AI & ML
Modeling Liquid-Cooled Data Centers in EnergyPlus
arXiv cs.SY0 views
arXiv:2610.33148v1 Announce Type: new Abstract: As AI workloads accelerate data center transition toward high-density racks with direct-to-chip (DTC) liquid cooling, existing simulation tools remain limited in evaluating whole-building and multi-year efficiency. To bridge this gap, we develop a native EnergyPlus object, ElectricEquipment:ITE:LiquidCooled, that models DTC liquid cooling for chilled-water and warm-water architectures as plant-loop components. It couples facility-water loops, rack-side secondary loops, coolant distribution units, and chip-junction temperatures within a single solver. Validation against an independent Modelica implementation across 21 operating conditions, including two full-year runs compared at one-minute resolution, yields loop-temperature RMSE at or below 0.021 K, well within the 0.1 K acceptance threshold. Our case study demonstrates that warm-water liquid cooling reduces annual PUE from 1.43 to 1.25, eliminates on-site water use, and cuts total facility energy by 37.9% relative to an air-cooled baseline. By embedding liquid-cooling logic into EnergyPlus, our work provides whole-building, long-term energy modeling for high-density AI infrastructure within an open-source framework.
Source:https://arxiv.org/abs/2610.33148PreviousBlind Random Search with Noisy Measurements: Almost Sure Convergence and Convergence RatesNextTerra-Fi: Decoupling Sensing and Wireless Depths for Sustainable Deep Underground Monitoring
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