Optimization of temperature distribution and heat flux functions for cylindrical and conical micro-fins by applying genetic algorithm

One of the engineering researches is improving the devises performance. In fact, after the devises are designed, optimization is necessary to obtain more performance, less cost and fast turnaround production. In this research, the single- and multi-objective genetic algorithms were applied to optimize the distribution of temperature and heat flux functions for both cylindrical and conical micro-pin fins. First, each equation was optimized separately in single-objective genetic algorithm, and then, both equations were optimized interdependently in multi-objective genetic algorithm. The desired values of derived equations are less temperature and more heat flux within micro-pin fins. The flow conditions, material properties and geometrical parameters were different cases which were simultaneously used in single- and multi-objective optimization approaches. The optimization parameters involved the design of the critical parameters of the micro-pin fins, including the size of the root and tip radius, length of micro-pin fin, fin and fluid thermal conductivity coefficients, convection heat transfer coefficient and relative roughness. Results showed that for cylindrical pin fin, in each arrangement, the value of 0.0 as minimum temperature distribution function was found, which means with suitable pin fin design, the fin tip temperature could reach to the environment temperature. The minimum temperature distribution function for conical pin fin was found to be near zero. Among four considered cases, geometry limitation had the maximum temperature value of 0.0045. The fin root radius and the coolant conductivity had significant effects on the cylindrical and conical pin fin, respectively.