A smart and sustainable energy approach by performing multi-objective optimization in a minichannel heat sink for waste heat recovery applications

Abstract

Minichannel heat sink is widely used in waste heat recovery systems for their compactness and ability to recover heat effectively from high heat flux applications. However, the heat recovery efficiency is constrained by the flow configurations resulting in flow maldistribution. Numerous neural network combined evolutionary algorithms have been used to reduce pressure drop and flow maldistribution factors in the literature. But it is very challenging to assign appropriate weights to these parameters with no physical significance between them for optimization studies. To overcome this, TOPSIS-based optimization studies have been used in the current work to reduce the flow maldistribution factor (ϕ) and increase the Nusselt number (Nu) with ribs and inclined structures. Four Minichannel designs are studied to assess the channel heat recovery efficiency from small-scale incinerators using water and Graphene oxide (GO) nanofluid for three different volume fractions of GO-0.02%, GO-0.07%, and GO-0.12%. The motive is to determine an optimal nanofluid volume fraction and a suitable Minichannel configuration for the given heat flux. The TOPSIS method handles five criteria, including the combination of weightage for the maldistribution factor and Nusselt number. For criteria I ((ϕ)<inf>min</inf>: (Nu)<inf>max</inf> = 0.0:1.0) maximum weightage is given to heat transfer, the ribbed channel has gained a higher performance score for GO-0.07% nanofluid volume fraction. For criteria V ((ϕ)<inf>min</inf>: (Nu)<inf>max</inf> = 1.0:0.0) maximum weightage is given to maldistribution reduction, the ribbed inclined channel has gained with significantly higher performance score for all the studied nanofluid volume fractions. Further, the study is extended to determine the heat recovery efficiency, and it is found that with the increase in mass flow rate and nanofluid volume fraction, the heat recovery efficiency increases significantly. In particular, the maximum heat recovery efficiency of 66% was obtained for ribbed Minichannel using GO-0.12% nanofluid. © 2023 Elsevier Ltd