CFD Modeling of an Existing Raised-Floor Data Center

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1 CFD Modeling of an Existing Raised-Floor Data Center Amir Radmehr 1, Brendan Noll 2, John Fitzpatrick 2, Kailash Karki 1 1. Innovative Research, Inc Harbor Lane N, Suite 300, Plymouth, MN 2. University of Rochester 601 Elmwood Avenue, Rochester, NY radmehr@inres.com, brendan.noll@rochester.edu, john.fitzpatrick@rochester.edu, karki@inres.com Abstract Computational Fluid Dynamics (CFD) modeling is being increasingly used for designing new and analyzing existing data centers. The application of CFD technique for designing new data centers is fairly straightforward since all of the design specifications are available. However, creating an accurate CFD model of an existing data center is often a challenge because some of the required input data is usually not available. The collection of missing details requires survey of the data center and even measurements. In this paper, we present several measurement and modeling techniques that can help the users of CFD technology to create an accurate model of an existing raised-floor data center. These techniques have been implemented in modeling a data center at the University of Rochester in Rochester, NY. To verify the accuracy of the model, calculated values of airflow rates through perforated tiles, rack inlet and exhaust temperatures, and supply and return temperatures for the AC units were compared with the measured values. The agreement is good. Keywords Data center, cooling, airflow modeling, CFD, simulation, measurement 1. Introduction Computational Fluid Dynamics (CFD) modeling has been used extensively in aerospace, automotive, and power industries since the early 1970 s. It was introduced to the data center community in early 2000 through the work of Kang et al. [1], Schmidt et al. [2], Karki et al. [3], among others. Since then, CFD modeling has become a standard practice in both designing new data centers and resolving cooling problems and inefficiencies in existing data centers. In the design stage, CFD modeling is used to validate and optimize different design parameters. For existing data centers, CFD modeling is used to identify the cooling issues and to explore various cooling improvements without risking the operation of the data center. Once the best practical and cost-effective remedies are identified, they can be implemented in the real data center. It s worth noting that although measurements and monitoring systems (without CFD modeling) may reveal the current cooling issues, they cannot be used to predict the effect of proposed changes. In general, the following data is needed to create the CFD model of a raised-floor data center: XXXX-X/13/$ IEEE 1. Dimensions and shape of the data center. 2. The location and size of structural obstructions such as columns, elevator shafts, ramps, etc. 3. The raised floor height. 4. The location of the cooling units. 5. The manufacturer and model number of the cooling units. This information can be used to obtain the flow rate and cooling behavior of the units. 6. The layout, size, and elevation (distance from the subfloor) of under-floor obstructions such as pipes, cable trays, etc. 7. If the data center has an active ceiling plenum, the height of the drop-ceiling and the size and location of the vents on the drop ceiling. 8. The layout, location, size, and elevation (distance from the raised-floor) of above-floor obstructions such as walls, partitions, cable trays, file cabinets, etc. 9. The location of perforated tiles. 10. The type or the percentage open area of perforated tiles. This information can be used to obtain the flow resistance of the perforated tiles. 11. The location and size of cable cutouts or other openings on the raised floor. 12. The location, dimensions, and orientation of racks. 13. The actual heat load or power consumption of racks. In some cases, detail information of the equipment inside the racks, open spaces, and blanking panels are needed to represent the rack accurately. 14. The location and type of PDUs, UPSs, RPPs, etc. 15. If there is any supplementary cooling mechanism in the data center such as house air, in-row coolers, overhead ducts, free cooling, rear-door heat exchangers, etc., then the information about the supplementary cooling is needed. When CFD modeling is used for designing new data centers, providing the input data is relatively straightforward. For example, in the design stage, the precise details about type and placement of the computer equipment within racks are usually not important, and it is sufficient to characterize the racks by their total heat load and airflow. This is, however, not the case when CFD modeling is used to analyze cooling in an existing data center. Now the required input data may not be available. For example, the layout could have deviated from the original design and the changes may not have been

