Efficient Data Center Modeling for Princeton University

1. CFD Modeling of Princeton Data Center Jamie Wilkinson, Connor Nolan, Jeff Kling Paul Bemis, Project Advisor Department of Mechanical Engineering, University of New Hampshire, Durham NH 1. Creating a Geometrical Model • Computational fluid dynamic (CFD) software program of choice is CoolSim • Created by Paul Bemis and his team at Applied Math Modeling, Inc. • Create an initial small scale model to understand basic data center characteristics (Fig. 2) • Three notable elements 1. Rear door heat exchangers 2. Chimneys 3. 3 story system • Schematics provided by Charles Augustine of Princeton Project goal: create a working model of Princeton’s data center to within 10% accuracy Fig. 5: First model of Princeton’s data center, before any validation. Project Motivation: • Opportunity to explore building efficiency technology and the engineering design process • Improving the thermal efficiency will save Princeton University money by reducing energy cost • Project will help Princeton to reduce greenhouse emissions and obtain a lower carbon footprint • Gain valuable experience concerning data centers and CFD software. 3-5. Validation • Project group traveled to Princeton to gather temperature measurements • Check differences between predicted and measured average temperatures • Inlet error: 0.3% (68.57 F predicted versus 68.77 F measured) • Outlet error: 5% (81 F predicted versus 76.75 F measured) • All temperatures within acceptable range set by ASHRAE (59 F to 90 F) Fig. 2: Initial small-scale model capturing important characteristics of Princeton’s data center. Additional Work: Increasing Data Center Efficiency • Methodology 1. Decrease AHU flow rate to reduce bypass airflow 2. Increase supply air temperature to reduce energy consumption 3. Manage airflow where needed • Important metrics are return temperature index (RTI) and rack cooling index (RCI) • Results • 30% reduction in volume flow rate (CFM) • 43% reduction in mechanical fan energy • Strategic baffle placement to reduce undesirable airflow • All temperatures stay within acceptable range set by ASHRAE General Methodology: 1.Create a geometrical model of the data center 2.Initialize boundary conditions using physical measurements 3.Validate the model using physical temperature measurements 4.Adjust model parameters 5.Iterate 3-4 until acceptable model accuracy is reached Fig. 6: Temperature map of Princeton data center before improvements to efficiency. Blue indicates below desirable temperature; green is at desirable temperature. Fig. 3/4: Schematics used to build make first attempt at geometrical model. Fig. 1: Final model of Princeton’s data center, to within 95% accuracy. Princeton’s data center characteristics • 136 ft x 110 ft x 10 ft (~15,000 ft2 floor area) • 12 AHUs (75 rear-door heat exchangers) • Total flow rate of 166,000 cfm • 192 racks (29 rack rows) • Generate a heat load of 757 kW 2. Initializing Boundary Conditions • Use measured air handling unit (AHU) flow rates • Heat loads provided by Princeton • Each rack has individual load • Must also specify individual flow rate through each rack • Set an initial “guess” for temperature rise through racks (delta of 20 F for starting point Fig. 7: Temperature map of Princeton data center after improvements to efficiency. Red is above desirable temperature; green is at desirable temperature.