Efficient Implementation of Potential-Flow Airflow Prediction for Data Centers

2013 ◽  
Author(s):  
Christopher M. Healey ◽  
James W. VanGilder ◽  
Xuanhang (Simon) Zhang
Keyword(s):  
Potential Flow ◽  
Data Centers ◽  
Processing Task ◽  
Flow Models ◽  
Sample Data ◽  
Simplified Solution ◽  
Main Components ◽  
Prediction Techniques ◽  
Ci Calculations ◽  
Potential Flow Model

We present improvements to airflow prediction techniques for data centers, specifically within potential flow models. As a potential-flow model presents a simplified solution to the room airflow physics, additional approximations can be implemented to improve runtime without changing the accuracy of potential-flow. The improvements concentrate on two main components of current prediction methods: namely, the pre-processing task of automatic and efficient grid generation and post-processing task of capture index (CI) calculation. We propose a variable grid oriented around the objects in the room, creating cells with variable sizes (in width, height, and depth). We also show how CI calculations can be made more efficient through an understanding of the local nature of CI. An empirical study of sample data center layouts shows that these improvements can yield significant improvements in speed while maintaining a good level of accuracy.

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.

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.

Fluid mechanics of the cochlea. Part 1

1972 ◽  
Vol 51 (3) ◽  
pp. 497-512 ◽  
Author(s):  
M. B. Lesser ◽  
D. A. Berkley
Keyword(s):  
Fluid Mechanics ◽  
Potential Flow ◽  
Analytical Study ◽  
Nonlinear Effects ◽  
Two Dimensional ◽  
One Dimensional ◽  
Flow Models ◽  
Place Theory ◽  
Mechanical Models ◽  
Potential Flow Model

The physiology of the cochlea (part of the inner ear) is briefly examined in conjunction with a description of the ‘place’ theory of hearing. The role played fluid motions is seen to be of importance, and some attempts to bring fluid mechanics into a theory of hearing are reviewed. Following some general fluid-mechanical considerations a potential flow model of the cochlea is examined in some detail. A basic difference between this and previous investigations is that here we treat anenclosedtwo-dimensional cavity as opposed to one-dimensional and open two-dimensional models studied earlier. Also the two time-scale aspect of the problem, as a possible explanation for nonlinear effects in hearing, has not previously been considered. Thus observations on mechanical models indicate that potential flow models are applicable for times of the same scale as the frequency of the driving acoustic inputs. For larger time scales mechanical models show streaming motions which dominate the qualitative flow picture. The analytical study of these effects is left for a future paper.

Exergy Analysis of Data Center Thermal Management Systems

2003 ◽  
Author(s):  
Amip J. Shah ◽  
Van P. Carey ◽  
Cullen E. Bash ◽  
Chandrakant D. Patel
Keyword(s):  
Thermal Management ◽  
Data Center ◽  
Data Centers ◽  
Exergy Analysis ◽  
Thermal Control ◽  
Management Systems ◽  
World Systems ◽  
Sample Data ◽  
Potential Applications ◽  
Temperature Ranges

Data centers today contain more computing and networking equipment than ever before. As a result, a higher amount of cooling is required to maintain facilities within operable temperature ranges. Increasing amounts of resources are spent to achieve thermal control, and tremendous potential benefit lies in the optimization of the cooling process. This paper describes a study performed on data center thermal management systems using the thermodynamic concept of exergy. Specifically, an exergy analysis has been performed on sample data centers in an attempt to identify local and overall inefficiencies within thermal management systems. The development of a model using finite volume analysis has been described, and potential applications to real-world systems have been illustrated. Preliminary results suggest that such an exergy-based analysis can be a useful tool in the design and enhancement of thermal management systems.

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