Potential-flow-based airflow and heat transfer models have been proposed as a computationally efficient alternative to the Navier-Stokes Equations for predicting the three-dimensional flow field in data center applications. These models are simple, solve quickly, and capture much of the fluid flow physics, but ignore buoyancy and frictional effects, i.e., rotationality, turbulence, and wall friction. However, a comprehensive comparison of the efficiency and accuracy of these methods versus more sophisticated tools, like CFD, is lacking. The main contribution of this paper is a study of the performance of potential-flow methods compared to CFD in eight layouts inspired by actual data center configurations. We demonstrate that potential-flow methods can be helpful in data center design and management applications.

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