Rate of Heating Analysis of Data Centers during Power Shutdown


 Randolf Randall
 3 years ago
 Views:
Transcription
1 2011. American Society of Heating, Refrigerating and AirConditioning Engineers, Inc. ( Published in ASHRAE Transactions, Volume 117, Part 1. For personal use only. Additional reproduction, distribution, or transmission in either print or digital form is not permitted without ASHRAE'S prior written permission. LV11C026 Rate of Heating Analysis of Data Centers during Power Shutdown Kishor Khankari, PhD Member ASHRAE Abstract During power outages servers in the data centers are generally powered by uninterruptible power supplies (UPS). At the same time the sources for active cooling such as CRACs, CRAHs, and chillers stop operating for a period until powered by alternate power sources. During this period servers continue to generate heat without any active cooling. This results in increase in the room air temperature within a short period that can be detrimental to the servers. This paper, with the help of a mathematical model, indicates that the rate of heating of a data center can start initially at a certain maximum level, and can then gradually reduce to a certain minimum level, which is the lowest possible rate of heating that a data center can attain. The rate of such exponential decay is a function of the time constant, which is the characteristic of a data center design and layout. The time constant depends on the heat capacity ratio and the specific surface area of racks in a data center. This paper analyzes various factors that affect these parameters and demonstrates how the time constant can be employed as a matrix to compare the thermal performance of data centers during the power outage period. INTRODUCTION Provision of continuous cooling to mission critical facilities is essential to maintain supply air temperatures to servers within the recommended range of 64.4 F (18 C) to 80.6 F (27 C) (as recommended by ASHRAE, 2008). During power outages servers continue to operate with the power provided by the uninterruptible power supply (UPS) units while the supply of cooling air is completely halted until alternate means of powering the cooling system are activated. During this time servers continue to generate heat and the server fans continue to circulate room air several times though the servers. This can result in sharp increase in the room air temperature to undesirable levels, which in turn can lead to automatic shutdown of servers, and in some cases can even cause thermal damage to servers. Provisions for making continuous cooling available during this period by alternate means are generally expensive and tedious. Data centers contain a large number of rack enclosures constructed out of rolled carbon steel. Before considering the other expensive options for continuous cooling it would be valuable to analyze whether rack thermal mass can help in reducing or eliminating the need for provisional cooling. Previous analysis by Khankari (2010) showed that thermal mass of rack enclosures can play a crucial role in attenuating the temperature rise of room air during the power shutdown period. However, availability of this thermal mass depends on the extent of the exposed surface area of the racks, which in turn, depends on the number of racks and number of rack rows in a data center. It was further demonstrated that data centers with low heat load densities are less likely to experience automatic server shut off due to increased air temperatures and can provide more time for starting alternate power systems. In addition to the temperature, the rate of heating of room air during the power outage period is also an important factor. Not only the temperature levels in the room be maintained within the recommended range but the rate of heating should also be kept at a minimum level. During a power outage the temperature of the room air as well as the rate of temperature rise vary with time. If the rate of heat generation from servers remains constant, the temperature levels in the room would Kishor Khankari is a Associate Partner at Syska Hennessy Group in Ann Arbor, Michigan. 212 ASHRAE Transactions
