Assessment of two different optimization principles applied in heat conduction

Abstract

Optimization principles play a crucial role in the intensification of the heat-transfer process. In this study, we assess and compare two principles, i.e., the entransy dissipation extremum (EDE) principle and the minimum entropy generation (MEG) principle, used in a typical “area to point” heat conduction problem solved via a cellular automaton algorithm. The simulated results indicate that both rules can ameliorate the tree-network conductive path, leading to a more uniform thermal field and lower average and maximum temperatures. In contrast to the MEG principle, the EDE principle is more appropriate to be linked to the algorithm when dealing with the “area to point” heat conduction optimization, especially with a higher conductivity ratio, kp/k0, between the high conductivity material and the low conductivity material and the fraction of high conductivity, ϕ0. With the analysis of total entransy dissipation rate and entropy generation of the domain optimized by two principles, the results indicate that the EDE principle is more suitable for the heat-transfer processes without heat–work conversion. Moreover, optimization via reducing the total entransy dissipation rate exhibits better performance in decreasing the equivalent resistance theoretically.