2 documented. The cooling units may have been modified or their characteristics may have changed due to normal wear and tear. Racks might contain a wide range of servers and could have open spaces and blanking panels, and, as a result, they can no longer be represented using a single heat load. To get these and other details, the data center must be surveyed. For certain items, specific measurements may be required. One item that requires measurement is the flow rate of a Computer Room Air Conditioner (CRAC) unit. The actual flow rate of a CRAC unit could be very different from the rated flow rate reported by the manufacturer of the unit. Factors such as wear and tear, dirty filter, pre-filter, loose belts, etc. can make the actual flow rate of a CRAC unit noticeably less than the rated flow rate. Another such item is the actual power consumption (heat load) of the computer equipment (servers) in a rack. The server manufacturers usually report the nameplate power and occasionally the power consumption for maximum, typical, and minimum configurations. This data provides a range for the power consumption of a server, but the true power consumption can be obtained only by measurements. Collecting accurate data often presents a challenge. For example, in some data centers brush-type grommets are used to close the cable openings on the floor. In theory, these brushes are supposed to seal the openings completely. However, in reality the cables that pass through a brush make a relatively large opening in the brush. The size of this opening needs to be measured and represented in the CFD model. Another example is the openings under the PDUs RDCs, RPPs, etc. These openings need to be represented in the CFD model accurately. However, it is very difficult and in some cases impossible to access these openings and measure them. Radmehr et. al. [4] have presented some of the techniques for collecting data and creating an accurate CFD model of a data center. However, their work was limited to the underfloor space in a confined section of a data center. In this paper, the scope of that work is expanded to cover both the under-floor and above-floor spaces in a real-life data center. Specific measurements have been made to provide the necessary data to be used in the CFD model. Various methods are explained for collecting the data and implementing it in the CFD model. The results of the CFD analysis are then compared with the measurement done in the data center. The agreement is satisfactory. In the following sections, the layout of the data center is presented, the measured data is listed, the details of the CFD model are described, and the comparison of calculated values with measured values is presented. 2. Data Center Layout The data center has a raised floor. Eight chilled-water down-flow CRAC units provide the cooling air into the plenum under the floor. The plenum height is 92 cm (36 inches). The data center does not have a drop ceiling, therefore the air returns directly to the CRAC units through the room. The usable floor area for placing IT equipment is approximately 700 sq. m (7,500 sq. ft). Figure 1 shows the layout of the equipment. Figure 1: Data Center Layout Table 1 provides general information about the data center. Number of CRAC units 8 Number of perforated tiles 283 Number of cable openings 159 Number of racks 124 Number of Transformers 2 Number of PDUs 6 Number of RPPs 6 Total Heat Load 314 kw Heat Load Density 450 W/sq. m (42 W/sq. ft.) Table 1: Data Center Specifications The perforated tiles on the floor have 25% open area and a damper for controlling airflow. Some of the tiles are placed in areas for future expansion. The dampers for these tiles are completely closed. The dampers of the tiles in front of the active racks are fully open. There are 117 tiles with closed dampers and 166 tiles with fully open dampers. There are cable openings under most of the racks. These openings have been closed using brush-type grommets. There are three types of under-floor obstructions in this data center: chilled water pipes, power cable trays, and network cable trays. The power cable trays are wire-meshed while the network cable trays are solid. The racks are placed in hot aisle-cold aisle arrangement. There are various types of equipment inside these racks. Each rack has a unique combination of equipment, blanking panels, and open spaces. A small number of racks are from equipment manufacturers. Examples are IBM Z10 and IBM Blue Gene. The airflow direction for all of the racks is front to rear (the cooling air enters to the front of the rack and exhaust from the rear) except for an IBM Blue Gene, for which the cooling air enters from bottom and exits through the top. The PDUs and RPPs have short legs that make them sit a few inches above the floor and there are large openings under

