The Effect of Under-Floor Obstructions on Data Center Perforated Tile Airflow

2011 ◽  
Author(s):  
James W. VanGilder ◽  
Zachary R. Sheffer ◽  
Xuanhang Simon Zhang ◽  
Collyn T. O’Kane
Keyword(s):  
Best Practices ◽  
Data Center ◽  
Flow Model ◽  
Design Parameters ◽  
Tile Type ◽  
Airflow Distribution ◽  
Specific Advice ◽  
Typical Data ◽  
Cfd Analyses ◽  
Potential Flow Model

Typical data center architectures utilize a raised floor; cooling airflow is pumped into an under-floor plenum and exits through perforated floor tiles located in front of IT equipment racks. The under-floor space is also a convenient place to locate critical building infrastructure, such as chilled-water piping and power and network cabling. Unfortunately, the presence of such objects can disrupt the distribution of cooling airflow. While the effects of other design parameters, such as room layout, plenum depth, perforated tile type, and leakage paths, have been systematically studied — and corresponding best-practices outlined, there is no specific advice in the literature with regard to the effect of under-floor infrastructure on airflow distribution. This paper studies the effects of such obstructions primarily through CFD analyses of several layouts based on actual facilities. Additionally, corresponding scenarios are analyzed using a Potential Flow Model (PFM), which includes a recently-proposed obstruction-modeling technique. It is found that under-floor obstructions significantly affect airflow distribution only when they are located very near perforated tiles and cooling units and occupy a substantial fraction of the total plenum depth.

Data Center Airflow Prediction With an Enhanced Potential Flow Model

2013 ◽  
Author(s):  
James W. VanGilder ◽  
Xuanhang (Simon) Zhang ◽  
Christopher M. Healey
Keyword(s):  
Data Center ◽  
Potential Flow ◽  
Data Centers ◽  
Flow Model ◽  
Computational Effort ◽  
Temperature Estimation ◽  
Flow Models ◽  
Physics Potential ◽  
Empirical Tests ◽  
Potential Flow Model

Potential flow models (PFM) have been implemented for a variety of applications, including data center airflow and temperature estimation. As an approximate solution to the data center room physics, potential flow models have great value in their simplicity and the limited computational effort required providing estimates. However, potential flow models lack the ability to capture the effects of buoyancy, which can affect airflow patterns within data centers. We show how this effect can be simulated within PFM; resulting in a model we call Enhanced PFM (EPFM). This model is only marginally more complex to implement than PFM and retains much of the properties of the original PFM, specifically its simplicity and stability. Solution time, about double that of PFM, is still only a small fraction of that of CFD, while empirical tests show a marked improvement in the prediction of key data center temperatures.

scholarly journals Pre-eminent Strategy for Effective Utilization of Power in Data Center

2020 ◽  
Vol 8 (5) ◽  
pp. 1442-1447
Keyword(s):  
Energy Consumption ◽  
Best Practices ◽  
Data Center ◽  
Cooling System ◽  
Environmental Concern ◽  
Electricity Consumption ◽  
Innovative Technology ◽  
Effective Utilization ◽  
Slowing Down ◽  
Typical Data

Cloud computing is generating billions of dollars in revenue annually with very minor indication of slowing down. Today, most innovative technology is cloud-centric by retrofitting the technology to on-premises. Every IT business is also rushing from cloud-first to cloud-only concept. Data center are accounting for billions of kilowatt hours of electricity consumption every year. Huge costs spend for energy consumption than establishing the data center Infrastructure. In this paper we discuss some of the best practices to decrease energy consumption in data center .We can better control the things when we can measure it. So we also focus on seizing and measuring the energy needed for a typical data center. There is also environmental concern to be taken care with respect to data center because of CO2 Emission in cooling system.

Perforated Tile Airflow Prediction: A Comparison of RANS CFD, Fast Fluid Dynamics, and Potential Flow Modeling

2015 ◽  
Author(s):  
Christopher M. Healey ◽  
James W. VanGilder ◽  
Zachary M. Pardey
Keyword(s):  
Fluid Dynamics ◽  
Video Game ◽  
Data Center ◽  
Potential Flow ◽  
Data Centers ◽  
Flow Model ◽  
Navier Stokes ◽  
Flow Modeling ◽  
Standard Potential ◽  
Potential Flow Model

Fast Fluid Dynamics (FFD), which has its origins in video game and movie animation applications, promises faster solve times than traditional RANS (Reynolds-Averaged Navier Stokes) CFD, is relatively easy to code, and is particularly suited to parallelization. Further, FFD is capable of modeling all relevant airflow physics including momentum, buoyancy and frictional effects which are not included in a standard Potential Flow Model (PFM). The present study is a first attempt to formally evaluate FFD for data center applications in which perforated tile airflow is predicted utilizing two-dimensional plenum models. Comparisons are made to RANS CFD and Potential Flow Modeling (PFM) over a variety of data center configurations based on five basic data center layouts, most of which are based on actual data centers. Results are compared to experimental measurements for one scenario.

Performance of a Propeller in a Wake and the Interaction of Propeller and Hull

1965 ◽  
Vol 9 (02) ◽  
pp. 1-36
Author(s):  
Quentin Wald
Keyword(s):  
Potential Flow ◽  
Flow Model ◽  
Practical Case ◽  
Viscous Effects ◽  
Actuator Disk ◽  
Potential Flow Model

Relations are developed which describe the propeller-hull interaction and the efficiency of the wake-operating propeller in the practical case where both potential and viscous effects are important. Momentum equations and the actuator disk representation of the propeller are used. Thrust deduction and efficiency are found to be functions of both the local and the ultimate wake velocity which are, in turn, expressible as functions of the static and total pressures in the propeller plane. The two velocity ratios have opposite effects on the thrust deduction, hence a potential-flow model simulating the velocity at the propeller plane and ignoring the ultimate wake-velocity deficiency arising from viscosity is inadequate.

A Two-Dimensional Potential Flow Model of the Wave Field Generated by a Semisubmerged Body in Heaving Motion

1988 ◽  
Vol 32 (02) ◽  
pp. 83-91
Author(s):  
X. M. Wang ◽  
M. L. Spaulding
Keyword(s):  
Free Surface ◽  
Boundary Conditions ◽  
Potential Flow ◽  
Flow Model ◽  
Second Order ◽  
Two Dimensional ◽  
Third Order ◽  
The Third ◽  
Potential Flow Model ◽  
Good Agreement

A two-dimensional potential flow model is formulated to predict the wave field and forces generated by a sere!submerged body in forced heaving motion. The potential flow problem is solved on a boundary fitted coordinate system that deforms in response to the motion of the free surface and the heaving body. The full nonlinear kinematic and dynamic boundary conditions are used at the free surface. The governing equations and associated boundary conditions are solved by a second-order finite-difference technique based on the modified Euler method for the time domain and a successive overrelaxation (SOR) procedure for the spatial domain. A series of sensitivity studies of grid size and resolution, time step, free surface and body grid redistribution schemes, convergence criteria, and free surface body boundary condition specification was performed to investigate the computational characteristics of the model. The model was applied to predict the forces generated by the forced oscillation of a U-shaped cylinder. Numerical model predictions are generally in good agreement with the available second-order theories for the first-order pressure and force coefficients, but clearly show that the third-order terms are larger than the second-order terms when nonlinearity becomes important in the dimensionless frequency range 1≤ Fr≤ 2. The model results are in good agreement with the available experimental data and confirm the importance of the third order terms.

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