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Unsteady-state heat transfer characteristics of spiral water wall tube in advanced-ultra-supercritical boilers from experiments and distributed parameter model

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  • Ge, Xueli
  • Zhang, Zhongxiao
  • Fan, Haojie
  • Zhang, Jian
  • Bi, Degui

Abstract

The design and operation of water walls are crucial for ultra-supercritical boilers, particularly with the advent of advanced-ultra-supercritical (A-USC) boilers. In this study, heat transfer characteristics for a spiral water wall were analysed in a 0.3 MWt experimental facility to understand the combustion and hydrodynamics of A-USC boilers. The working pressure ranged from 13.5 to 41.0 MPa, while mass flux varied from 124.4 to 557.1 kg/(m2⋅s), along with a maximum heat flux of approximately 448 kW/m2. As the heat flux was increased, evidently enhanced and deteriorated heat transfer performances were observed near the pseudo-critical point during the unsteady operating process. The distributed parameter model was employed along with different correlations from literatures to predict the distribution of temperatures and heat transfer coefficients. Predicted temperatures were compared with the experimental measurements. The results demonstrated that distributed parameter model combining with appropriate correlation for each region, yielded good agreement with the experimental data. Particularly, for the top, middle, and bottom regions of the furnace, the correlations by Swenson et al., Jackson et al., and Mokry et al., respectively are found to be suitable. Furthermore, a criterion for heat transfer deterioration for the spiral water wall was also suggested for the A-USC units.

Suggested Citation

  • Ge, Xueli & Zhang, Zhongxiao & Fan, Haojie & Zhang, Jian & Bi, Degui, 2019. "Unsteady-state heat transfer characteristics of spiral water wall tube in advanced-ultra-supercritical boilers from experiments and distributed parameter model," Energy, Elsevier, vol. 189(C).
    • Handle: RePEc:eee:energy:v:189:y:2019:i:c:s0360544219318535
    DOI: 10.1016/j.energy.2019.116158
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    Cited by:

    1. Li, Haozhe & Song, Meiqi & Liu, Xiaojing, 2024. "Interpretable machine learning-based prediction and analysis of supercritical fluid heat transfer characteristics at different boundary conditions," Energy, Elsevier, vol. 308(C).
    2. Zima, Wiesław & Grądziel, Sławomir & Cebula, Artur & Rerak, Monika & Kozak-Jagieła, Ewa & Pilarczyk, Marcin, 2023. "Mathematical model of a power boiler operation under rapid thermal load changes," Energy, Elsevier, vol. 263(PC).

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