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Optimizing the heat transfer performance of the recovery boiler superheaters using simulated annealing, surrogate modeling, and computational fluid dynamics

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  • Maakala, Viljami
  • Järvinen, Mika
  • Vuorinen, Ville

Abstract

The energy efficiency of recovery boiler power plants is largely influenced by the heat transfer to the superheaters. In the design process of such very large-scale applications, one of the key challenges is the a priori geometry optimization by robust numerical approaches. The main objectives of this work are to demonstrate a numerical optimization framework and to optimize the geometry of the superheater region to enhance the heat transfer. The framework is implemented as a surrogate-based optimization method, which combines simulated annealing, local polynomial regression, and computational fluid dynamics. The novelty of this work consists of the following: 1) The optimization framework is designed and introduced. 2) The connection between the geometry and heat transfer is quantified by formulating the optimal design curve. 3) The optimal design for a typical, existing recovery boiler is identified. The results indicate that the uniformity of the flow field is improved, and the heat transfer rate is increased by 5%. 4) The results indicate the importance of minimizing the separation vortices through the geometrical design with a strong linkage to the overall heat transfer rate. 5) The potential of optimization methods in this very large-scale energy production application is demonstrated for the first time.

Suggested Citation

  • Maakala, Viljami & Järvinen, Mika & Vuorinen, Ville, 2018. "Optimizing the heat transfer performance of the recovery boiler superheaters using simulated annealing, surrogate modeling, and computational fluid dynamics," Energy, Elsevier, vol. 160(C), pages 361-377.
    • Handle: RePEc:eee:energy:v:160:y:2018:i:c:p:361-377
    DOI: 10.1016/j.energy.2018.07.002
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    Cited by:

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    6. Lim, Jonghun & Kim, Junghwan, 2022. "Optimizing ash deposit removal system to maximize biomass recycling as renewable energy for CO2 reduction," Renewable Energy, Elsevier, vol. 190(C), pages 1006-1017.

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