3 them. The PDUs and RPPs have internal fans that take the cooling air from bottom and exhaust the hot air from top. Some of the air from the under-floor space flow through the PDUs and RPPs and the rest of it passes through the gap between the bottom of the PDUs/RPPs and the floor. 3. Creating the CFD Model The CFD model is created using the commercially available software package TileFlow [5]. In this section the specifications of creating the CFD model are described. Representing most of the items in the CFD model is straight forward. These items can be selected from the TileFlow database and placed in the model. However, representing some of the items requires special treatment. The important items and the way they are represented in the CFD model are described below CRAC Units CRAC units are Liebert FH529C. The rated flow rate of the CRAC units is 21,000 m 3 /h (12,400 CFM). The actual flow rate of these units may differ because of a number of reasons such as wear and tear, dirty filters, changes in settings, and excessive plenum pressure. The flow rate of each CRAC unit was measured using the Velocity Grid accessory from Shortridge Instruments, Inc. [6]. The details of the measurement technique are described in Radmehr et al. [4]. The flow rate of two CRAC units was measured at 18,700 m 3 /h (11,100 CFM) and the other six at 17,850 m 3 /h (10,500 CFM). In the CFD model the measured flow rates are used. Also, the return and supply temperature of the CRAC units were measured. The measured supply temperature was assigned to individual CRAC units in the CFD model. The measured return temperatures were used to assess the accuracy of the CFD calculation Perforated Tiles There is one type of perforated tile used in this data center. It is manufactured by Tate Access Floors, Inc. [7]. The nominal open area of the tile is 25%. The tile has a damper. In this data center, the damper position is either completely open or completely closed. The flow resistance of the tile can be expressed by a quadratic equation as follows: P = RQ 2 Eq. 1 In this equation, P is the pressure drop across the tile and Q is the airflow rate. R is the resistance of the perforated tile and its value is determined by using the pressure drop-flow rate data provided by the manufacturer of the tile for open and closed damper positions. The database of TileFlow already has the information about these tiles and their flow resistances. A value of R for the tiles with an open damper is 3.2 E-5 when pressure is represented in Pa and flow rate is represented in m 3 /h. When the damper is fully closed the value of R increases more than 100 times Cable Openings There are cable openings under most of the racks. The cable openings are closed using brush-type grommets. However, because of the penetration of cables through the brush, in most cases a considerable opening is left in the brush. All cable openings were visited and their approximate open areas were recorded. TileFlow has a library of openings of various sizes. The cable openings are selected from the TileFlow database and placed on the floor under the racks. The relationship between the pressure drop and flow rate across a cable opening can also be represented by Eq. 1, where R now depends on the open area Airflow Leakage from Underneath the PDUs and RPPs There were large openings under the PDUs and RPPs. These openings were inaccessible and their open areas could not be measured. Instead of guessing the open area of the openings, it was decided to estimate the airflow through them and represent them as openings with known flow rates. Some of the air from these openings flows through the PDUs and RPPs and the rest escapes through the gaps between the bottom of the PDUs/RPPs and the floor. The flow direction for these units is bottom to top. The PDUs have two fans at the top that exhaust the air. The RPPs have internal fans and the entire top surface is open for venting. The fan flow rates were not known. They were calculated using the measured air velocity through the vents. For this measurement, the airfoil tool from Shortridge was used. Moreover, the size of the gaps and the average air velocity through the gaps under the PDUs and RPPs were measured. Then, the amount of the airflow that passes through these gaps was calculated. The sum of the flow rate at the top and flow rate leaking from the gaps underneath gives the total flow rate from the openings under the PDUs and RPPs PDUs and RPPs PDUs and RPPs are represented by rectangular boxes that generate heat. It is difficult to find the actual heat generated by these devices and there is little data available from manufacturers. Measurement of the inlet and exhaust temperature of the PDUs and RPPs indicated that the heat loads were around 500 W Under-Floor Obstructions There are three types of under-floor obstructions in this data center: chilled water pipes, power cable trays, and network cable trays. The size and position of the pipes and cable trays and their distances from the subfloor were measured and recorded. The pipes are represented as cylindrical obstructions. The power cable trays are wiremeshed while the network cable trays are solid. In some sections the wire-meshed cable trays were either empty or partially filled. The empty cable trays were not represented in the CFD model since they do not provide a significant blockage. The partially filled trays were represented as rectangular blockages with height equal to the height occupied by the cables. Since the under-floor plenum height in this data center is large, the under-floor obstructions do not have a significant impact on the airflow distribution. Authors past experiences have shown that for data centers with under-floor plenum height of 45 cm (18 inches) and higher, the obstructions smaller than 7 cm (3 inches) have little effect on the airflow and pressure distribution under the floor.