2 continue to rise and not reach a steady state during the power shutdown period. However, the rate of temperature rise can reach a steady state and attain a constant rate, which can also be the lowest rate of heating that a data center can attain. This lowest rate of heating and the rate at which it can be reduced from the maximum rate are the characteristics of the design and layout of a data center. This paper with the help of a heat transfer model evaluates this phenomenon and analyzes various parameters that can affect the thermal performance of a data center during the power shutdown period. DESCRIPTION OF HEAT TRANSFER MODEL The heat transfer analysis presented in this study is based on the heat transfer model developed during the previous study ( Khankari.2010). Unlike the previous heat transfer model, which was mainly related to study the variation of room air temperature with time, the present model is developed to study the variation of rate of air temperature rise or the rate of heat transfer between the air and rack mass with time. The previous model was based on the hypothesis that the total heat generated by servers during the off cooling period is primarily dissipated to the surrounding air through active recirculation induced by the server fans. Air then dissipates part of this heat to the surroundings through several pathways that includes rack enclosure mass, mass of the cold air trapped under the raised floor, and to the outside world through the building envelop. However, the previous analysis showed that about 98 percent of the total heat generated by the servers is absorbed by the room air and rack enclosures and less than 2 percent is dissipated to the other components. Therefore, in this analysis the heat transfer model is modified to assume that the total generated heat is dissipated among the room air and the rack enclosures only. This is described by the equation (1) (Table 1). The rate of heat transfer mechanism between the air and the rack enclosures, as shown in the equation (2b), depends on the heat transfer coefficients (U), exposed rack surface area (A rack ), and the temperature differences ( T) between the rack mass and the room air. It should be noted that the exposed rack surface area depends not only on the number of racks but also on the number of rack rows. The assumptions related to the previous analysis are still valid and are mentioned here for reference. The heat transfer model considered in this analysis is a zero dimensional model and assumes that all spatial variations within the data center are negligible. The air in the data center room is assumed to be well mixed, and hence, assumes a single mixed temperature. Since the air is rapidly moved by the server fans this assumption is quite reasonable. Also all the rack enclosure mass assumes a single temperature. The resistance to heat transfer within the rack mass is assumed to be small due to large thermal conductivity compared to the heat transfer coefficient on the surfaces. The rate of heat generation from servers is assumed to be constant during the power shut down period. Mathematical analysis of the heat transfer model and the development of various equations are presented in Table 1. RATE OF HEATING ANALYSIS After the active cooling completely stops, the air and rack temperature start rising due to the heat generated from the servers. Figure 1a shows a hypothetical trend of room air and rack temperature rise. Effect of various factors that can affect these trends is discussed in detail in Khankari (2010). Figure 1b shows the corresponding trend of rate of heating or rate of temperature rise with time. These trends reveal two important facts a) after an initial rapid rise, both the air and rack temperatures tend to vary at constant rate; and b) this rate is equal for both the air and the rack mass. As shown in Figure 1b the rate of heating of air starts at a certain maximum level (R max ), and then, gradually reduces to a certain minimum level (R min ), which is the lowest possible rate of heating that a data center can attain. Thus, R min can be an important characteristic of a data center design. The heat transfer analysis presented in Table 1 indicates that with increasing time, the difference between R max and R min gradually approaches zero while the room air temperature continues to increase at a constant rate of R min. For the purpose of this analysis a nondimensional rate of heating (θ) is introduced. According to equation (6), initially when the rate of heating, R, is at R max, θ is equal to 1. Similarly, when R approaches the R min, and theoretically at time equal to infinity, θ will approach to zero. Thus, the nondimensional rate of heating varies exponentially from 1 to 0 as shown in Figure 1c. This 2011 ASHRAE 213
