No abstract

In this study, an open-source computational fluid dynamics (CFD) model was developed based on OpenFOAM libraries for the accurate and robust simulation of thermal distribution in a data center. Two boundary conditions were developed for the temperature field in the black-box modeling of server components. The numerical model was first validated by comparing numerical results with the experimental measurements for three benchmark problems in the field of thermal engineering. Then, thermal distribution in an open-aisle data center was simulated using the proposed numerical model and results were compared with the experimental measurements. The consistency between numerical results and previous experimental measurements indicates that the present numerical model can be reliably used for the efficiency assessment of air-cooled data centers. Efficiency of the data center can be evaluated with respect to four metrics in the proposed numerical model. In addition to the determination of the overall efficiency, distribution of the efficiency can be monitored over the racks to capture thermal zones where the efficiency decreases due to the recirculation effects and cold air by-pass.

Modeling IT equipment is of critical importance for the simulations of flow and thermal structures in air cooled data centers. Turbulent flow undergoes a significant pressure drop through the server due to the energy losses originating from the internal components. Therefore, there is an urgent need to develop a fast and an accurate method for the calculation of pressure losses inside server components for data center applications. In this study, high resolution numerical simulations were performed on an OCP (Open Compute Project) server under various inlet flow rates for inactive and active conditions. Meanwhile, one key challenge of modeling complete geometry of the server results from using an intense mesh even for a single server. To address this challenge, the server was modeled as a porous zone to mimic inertia and viscous resistance in a realistic way. Comparison of the results of porous and complete models showed that the proposed model could calculate pressure drop accurately even when the number of cells in the server was reduced to 0.3% of the complete model. Porosity coefficients were determined from the numerical simulations conducted in a broad range of air discharge for both active and inactive conditions. Errors in the calculation of pressure drop may result in a significant deviation in the prediction of the temperature rise over the server. Thus, the present model can effectively be used for the fast and accurate prediction of pressure drop inside a server component rather than solving internal flow on an intense mesh, while simulating airflow inside an air-cooled data center, which is crucial for the design safety of data centers. Finally, calculated porosity coefficients can be used for the prediction of the pressure drop in a server, while designing data centers based on numerical simulations.