Energy and cost optimization of shell and tube heat exchanger with helical baffles using Kriging metamodel based on MOGA

  • Jian Wen
  • , Huizhu Yang
  • , Guanping Jian
  • , Xin Tong
  • , Ke Li
  • , Simin Wang

Research output: Contribution to journalArticlepeer-review

76 Scopus citations

Abstract

In order to overcome the dependence on empirical correlations and to achieve a more accurate results for modeling the computer response, an improved algorithm combing a Kriging response surface and the multi-objective genetic algorithm (MOGA) for the optimization design of shell and tube heat exchanger with helical baffles (STHXsHB) is proposed in this paper. The helical angles β, baffle overlap proportion e and inlet volume flow rate V are considered as optimization parameters, in which the heat transfer rate and total cost are optimized by multi-objective optimization. The results show that compared with the real solutions of CFD simulation, the optimized results illustrated a good agreement within ±3% error. Therefore, the optimization method is verified to be successful. Besides the obtained Pareto-optimal points show that a small helical angle with 15° and the baffle overlap proportion is equal to 0.25 are beneficial to trade off the heat transfer rate and total cost of STHXsHB. Furthermore, the comparison between the optimum STHXsHB and a conventional shell and tube heat exchanger with segmental baffles (STHXsSB) are carried out. The results show that the comprehensive performances of the optimum STHXsHB are better. The evaluation index PEA and PEB increase by 76.5-91.2% and 69.0-84.5%, respectively. Therefore, it can be concluded that employed helical baffles in the STHXs can obtain a better performance. Moreover, this new method can be used to optimize the STHXsHB and the conclusions are benefit in the design of STHXsHB for energy saving and cost reduction.

Original languageEnglish
Pages (from-to)29-39
Number of pages11
JournalInternational Journal of Heat and Mass Transfer
Volume98
DOIs
StatePublished - Jul 2016

Keywords

  • Genetic algorithm
  • Helical baffles
  • Kriging response surface
  • Multi-objective optimization
  • Shell and tube heat exchanger

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