3 parameter is helpful in analyzing the extent of the rate of heating (R) from reaching the potential minimum rate of heating (R min ) at any given time during the power outage period. As shown in equation (6), the rate of such exponential decay depends on the time constant (τ) of the data center. Air Rack R max Air Rack Temperature Rate of Temperature Rise (dt/dt) R min Time Time Figure 1 (a) Variation of temperature with time. Figure 1 (b) Variation of rate of heating with time Nondimensional rate of heating (θ) % line Time Figure 1 (c) Variation of nondimensional rate of heating (θ) with time. The time constant (τ) of the data center depends on the heat transfer coefficient (U), the specific heat of rack mass (C prack ), the specific surface area of the rack (A s ), and on the heat capacity ratio (C r ). Thus, the time constant is a characteristic of the design and layout of the data center. A good design of a data center should not only try to reduce the minimum rate of heating (R min ) to the lowest possible level but should also reduce the time constant (τ), which determines the rate at which the initial maximum rate of heating reduces to the minimum rate. MAXIMUM AND MINIMUM RATE OF HEATING It is assumed that initially (at time t=0), right after the power outage, room air and rack mass are in thermal equilibrium and both assume a certain average initial temperature. According to this assumption at time t=0, there is no exchange of heat between the air and the rack mass. This assumption leads to equation (4a) for the initial rate of heating, R max. This initial 214 ASHRAE Transactions
4 maximum rate of heating increases with the heat load in the data center and decreases with the room heat capacity. The heat capacity of the room depends on the volume of a data center. Thus, the maximum rate of heating decreases with an increase in the floor area and/or height of a data center room. In other words, data centers with larger floor area and/or larger height will have lower R max. This mathematical analysis also leads to another important conclusion, as indicated by equation (4b), that at steady state when the rate of heat transfer between the air and rack mass becomes constant, the rate change of air and rack temperature become equal (Figure 1b). This analysis leads to the equation (4c) for R min, which is the lowest possible rate of heating the room air can attain. Equation 4c indicates that the minimum rate of heating also varies directly with the heat load, but unlike the maximum rate, it decreases with the total heat capacity of the system, which is the sum of the room and rack mass heat capacities. As thermal mass increases, R min decreases. In other words, data center with larger thermal mass, for example, due to more number of racks will have a lower R min than an identical data center with a fewer racks. Similar to R max, the minimum rate of heating also decreases with an increase in the heat capacity of a data center room. Table 1: Mathematical Model (1) Therefore, from equation (1) and (2) From the equations (1) and (2) (2a) (2b) (3a) (3b) Initial and final conditions for the equation (3a) are, 0 (4), At time t = 0, T = 0, and therefore, from equation (1) and (2a) (4a) At steady state (time t = ), the equation (3b) reduces to (4b) From equation (4a) and (4c) 1 (4c) (4d) (5) With the initial and final conditions described above, the solution of the equation (3) is where, / (6) Time constant 1 and the specific surface area of rack 2 2 /N / (7) (8a) (8b) TIME CONSTANT As mentioned before the time constant (τ) of a data center is an important design parameter that determines its ability to reduce the initial maximum rate of heating, R max, to the final minimum rate of R min. Data centers with a large time constant will take relatively long time to reach the minimum level of heating compared to those with lower time constant. According to equation (6) and as shown in the Figure 1c, when the physical time, after the power outage, reaches the value of the time constant (t = τ), the difference (R R min ) reduces to 36.8 percent of its initial difference, (R max R min ). Thus, the time constant can be employed as a matrix to compare the thermal performance of the data centers. It should be noted that time constant is independent of the heat load in a data center. It mainly depends on the parameters related to the design and layout 2011 ASHRAE 215