4 3.7. Server Racks Most of the racks are partially filled with servers. Some of the gaps between the servers have been left open while others are closed using blanking panels. Therefore, the racks could not be represented by a single cumulative heat load. The height of the blanking panels, open sections, and equipment inside racks were measured. The nameplate heat loads of the equipment were available from the asset management software used by the data center manager. However, the nameplate heat load is much higher than the actual heat load produced by the equipment. The data center manager provided us with a good estimate of the total power consumption of all of the IT equipment in the data center. It was estimated to be between 300 to 320 kw. Using the nameplate heat loads, the total power consumption of all of the IT equipment was calculated to be 600 kw. Therefore, a de-rating factor of 0.5 was applied to the nameplate heat load to represent the equipment heat load in the CFD model Blue Gene Cabinet There is one Blue Gene cabinet in the data center. The cabinet takes airflow from the bottom and exhausts it from top. There were large openings underneath the cabinet to provide the cooling air. The size of the vent at the top of the cabinet and the exhaust air velocity at several locations were measured. Using this data, the average exhaust air velocity and the airflow rate through the Blue Gene cabinet were calculated. In the CFD model, this measured airflow is assigned to the vents underneath the Blue Gene cabinet and to the cabinet itself. Also, the air temperature at the exhaust and inlet of the Blue Gene cabinet were measured. The heat load of the Blue Gene cabinet was calculated to be 40 kw. 4. Measurements to Validate the Model In order to verify the accuracy of the computer model, the flow rate from perforated tiles, return temperatures of the CRAC units, inlet temperature of racks, and exhaust temperatures of a limited number of racks were measured. In this section the measurement procedure for each parameter is described Flow Rates of Perforated Tiles The flow rates through perforated tiles were measured using a flow hood (Model CFM-870) manufactured by Shortridge Instrument, Inc. The flow hood has a 61 x 61 cm (2 x 2 ft.) opening that fits perfectly over the tiles. The placement of the hood over a perforated tile, however, creates an extra resistance and reduces the flow rate discharged by the tile during the measurement. The Shortridge flow hood has a mechanism to correct for this effect. It is done by adding a known resistance (a pair of flaps) to the measurement area in the hood. The user makes two measurements for each tile. In the first measurement, the flaps are open and provide no extra resistance. In the second measurement, the flaps are closed. Since the resistance of the flaps is known, one can use the two sets of the measurements to calculate the effect of the flow hood on the flow measured from a particular tile and compensate for it. This measurement meter attached to the flow hood makes this correction automatically and reports the actual flow rate that would exist in absence of the hood. Usually, there are some fluctuations in measured airflow. Whenever, such fluctuations are observed, several measurements were taken and the averaged value is recorded. The measurement indicated little variation between the flow rates of the tiles. This is because of the relatively large plenum height and restrictive perforated tiles in this data center. This distribution of airflow rates is consistent with the results of the parametric study on the effect of plenum height on the airflow rates reported in Schmidt et. al. [2] Rack Inlet and Exhaust Temperatures The inlet temperatures of 38 racks selected randomly were measured by a temperature probe. These temperatures were measured at the center of the rack (in the width direction), 165 cm (65 inches) from the floor, and 1.5 cm from the face of the rack. Also, the exhaust temperatures were measured for eight racks. These temperatures were measured at the center of the racks and 1.5 cm from the rear face of the rack. Unlike the inlet temperatures, the exhaust temperatures were measured at various heights. This was done to capture the exhaust temperature of the equipment of interest inside the rack Return Temperature of CRAC Units The average return temperature of the CRAC units was measured by both a thermometer supplied by Shortridge and a Flir I7 Infrared Camera. The differences between temperatures measured by the two devices were less than 0.5 C. 5. Numerical Solution Procedure The governing equations are solved using the computational fluid dynamics software package TileFlow [5]. TileFlow uses the finite-volume method described by Patankar [8]. 6. Results from CFD Model and Comparison with Measurement To verify the correctness of the data and the computational model, the results obtained from the calculations were compared with measurements described above. The measured flow rates through perforated tiles were compared with the calculated values. The average difference between the measured and calculated flow rates is 8%. Figures 2, 3, and 4 show the comparison of calculated and measured flow rates for three different rows. The horizontal axis represents the tiles labels in the data center. The agreement is excellent. Tiles with large flow rates are the ones with dampers fully open and tiles with low flow rates are the ones with dampers fully closed. Dampers are doing a relatively good job in blocking the airflow. The typical airflow discharged from the tiles with closed dampers is around 50 m 3 /h (30 CFM). Figure 5 shows the comparison of calculated and measured return temperature for the CRAC units. The agreement between measured and calculated values is satisfactory and indicates that the CFD calculations for airflow mixing in the room, temperature calculation, and energy balance are acceptable.

