Abstract
Fast indoor airflow simulations are necessary for building emergency management, preliminary design of sustainable buildings, and real-time indoor environment control. The simulation should also be informative since the airflow motion, temperature distribution, and contaminant concentration are important. Unfortunately, none of the current indoor airflow simulation techniques can satisfy both requirements at the same time. Our previous study proposed a Fast Fluid Dynamics (FFD) model for indoor flow simulation. The FFD is an intermediate method between the Computational Fluid Dynamics (CFD) and multizone/zonal models. It can efficiently solve Navier–Stokes equations and other transportation equations for energy and species at a speed of 50 times faster than the CFD. However, this speed is still not fast enough to do real-time simulation for a whole building. This paper reports our efforts on further accelerating FFD simulation by running it in parallel on a Graphics Processing Unit (GPU). This study validated the FFD on the GPU by simulating the flow in a lid-driven cavity, channel flow, forced convective flow, and natural convective flow. The results show that the FFD on the GPU can produce reasonable results for those indoor flows. In addition, the FFD on the GPU is 10–30 times faster than that on a Central Processing Unit (CPU). As a whole, the FFD on a GPU can be 500–1500 times faster than the CFD on a CPU. By applying the FFD to the GPU, it is possible to do real-time informative airflow simulation for a small building.
