Two-step optimal design method using genetic algorithms and CFD-coupled simulation for indoor thermal environments

The optimal design method of the indoor thermal environment using CFD coupled simulation and genetic algorithms (GA) is developed in this study. CFD could analyze the thermal environment considering the distribution of temperature and air flow in a room. Therefore, it would be appropriate to use CFD for the optimal design method considering their distribution. In this study, the optimal design means the most appropriate boundary conditions of the room among the conditions where the design target of the indoor thermal environment is achieved. The authors have been examined many types of the optimal design methods using CFD, and find that the high calculating load and the different results according to the initial conditions, among other factors, are the difficulties of the optimal method. Considering these difficulties, a two step optimal design method for the indoor thermal environment is proposed. It includes the GA for determining the optimal design for the indoor thermal environment. To examine the performance of this method, the optimal design of a hybrid ventilation system, which uses the natural cross ventilation and the radiant cooling panel, is completed. The optimal design which satisfies the design target (thermal comfort, minimum cooling load, and minimum vertical temperature difference) is found using a two step optimal design method.