Annual hourly CFD simulation: new approach— an efficient scheduling algorithm for fast iteration convergence

Computational fluid dynamics (CFD) is one of the branches of fluid mechanics that uses numerical meth-ods and algorithms to solve and analyze problems that involve fluid flows. Annual hourly fast flow simula-tions are needed for some applications in building in-dustry, such as the conceptual design of indoor envi-ronment, or coupled with energy simulation to pro-vide deep analysis on the performance of the build-ings. Year round simulation, which consists of 8760(365⇥24) independent hourly simulations, is needed to help the designer investigate the problem clearly. However, CFD computation is time consuming, and usually only two or three extreme cases can be sim-ulated in practice. Annual hourly simulation using the traditional method can be considered as a com-putational intractable problem. Based on previous researches (Yue Wang and Feng, 2012a)(Yue Wang and Feng, 2012b), even though the fast fluid dy-namics (FFD) algorithm combined with the General Purposed Graphics Processing Unit (GPGPU) hard-ware acceleration can make CFD simulation much faster(400x), annual hourly simulation still requires CFD performance to be further improved by 10-20x to make it practical. In this study, a minimal spanning tree based scheduling algorithm is developed, which always gives the best CFD simulation strategy that reuses previous calculated results to generate new re-sults, thus making iteration convergence much faster. It is shown in the paper that the annual hourly simu-lation by GPGPU accelerated FFD by using this new algorithm requires a similar simulation time to the one used to perform two or three extreme cases of simula-tion using the traditional method.