免疫遗传算法在百叶窗最优化热设计中的应用

Application of Immune Genetic Algorithm to the Optimal Thermal Design of Louvered Panels

考虑优化过程中辐射能量交换的特殊性,为了加速优化过程的进行,通过引入漫反射系统单元表面间辐射传递系数与角系数之间的关系来处理百叶窗的辐射能量交换;同时为了克服传统优化算法存在的缺陷,提出了一种免疫遗传算法,并且应用于百叶窗最优化热设计中。优化设计表明,与标准遗传算法相比,该优化算法具有较强收敛度与全局寻优能力,可以较好地用于最优化热设计中。

To improve the thermal performance, based on the theory of heat transfer and optimal algorithm, a computational method is presented to optimize thermally louverd panels. Considering the particularity possessed by radiative energy transfer throughout the optimization of louvered panels, accelerating the optimal process, radiative energy transfer of louvered panels is resolved by the introduction of the relation between radiative transfer coefficient and angle factor, which only could be applied to the diffuse system. At the same time, to overcome the limitations inherit in traditional optimal algorithms, an immune genetic algorithm is developed, and in addition, it is applied to the optimal thermal design oflouvered panels. It reveals that, in contrast to standard genetic algorithm, the immune genetic algorithm performs better, in the aspects of search speed as well as global search ability. And it could be well applied to thermal design.