Assessment of two different optimization principles applied in heat conduction

AbstractOptimization 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.摘要优化原则对于传热过程强化十分重要。本文针对火积耗散极值原则(EDE)以及最小熵产原则(MEG)两种优化原则在 “面-点”导热问题中的应用进行了评价和比较。该过程采用格子气自动机算法进行模拟。结果表明,两种优化原则均可改善其树状网络结构的导热路径,并导致温度分布更加均匀以及平均温度及最大温度的降低。在该算法下,EDE原则更加适用于处理该“面-点”导热优化问题,特别是在导热比kp/k0和高导热材料分率ϕ0较大的情况下。针对总火积耗散率及熵产的分析结果表明,EDE原则更加适用于没有热功转换的传热过程优化。此外,降低总火积耗散率可以降低传热过程的等价热阻,因而表现出更好的传热性能。