5 of a data center. For constant values of heat transfer coefficient (U) and the specific heat of the rack material, according to equation (7), the time constant varies with the specific surface area of the racks (A s ) and the heat capacity ratio (C r ). While the specific surface area of racks determines the thermal conductance, the heat capacity ratio (C r ) determines the thermal capacitance of a data center. Larger values of thermal conductance and capacitance together determine the ability of a data center to keep the rate of heating to a minimum level by keeping the value of time constant low. Note the C r increases with the number of racks and decreases with the height of a data center. Figure 2a shows variation of time constant with the C r for various levels of specific surface area (A s ). According to this analysis, the time constant decreases with increase in the heat capacity ratio and specific surface area of racks. The effect of specific surface area of racks has a larger impact on the time constant at lower values of C r. This means that with fewer racks, the time constant can be reduced by increasing the available surface area of racks. This can be achieved, for example, by increasing the number of rack rows in a data center. On the other hand, at higher values of C r (higher rack density) the effect of specific surface area has a lower impact on the time constant Sp. Surface Area ft 2 /lb (m 2 /kg) 0.07 (0.014) 0.08 (0.016) 0.09 (0.018) Time Constant (τ), s Heat Capacity Ratio (C r ) Figure 2a: Variation of time constant with heat capacity ratio at various levels of rack specific surface area Room Ht 10 ft (3 m) 15 ft (4.6 m) ft (6.1 m) Time Constant (t), s Number of racks per 100 ft 2 (9.3 m 2 ) floor area Figure 2b: Variation of time constant with number of rack rows at various levels of room height. 216 ASHRAE Transactions
6 50 45 Time Constant (t), s Rack Weight 200 lb (90.7 kg) 300 lb (136 kg) 400 lb (181.4 kg) Number of racks per row Figure 2c: Variation of time constant with number of rack rows at various levels of rack weight. An increase in the data center room height can increase the heat capacity of the room and decrease the heat capacity ratio. As a result, as shown in Figure 2b, the time constant decreases with increase in the room height at all levels of rack densities. It means that a data center with higher ceilings would take longer to reach the R min. However, it should be noted that the increased heat capacity of a room helps in maintaining low air temperature levels as shown in the previous study (Khankari, 2010). In order to keep the time constant low, the layout of data centers with higher ceilings can be modified by increasing the number of rack rows which can provide larger surface area. Figure 2c shows that the weight of racks has relatively a little impact on the time constant in comparison to the specific surface area of the racks. HEAT CAPACITY RATIO (C R ) The heat capacity ratio (C r ), a measure of thermal capacitance of a data center, is a ratio of heat capacities of rack mass and room air. According to equation (5), C r increases with increase in the rack density (number of racks per unit floor area) and weight of individual racks but decreases with the increase in the height of a data center room. It is convenient to express the rack density in terms of number of racks per 100 ft 2 (9.3 m 2 ) of a data center floor area. Figure 3 shows the variation of C r with the number of racks for various room heights. This analysis is developed for the rack weight of 250 lb (113.4 kg). With increase in the height the heat capacity of the room increases, and therefore, the heat capacity ratio decreases. A fully occupied data center, depending on the depth (D) of racks, can realistically accommodate maximum four to six racks per 100 ft 2 (9.3 m 2 ). As shown in Figure 3 data centers with room height between 10 to 20 feet, C r values can approximately range from 10 to 3, and therefore according to Figure 2a, the time constant values can range from 25 to 125 seconds. As indicated by equation (4d), the ratio of R max and R min varies with C r. It should be noted this ratio is independent of the rate of heat generation or the heat load in a data center. This relationship is useful in computing the potential R min of a data center from the initial R max and the C r of a data center. This ratio can be determined from the Figure 3 just by adding 1 to the values of C r on the y axis. Thus, for the most common data center designs with four to six racks per 100 ft 2 (9.3 m 2 ) floor area, depending on the height of a data center, R min can be reduced to 1/4th to 1/11th of the R max ASHRAE 217
