TY - JOUR
T1 - Fast and informative flow simulations in a building by using fast fluid dynamics model on graphics processing unit
AU - Zuo, Wangda
AU - Chen, Qingyan
N1 - Funding Information:
This study was funded by the US Federal Aviation Administration (FAA) Office of Aerospace Medicine through the National Air Transportation Center of Excellence for Research in the Intermodal Transport Environment under Cooperative Agreement 07-CRITE-PU and co-funded by the Computing Research Institute at Purdue University. Although the FAA has sponsored this project, it neither endorses nor rejects the findings of this research. The presentation of this information is in the interest of invoking technical community comment on the results and conclusions of the research.
PY - 2010/3
Y1 - 2010/3
N2 - 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.
AB - 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.
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U2 - 10.1016/j.buildenv.2009.08.008
DO - 10.1016/j.buildenv.2009.08.008
M3 - Article
AN - SCOPUS:70350588997
SN - 0360-1323
VL - 45
SP - 747
EP - 757
JO - Building and Environment
JF - Building and Environment
IS - 3
ER -