• 文献标题:   A combined multi-criterion optimization to determine optimum geometrical parameters for flow of an ecofriendly graphene-based nano fluid inside tube enhanced with twisted conical strip inserts
  • 文献类型:   Article
  • 作  者:   BAHIRAEI M, RAHIMI Z, NAZARI F
  • 作者关键词:   green nanofluid, graphene nanoplatelet, twisted conical strip insert, optimization, neural network, heat transfer enhancement
  • 出版物名称:   POWDER TECHNOLOGY
  • ISSN:   0032-5910 EI 1873-328X
  • 通讯作者地址:  
  • 被引频次:   10
  • DOI:   10.1016/j.powtec.2020.08.044
  • 出版年:   2021

▎ 摘  要

Thermohydraulic attributes of a biologically produced nanofluid containing graphene nanoplatelets inside a pipe fitted with twisted conical strip inserts are optimized. The slant angle, geometry angle, and pitch are the geometrical parameters, which are optimized to reach highest Nusselt number and lowest friction coefficient. Genetic algorithm in combination with compromise programming method is used. The slant angle and pitch have more profound impacts on Nusselt number in comparison with their influence on friction factor, while the geometry angle has a greater effect on the friction factor. In the case that the friction coefficient and Nusselt number have rather similar priorities, one should utilize the larger slant angles and smaller geometry angles. Under similar priority of two outputs, at the relevant optimum point, Nusselt number and friction factor respectively increase by about 40.4% and 2.2 times relative to those in the plain tube. (C) 2020 Elsevier B.V. All rights reserved.