7 Rack Ht Heat Capacity Ratio (C r ) Room Ht 10 ft (3 m) 15 ft (4.6 m) 20 ft (6.1 m) 30 ft (9.1 m) Specific Surface Area of Racks (ft 2 /lb) m 2 /kg 7 ft (2.1 m) 5 ft (1.5 m) 3 ft (0.9 m) Number of racks per 100 ft 2 (9.3 m 2 ) floor area Number of racks per row Figure 3: Variation of heat capacity ratio (C r ) with number of racks. Figure 4: Variation of specific surface area (A s ) with number of racks Specific Surface Area The specific surface area affects the thermal conductance of a data center. The rate of heat transfer from the room air to the rack mass depends on the extent of the surface area of racks exposed to the surrounding moving air. The conductance (UA s ), and in turn, the time constant (τ), of a data center varies directly with the available surface area of racks. Data centers with larger available surface area can reach the minimum heating rate (R min ) in a shorter time. For most racks only the top and bottom surfaces are available for exchanging the heat. In addition, side panels of the end racks located at the end of each rack row are available for such exchange. Thus, the net available surface area of the racks varies with the size and number of racks, and number of rack rows. For this analysis the specific surface area is defined as the effective surface area of racks per unit weight of the rack. This can be computed by combining available surface areas of all racks and rack rows (equation 8a) and then dividing it by the total weight of the racks. If all racks in the data center are assumed to be identical, then the specific surface area can be computed by equation (8b). In this equation the total available surface area is expressed on a per rack basis and then divided by the weight of the individual rack. It should be noted that less number of racks per row (N rpr ) implies more number of rack rows. Figure 4 shows a variation of the specific surface area of racks with the number of racks per row for three different rack heights. With an increase in the number of racks per row (a fewer rack rows) the specific surface area of racks decreases. For example, for 7feet high racks increasing the number of racks from five to ten per row, the specific surface area can reduce by about 18 percent. Increasing the number of racks beyond 15 per row has a minimum impact on the specific surface area. It means for the data center with fewer racks, the layout of the racks plays an important role in determining the time constant. Equation (8) shows specific surface area decreases with an increase in the individual rack weight; however, as discussed before that rack weight has of a less impact on the time constant. APPLICATIONS This section demonstrates the application of the above analysis for comparing the thermal performance of data centers during a power outage. Three different data centers were considered for this application. A list of various design parameters for these data centers is documented in Table 2. The thermal parameters are computed from the equations presented in Table 1. Data center B (DC B) is considered as a default case. Data center A (DC A) is similar to the Data center B in all respects except it is only half occupied, which is often the case on the first day of a newlycommissioned data center. Data center C (DC C) is also similar to DC B but has a ceiling height of 15 feet instead of 10 feet. In all cases the value of racks per row is 218 ASHRAE Transactions
8 kept the same, and hence, the specific surface area in all the cases remains the same as well. Table 2: List of parameters for the application examples Design Parameters Data Center A Data Center B Data Center C Floor area, ft (232.2 m 2 ) 2500 (232.2 m 2 ) 2500 (232.2 m 2 ) Height, ft 10 (3 m) 10 (3 m) 15 (4.6 m) Heat load, W/ft 2 50 (538 W/m 2 ) 100 (1076 W/m 2 ) 100 (1076 W/m 2 ) Initial temperature, F 65 (18.33 C) 65 (18.33 C) 65 (18.33 C) Number of racks per 100 ft 2 (9.3 m 2 ) Number of racks per row Weight of individual rack, lb 250 (113 kg) 250 (113 kg) 250 (113 kg) Thermal Parameters Max rate of heating (R max ), F/s 0.25 (0.14 C/s) 0.52 (0.29 C/s) 0.34 (0.19 C/s) Min rate of heating (R min ), F/s 0.06 ( C/s) 0.07 (0.038 C/s) (0.036 C/s) Specific surface area, ft 2 /lb (0.02 m 2 /kg) (m 2 /kg) (m 2 /kg) Heat Capacity Ratio, Cr Time constant (t), s As shown in the Table 2, DC A has the highest value of time constant. In spite of the reduced heat load, as shown in Figure 5, it would take longer for DC A to reach its R min than DC B and DC C. With fewer racks, DC has a lower heat capacity ratio (C r ) than DC B, which in turn, results in a larger time constant. While it would take 67.4 seconds for DC A to reduce (R max R min ) to 36.8 percent level, DC B can achieve the same in 38.2 seconds. This situation can be improved by increasing the number of rack rows (reducing