Abstract
Recently, increased attention has been given to the coupling of computational fluid dynamics (CFD) with the fuzzy logic control system for obtaining the optimum prediction of many complex engineering problems. The data provided to the fuzzy system can be obtained from the accurate computational fluid dynamics of such engineering problems. Windcatcher performance to achieve thermal comfort conditions in buildings, especially in hot climate regions, is considered as one such complex problem. Windcatchers can be used as natural ventilation and passive cooling systems in arid and windy regions in Saudi Arabia. Such systems can be considered as the optimum solution for energy-saving and obtaining thermal comfort in residential buildings in such regions. In the present paper, three-dimensional numerical simulations for a newly-developed windcatcher model have been performed using ANSYS FLUENT-14 software. The adopted numerical algorithm is first validated against previous experimental measurements for pressure coefficient distribution. Different turbulence models have been firstly applied in the numerical simulations, namely, standard k-epsilon model (1st and 2nd order), standard Wilcox k-omega model (1st and 2nd order), and SST k-omega model. In order to assess the accuracy of each turbulence model in obtaining the performance of the proposed model of the windcatcher system, it is found that the second order k-epsilon turbulence model gave the best results when compared with the previous experimental measurements. A new windcatcher internal design is proposed to enhance the ventilation performance. The fluid dynamics characteristics of the proposed model are presented, and the ventilation performance of the present model is estimated. The numerical velocity profiles showed good agreement with the experimental measurements for the turbulence model. The obtained results have shown that the second order k-epsilon turbulence can predict the different important parameters of the windcatcher model. Moreover, the coupling algorithm of CFD and the fuzzy system for obtaining the optimum operating parameters of the windcatcher design are described.