Optimizing the Heat Transfer Performance of the Recovery Boiler Superheaters Using Simulated Annealing, Surrogate Modeling, and Computational Fluid Dynamics

Viljami Maakala, Mika Järvinen, Ville Vuorinen

Research output: Contribution to journalArticleScientificpeer-review

7 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)361-377
Number of pages17
JournalEnergy
Volume160
DOIs
Publication statusPublished - 1 Oct 2018
MoE publication typeA1 Journal article-refereed

Keywords

  • Computational fluid dynamics
  • Energy efficiency
  • Heat transfer
  • Optimization
  • Recovery boiler
  • Surrogate modeling

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