5 Figure 2: Comparison of Measured and Calculated flow rates for row 7. Figure 3: Comparison of measured and calculated flow rates for row 20. Figure 4: Comparison of measured and calculated flow rates for row 33.

6 nameplate power consumption values. This approach produced acceptable rack inlet/exhaust temperatures. It can, therefore, be used as a first-level approximation for server heat loads in absence of detailed information. Figure 5: Comparison of measured and calculated average return temperature to the CRAC units. The cooling produced by each CRAC unit can be calculated using the CRAC unit flow rate and temperature drop. These values are calculated for measured and computed temperature drops and the results are shown in Figure 6. Again the agreement is acceptable. Figure 7: Comparison of measured and calculated inlet temperatures of racks. Figure 6: Comparison of measured and calculated cooling produced by CRAC units. The sum of the measured cooling produced by eight CRAC units is 300 kw, which is in agreement with the total power consumed by the IT equipment in the data center reported by the data center manager (300 to 320 kw). This is an independent verification of the power consumed by the IT equipment. Figures 7 and 8 show the comparison of calculated and measured rack inlet temperatures for a number of racks. The horizontal axis represents the rack labels in the data center. The results for other racks are comparable to the ones shown here. In general, the agreement between measured and calculated values is acceptable for practical purposes. Figure 9 shows the comparison of calculated and measured rack exhaust temperatures for the eight racks considered in the measurement. The temperature distribution in the data center depends on the server heat loads. In this study, the individual server heat loads (power consumption) were not known. They were deduced by applying a global de-rating factor to the Figure 8: Comparison of measured and calculated inlet temperatures of racks. Figure 9: Comparison of measured and calculated racks exhaust temperatures. 7. Conclusions The common difficulties in collecting data for creating an accurate CFD model of an existing raised-floor data center are explained. The major challenges are in finding the actual flow

7 rates of the CRAC units, approximating the open area of cable openings and grommets, approximating the leakage airflow from underneath the racks and devices such as PDUs and RPPs, and the actual heat load of the racks. Several measurement techniques are presented to collect the data and approximate the values of the input parameters needed in the CFD model. These techniques are used to create a CFD model of a data center belonging to the University of Rochester. The flow rate from perforated tiles, return temperature to the CRAC units, inlet and exhaust temperatures of the racks are measured and compared with the results obtained from the CFD analysis. This comparison indicates that the representation of airflow and temperature distribution in the data center by the CFD model is acceptable for all practical purposes. The methodology described in this paper can be used to create accurate CFD models for other existing data centers. Acknowledgments The authors express their gratitude to Rob Panik and John Pacitto of the University of Rochester for their contributions towards the data collection and their assistance with making measurements. References [1] Kang, S., Schmidt, R., Kelkar, K., Radmehr, A., and Patankar, S., 2000, A Methodology for the Design of Perforated Tiles in Raised Floor Data Centers Using Computational Flow Analysis, ITHERM 2000, Las Vegas, Nevada, Proceedings, Vol. 1, pp [2] Schmidt, R. R., Karki, K. C., Kelkar, K. M., Radmehr, A., and Patankar, S. V., 2001, "Measurement and Predictions of the Flow Distribution Through Perforated Tiles in Raised-Floor Data Centers," Paper No. IPACK , Proceedings of InterPack'01, The Pacific Rim/ASME International Electronic Packaging Technical Conference and Exhibition, July 8-13, 2001, Kauai, Hawaii, USA. [3] Karki, K. C., Radmehr, A., and Patankar, S. V., 2003, "Use of Computational Fluid Dynamics for Calculating Flow Rates Through Perforated Tiles in Raised-Floor Data Centers," Int. J. of HVAC&R Research, Vol. 9, pp [4] Radmehr, A., R.R. Schmidt, K.C. Karki, and S.V. Patankar Distributed leakage flow in raised-floor data centers, IPACK ASME InterPack 05, July 17-22, San Francisco, CA. [5] Innovative Research, Inc TileFlow Version 5.0, [6] Shortridge, [7] Tate Access Floors, [8] Patankar, S. V., 1980, Numerical Heat Transfer and Fluid Flow, Hemisphere.

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