Advanced thermal management strategies for energy-efficient data centers
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A simplified computational fluid dynamics/heat transfer (CFD/HT) model for a unit cell of a data center with a hot aisle-cold aisle (HACA) layout is simulated. Inefficiencies dealing with the mixing of hot air present in the room, with the cold inlet air leading to a loss of cooling potential are identified. For existing facilities, an algorithm called the Ambient Intelligence based Load Management (AILM) is developed which enhances the net data center heat dissipation capacity for given energy consumption at the facilities end. It gives a scheme to determine how much and where the computer loads should be allocated, based on the differential loss in cooling potential per unit increase in server workload. While the gains predicted are validated numerically initially, experimental validation is conducted using server simulators. For new facilities, a novel layout of the data center is designed, which uses scalable pods (S-Pod) based cabinet arrangement and air delivery. For the same floor space, the S-Pod and HACA facilities are simulated for different velocities, and the results are compared. An approach to incorporate heterogeneity in data centers, both for lower heat dissipation and liquid cooled racks has been established. Various performance metrics for data centers have been analyzed and sorted on the basis of their applicability. Finally, a roadmap for the transformation of the existing facilities to a state of higher cognizance of Facilities/IT performance is laid out.