Abstract

Data centers have complex environments that undergo constant changes due to fluctuations in IT load, commissioning and decommissioning of IT equipment, heterogeneous rack architectures and varying environmental conditions. These dynamic factors often pose challenges in effectively provisioning cooling systems, resulting in higher energy consumption. To address this issue, it is crucial to consider data center thermal heterogeneity when allocating workloads and controlling cooling, as it can impact operational efficiency. Computational Fluid Dynamics (CFD) models are used to simulate data center heterogeneity and analyze the impact of two different cooling mechanisms on operational efficiency. This research focuses on comparing the cooling based on facility water for Rear Door Heat Exchanger (RDHx) and conventional Computer Room Air Conditioning (CRAH) systems in two different data center configurations. Efficiency is measured in terms of ΔT across facility water. Higher ΔT will result in efficient operation of chillers. The actual chiller efficiency is not calculated as it would depend on local ambient conditions in which the chiller is operated.

The first data center model represents a typical enterpriselevel configuration where all servers and racks have homogeneous IT power. The second model represents a colocation facility where server/rack power configurations are randomly distributed. These models predict temperature variations at different locations based on IT workload and cooling parameters. Traditionally, CRAH configurations are selected based on total IT power consumption, rack power density, and required cooling capacity for the entire data center space. On the other hand, RDHx can be scaled based on individual rack power density, offering localized cooling advantages. Multiple workload distribution scenarios were simulated for both CRAH and RDHx-based data center models. The results showed that RDHx provides a uniform thermal profile across the data center, irrespective of server/rack power density or workload distribution. This characteristic reduces the risk of over- or under-provisioning racks when using RDHx. Operational efficiency is compared in terms of difference in supply and return temperature of facility water for CRAH and RDHx units based on spatial heat dissipation and workload distribution. RDHx demonstrated excellent cooling capabilities while maintaining a higher ΔT, resulting in reduced cooling energy consumption, operational carbon footprint (?), and water usage.

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