List of papers for 2015:
- Comparison of optimized thermal performance of square and circular ammonia-cooled microchannel heat sink with genetic algorithm. Normah, G. M., Oh, J. T., Chien, N. B., Choi, K., -I., Robiah, A., Energy Conversion and Management. Volume 102. Pp 59- 65.
Abstract
Minimization of the thermal resistance and pressure drop of a microchannel heat sink is desirable for efficient heat removal which is becoming a serious challenge due to the demand for continuous miniaturization of such cooling systems with increasing high heat generation rate. However, a reduction in the thermal resistance generally leads to the increase in the pressure drop and vice versa. This paper reports the outcome of optimization of the hydraulic diameter and wall width to channel width ratio of square and circular microchannel heat sink for the simultaneous minimization of the two objectives; thermal resistance and pressure drop. The procedure was completed with multi-objective genetic algorithm (MOGA). Environmentally friendly liquid ammonia was used as the coolant and the thermophysical properties have been obtained based on the average experimental saturation temperatures measured along an ammonia-cooled 3.0 mm internal diameter horizontal microchannel rig. The optimized results showed that with the same hydraulic diameter and pumping power, circular microchannels have lower thermal resistance. Based on the same number of microchannels per square cm, the thermal resistance for the circular channels is lower by 21% at the lowest pumping power and lower by 35% at the highest pumping power than the thermal resistance for the square microchannels. Results obtained at 10 °C and 5 °C showed no significant difference probably due to the slight difference in properties at these temperatures.
Keyword: Optimization; Microchannel heat sink; Multi-objective genetic algorithm; Ammonia; Thermal resistance
http://www.sciencedirect.com/science/article/pii/S0196890415001132
- Performance optimization of a microchannel heat sink using the Improved Strength Pareto Evolutionary Algorithm (SPEA2). Adham, A. M., Mohd-Ghazali, N., Ahmad, R. Journal of Engineering Thermophysics. 1 February 2015. 24:1. Pp 86 – 100.
Abstract
In this paper, a feasible optimization scheme for rectangular microchannel heat sinks, which incorporates the thermal resistance model and the Improved Strength Pareto Evolutionary Algorithm (SPEA2), is reported. An alternative coolant, namely, ammonia gas, is used to improve the overall thermal and hydrodynamic performances of the considered system. Results from the optimization showed significant reduction in the total thermal resistance compared to the conventional air-cooled systems up to 35% for the same allowable pumping power. The SPEA2 exhibited excellent performance when it was compared to another multiobjective algorithm, NSGA2. The results reported in this study open the door for the incorporation of some other algorithms, which have not been used in the optimization of microchannel heat sinks. Finally, the outcome of this paper predicts a promising future for the usage of ammonia gas in the area of electronics cooling.
Keyword:
http://link.springer.com/article/10.1134%2FS1810232815010087
- Perturbation parameters tuning of multi-objective optimization differential evolution and its application to dynamic system modeling. Zakaria, M. Z., Jamaluddin, H., Ahmad, R., Harun, A., Hussin, R., Khalil, A., N., M., Naim, M. NK. M., Annuar, A. F. Jurnal Teknologi. Volume 75, Issue 11. Pp 77 – 90. Scopus.
Abstract
This paper presents perturbation parameters for tuning of multi-objective optimization differential evolution and its application to dynamic system modeling. The perturbation of the proposed algorithm was composed of crossover and mutation operators. Initially, a set of parameter values was tuned vigorously by executing multiple runs of algorithm for each proposed parameter variation. A set of values for crossover and mutation rates were proposed in executing the algorithm for model structure selection in dynamic system modeling. The model structure selection was one of the procedures in the system identification technique. Most researchers focused on the problem in selecting the parsimony model as the best represented the dynamic systems. Therefore, this problem needed two objective functions to overcome it, i.e. minimum predictive error and model complexity. One of the main problems in identification of dynamic systems is to select the minimal model from the huge possible models that need to be considered. Hence, the important concepts in selecting good and adequate model used in the proposed algorithm were elaborated, including the implementation of the algorithm for modeling dynamic systems. Besides, the results showed that multi-objective optimization differential evolution performed better with tuned perturbation parameters.
Keyword: Model structure selection; System identification; Multi-objective optimization; NSGA-II; Differential evolution
http://www.jurnalteknologi.utm.my/index.php/jurnalteknologi/article/view/5335