power plant reheater tubes," Energy, Elsevier, vol. 238(PA).
    3. Pieter Rousseau & Ryno Laubscher & Brad Travis Rawlins, 2023. "Heat Transfer Analysis Using Thermofluid Network Models for Industrial Biomass and Utility Scale Coal-Fired Boilers," Energies, MDPI, vol. 16(4), pages 1-49, February.
    4. Chen, Xi & Zhong, Wenqi & Li, Tianyu, 2023. "Fast prediction of temperature and chemical species distributions in pulverized coal boiler using POD reduced-order modeling for CFD," Energy, Elsevier, vol. 276(C).
    5. Ma, Lun & Fang, Qingyan & Yin, Chungen & Wang, Huajian & Zhang, Cheng & Chen, Gang, 2019. "A novel corner-fired boiler system of improved efficiency and coal flexibility and reduced NOx emissions," Applied Energy, Elsevier, vol. 238(C), pages 453-465.
    6. Hashimoto, Nozomu & Watanabe, Hiroaki & Kurose, Ryoichi & Shirai, Hiromi, 2017. "Effect of different fuel NO models on the prediction of NO formation/reduction characteristics in a pulverized coal combustion field," Energy, Elsevier, vol. 118(C), pages 47-59.
    7. Laubscher, Ryno & Rousseau, Pieter, 2020. "Numerical investigation on the impact of variable particle radiation properties on the heat transfer in high ash pulverized coal boiler through co-simulation," Energy, Elsevier, vol. 195(C).
    8. Modlinski, Norbert & Hardy, Tomasz, 2017. "Development of high-temperature corrosion risk monitoring system in pulverized coal boilers based on reducing conditions identification and CFD simulations," Applied Energy, Elsevier, vol. 204(C), pages 1124-1137.
    9. Li, Xinli & Wang, Yingnan & Zhu, Yun & Yang, Guotian & Liu, He, 2021. "Temperature prediction of combustion level of ultra-supercritical unit through data mining and modelling," Energy, Elsevier, vol. 231(C).
    10. Kantorek, Marcin & Jesionek, Krzysztof & Polesek-Karczewska, Sylwia & Ziółkowski, Paweł & Stajnke, Michał & Badur, Janusz, 2021. "Thermal utilization of meat-and-bone meal using the rotary kiln pyrolyzer and the fluidized bed boiler – The performance of pilot-scale installation," Renewable Energy, Elsevier, vol. 164(C), pages 1447-1456.
    11. Michalina Kurkus-Gruszecka & Piotr Krawczyk & Janusz Lewandowski, 2021. "Numerical Analysis on the Flue Gas Temperature Maintenance System of a Solid Fuel-Fired Boiler Operating at Minimum Loads," Energies, MDPI, vol. 14(15), pages 1-14, July.

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