project motivation: opportunity to explore building efficiency technology and the engineering
DESCRIPTION
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 - PowerPoint PPT PresentationTRANSCRIPT
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.
Project goal: create a working model of Princeton’s data center to within 10%
accuracy
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
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
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
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)
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
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. 2: Initial small-scale model capturing important characteristics of Princeton’s data center.
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.
Fig. 5: First model of Princeton’s data center, before any validation.
Fig. 6: Temperature map of Princeton data center before improvements to efficiency. Blue indicates below desirable temperature; green is at desirable temperature.
Fig. 7: Temperature map of Princeton data center after improvements to efficiency. Red is above desirable temperature; green is at desirable temperature.