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

33 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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