the number of racks per row parameter) which can help in increase the specific surface area. For example, if the number of racks per row in DC A is reduced to five, the time constant will reduce from 67.4 to 54.2 seconds. Like in the previous case, DC C also has lower heat capacity ratio than DC B, however, it is due to the higher ceiling height, which increases the heat capacity of the data center room. This results in larger time constant in the case of DC C than DC B. In spite of its lower R max value, as shown in Figure 5, it would take longer for DC C to reach its minimum rate of heating than DC B. Figure 6 shows a variation of room air temperature with time for all three data centers. It shows that DC A, due to lower heat load, has the lowest temperature levels. In spite of the same heat loads, the temperature levels in DC C are lower than DC B. This is due to the higher room height of DC C. In this case also if the number of racks per row is reduced to five, the time constant will reduce from 53.7 to 43.1 seconds DC A DC B DC C Theta % line Time (s) Figure 5: Variation of nondimensional rate of heating (θ) with time for the example cases in Table ASHRAE 219
9 DC A DC B DC C Temperature (F) Temperature (C) Time (s) Figure 6: Variation room air temperature with time for the example cases in Table 2. SUMMARY AND CONCLUSIONS A zero dimensional heat transfer model was developed to evaluate the rate of heating of room air during a power outage situation in a data center. Mathematical analysis indicates that the rate of heating of the room air can start initially at a maximum rate (R max ), and then, can exponentially reduce to a minimum rate (R min ), which is the lowest possible rate of heating that a data center can attain. The rate of this exponential decay depends on the time constant (τ), which is a characteristic of the design and layout of a data center. Data centers with larger time constant would take longer to reach the lowest level of heating, R min. A good design of a data center aims not only to keep the R min at low level but also tries to reduce the time constant (τ). The time constant (τ), which is independent of the heat load, depends on the room height, dimensions of racks, rack density, and on the number of racks per rackrow. These parameters are conveniently expressed in terms of the heat capacity ratio (C r ) and the specific surface area of racks (A s ) of data centers. This analysis demonstrates that increasing the heat capacity ratio and the specific surface area of a data center help in reducing the time constant. This can be achieved by increasing the rack density and number of rack rows, and by lowering the room height. However, lowering the room height can increase room air temperatures. In such situations it would be beneficial to arrange the layout of a data center with a higher number of rack rows without lowering the room height. Similarly the data centers with low rack densities can be arranged with a higher number of rack rows to reduce the time constant. The mathematical model developed in this paper demonstrates that the time constant can be employed as a matrix to compare and improve the thermal performance of data centers during a power outage. NOMENCLATURE Surface area of rack thermal mass (m 2 ) Specific surface area of racks area per unit weight of rack (m 2 /kg) Floor area of a data center (m 2 /kg) Heat capacity ratio of a data center Specific heat of rack mass (500 J/kg K) Depth of rack enclosures (m) Height of rack enclosures (m) 220 ASHRAE Transactions
10 Width of rack enclosures (m) Number of rack enclosures Number of rack rows Number of rack rows per rack per rack row Rate of heat generation from servers (W) t Rate of heat absorbed by room air (W) Rate of heat loss to rack enclosures (W) Rate of heating of a data center at time t (K/s) Maximum rate of heating of a data center (K/s) Minimum rate of heating of a data center (K/s) Temperature of room air (K) Temperature of rack thermal mass (K) Time (s) U Heat transfer coefficient of air over the rack surfaces (100 W/m 2 K) w Weight of an individual rack (kg) Heat capacity of room air (J/K) Heat capacity of rack mass (J/K) Thermal conductance between room air and rack mass (W/K) Temperature difference between room air and rack mass (K) Nondimensional rate of heating of a data center Time constant of a data center (s) REFERENCES ASHRAE ASHRAE Environmental Guidelines for Datacom Equipment  Expanding the Recommended Environmental Envelope. Atlanta: American Society of Heating Refrigeration and Air Conditioning Engineers, Inc. Khankari, K Thermal mass availability for cooling data centers during power shutdown. ASHRAE Transactions, Vol. 116, Pt ASHRAE 221
