Raised Floor Data Center Research Articles

Airflow and Cooling in a Data Center

This paper deals with the distribution of airflow and the resulting cooling in a data center. First, the cooling challenge is described and the concept of a raised-floor data center is introduced. In this arrangement, cooling air is supplied through perforated tiles. The flow rates of the cooling air must meet the cooling requirements of the computer servers placed next to the tiles. These airflow rates are governed primarily by the pressure distribution under the raised floor. Thus, the key to modifying the flow rates is to influence the flow field in the under-floor plenum. Computational fluid dynamics (CFD) is used to provide insight into various factors affecting the airflow distribution and the corresponding cooling. A number of ways of controlling the airflow distribution are explored. Then attention is turned to the above-floor space, where the focus is on preventing the hot air from entering the inlets of computer serves. Different strategies for doing this are considered. The paper includes a number of comparisons of measurements with the results of CFD simulations.

Prediction of Cold Aisle End Airflow Boundary Conditions Using Regression Modeling

This paper is a continuation of the development of software tools that estimate, in real time or in near-real time, the cooling performance of a cluster of racks bounding a common cold aisle in a raised-floor data center environment. A fundamental assumption within the algorithm of these tools is that the computation of airflow patterns inside the cold aisle can be decoupled from the room environment. The effect of the room environment impacts the solution in the estimation of the cooling performance primarily through the airflow boundary conditions prescribed at the ends of the cold aisle. Consequently, the accuracy of the cooling-performance tool is directly linked to the accuracy of the end airflow prediction for any room environment. The end airflow is a complex function of many factors including the location and airflow rate of each rack, the perforated-tile airflow rate, and room environment conditions. As shown here, the dominant room-environment parameter is the difference between ambient and supply air temperatures. This paper describes the model developed to estimate the end airflow rate. End airflow values are calculated from several hundred computational fluid dynamics (CFD) scenarios covering a broad range of rack airflow (and power) distributions, tile flow rates, and room environments. An end airflow model is developed based on a regression analysis from the CFD data, which facilitates the real-time prediction of the end airflow for any practical cluster layout and room environment. The difference between accepted and predicted end airflow values is typically less than 25% of the accepted value or per-tile airflow rate.

Optimization of Data Center Room Layout to Minimize Rack Inlet Air Temperature

In a typical raised floor data center with alternating hot and cold aisles, air enters the front of each rack over the entire height of the rack. Since the heat loads of data processing equipment continue to increase at a rapid rate, it is a challenge to maintain the temperature of all the racks within the stated requirement. A facility manager has discretion in deciding the data center room layout, but a wrong decision will eventually lead to equipment failure. There are many complex decisions to be made early in the design as the data center evolves. Challenges occur such as optimizing the raised floor plenum, floor tile placement, minimizing the data center local hot spots, etc. These adjustments in configuration affect rack inlet air temperatures, which is one of the important keys to effective thermal management. In this paper, a raised floor data center with 12kW racks is considered. There are four rows of racks with alternating hot and cold aisle arrangement. Each row has six racks installed. Two air-conditioning units supply chilled air to the data center through the pressurized plenum. Effect of plenum depth, floor tile placement, and ceiling height on the rack inlet air temperature is discussed. Plots will be presented over the defined range. A multivariable approach to optimize data center room layout to minimize the rack inlet air temperature is proposed. Significant improvement over the initial model is shown by using a multivariable design optimization approach.

Airflow distribution through perforated tiles in raised-floor data centers

Raised-floor data centers are the most commonly used facilities for housing computer and telecommunication equipment. To adequately cool this equipment, the cooling air through perforated tiles must be distributed properly. The airflow distribution depends on the pressure distribution or the flow field in the space under the raised floor (plenum); it is a complex function of a large number of variables, including the size of the plenum, the open area of the perforated tiles, the locations and flow rates of the computer room air conditioner (CRAC) units, and the size and location of the under-floor obstructions like cables and pipes. In this article, the effect of these parameters on the airflow distribution is studied using an idealized one-dimensional computational model. Within the one-dimensional framework, the airflow distribution is governed by two dimensionless parameters: one related to the pressure variation in the plenum and the other to the frictional resistance. Results, in terms of distributions of pressure in the plenum and flow rates through the perforated tiles, are presented over a range of values of these two parameters. These results provide an understanding of the fundamental fluid mechanical processes controlling the airflow distribution through the perforated tiles. The one-dimensional model is used to calculate flow rates for two possible arrangements of the CRAC units, and these results are compared with those given by a three-dimensional model.

Use of Computational Fluid Dynamics for Calculating Flow Rates Through Perforated Tiles in Raised-Floor Data Centers

This paper describes a computational fluid dynamics model for calculating airflow rates through perforated tiles in raised-floor data centers. The model is based on the assumption that the pressure in the space above the raised floor is uniform, which allows the calculation to be limited to the space below the raised floor. It uses a finite-volume method, the k-∊ turbulence model, and a multigrid method. The model is applied to a real-life data center. The calculated results for velocity and pressure distributions are discussed. The flow rates through the perforated tiles are shown to be in good agreement with the measured values.

A methodology for the design of perforated tiles in raised floor data centers using computational flow analysis

An important aspect of the design of data centers involves sizing of the perforated floor tiles for return of cold air, the size of the space under the raised floor, and placement of the DP equipment and modular chillers. The flow through individual perforated tiles needs to fulfil the cooling requirements of the computer equipment placed adjacent to them. The novelty of this paper lies in the treatment of the volume under the raised floor as a uniformly pressurized plenum. The accuracy of the Pressurized Plenum model is demonstrated with reference to a computational fluid dynamics (CFD) analysis of the recirculating flow under the raised floor and the limits of its validity are also identified. The simple model of the volume under the raised floor enables use of the technique of flow network modeling (FNM) for the prediction of the distribution of flow rates exiting from the various tiles. An inverse design method is proposed for one-step design of the perforated tiles and flow balancing plates for individual chillers. Subsequent use of the FNM technique enables assessment of the performance of the actual system. Further, required design changes to an existing system can also be evaluated using the FNM analysis in a simple, quick, and accurate manner. The resulting design approach is very simple and efficient, and is well suited for the design of modern data centers.