Thermal Mass Availability for Cooling Data Centers during Power Shutdown
2010 American Society of Heating, Refrigerating and AirConditioning Engineers, Inc. (www.ashrae.org). Published in ASHRAE Transactions (2010, vol 116, part 2). For personal use only. Additional reproduction,
More informationDataCenter 2020: hot aisle and cold aisle containment efficiencies reveal no significant differences
DataCenter 2020: hot aisle and cold aisle containment efficiencies reveal no significant differences November 2011 Powered by DataCenter 2020: hot aisle and cold aisle containment efficiencies reveal no
More informationData Center 2020: Delivering high density in the Data Center; efficiently and reliably
Data Center 2020: Delivering high density in the Data Center; efficiently and reliably March 2011 Powered by Data Center 2020: Delivering high density in the Data Center; efficiently and reliably Review:
More informationData Center Components Overview
Data Center Components Overview Power Power Outside Transformer Takes grid power and transforms it from 113KV to 480V Utility (grid) power Supply of high voltage power to the Data Center Electrical Room
More informationData Center Temperature Rise During a Cooling System Outage
Data Center Temperature Rise During a Cooling System Outage White Paper 179 Revision 0 By Paul Lin Simon Zhang Jim VanGilder > Executive summary The data center architecture and its IT load significantly
More informationData Center Temperature Rise During a Cooling System Outage
Data Center Temperature Rise During a Cooling System Outage White Paper 179 Revision 1 By Paul Lin Simon Zhang Jim VanGilder > Executive summary The data center architecture and its IT load significantly
More informationCooling Capacity Factor (CCF) Reveals Stranded Capacity and Data Center Cost Savings
WHITE PAPER Cooling Capacity Factor (CCF) Reveals Stranded Capacity and Data Center Cost Savings By Lars Strong, P.E., Upsite Technologies, Inc. Kenneth G. Brill, Upsite Technologies, Inc. 505.798.0200
More informationBenefits of Cold Aisle Containment During Cooling Failure
Benefits of Cold Aisle Containment During Cooling Failure Introduction Data centers are missioncritical facilities that require constant operation because they are at the core of the customerbusiness
More informationManaging Data Centre Heat Issues
Managing Data Centre Heat Issues Victor Banuelos Field Applications Engineer Chatsworth Products, Inc. 2010 Managing Data Centre Heat Issues Thermal trends in the data centre Hot Aisle / Cold Aisle design
More informationPower and Cooling for UltraHigh Density Racks and Blade Servers
Power and Cooling for UltraHigh Density Racks and Blade Servers White Paper #46 Introduction The Problem Average rack in a typical data center is under 2 kw Dense deployment of blade servers (1020 kw
More informationData Center Operating Cost Savings Realized by Air Flow Management and Increased Rack Inlet Temperatures
Data Center Operating Cost Savings Realized by Air Flow Management and Increased Rack Inlet Temperatures William Seeber Stephen Seeber Mid Atlantic Infrared Services, Inc. 5309 Mohican Road Bethesda, MD
More informationAPC APPLICATION NOTE #92
#92 Best Practices for Designing Data Centers with the InfraStruXure InRow RC By John Niemann Abstract The InfraStruXure InRow RC is designed to provide cooling at the row and rack level of a data center
More informationHow Does Your Data Center Measure Up? Energy Efficiency Metrics and Benchmarks for Data Center Infrastructure Systems
How Does Your Data Center Measure Up? Energy Efficiency Metrics and Benchmarks for Data Center Infrastructure Systems Paul Mathew, Ph.D., Staff Scientist Steve Greenberg, P.E., Energy Management Engineer
More informationOffice of the Government Chief Information Officer. Green Data Centre Practices
Office of the Government Chief Information Officer Green Data Centre Practices Version : 2.0 April 2013 The Government of the Hong Kong Special Administrative Region The contents of this document remain
More informationImproving Data Center Energy Efficiency Through Environmental Optimization
Improving Data Center Energy Efficiency Through Environmental Optimization How FineTuning Humidity, Airflows, and Temperature Dramatically Cuts Cooling Costs William Seeber Stephen Seeber Mid Atlantic
More informationCooling Audit for Identifying Potential Cooling Problems in Data Centers
Cooling Audit for Identifying Potential Cooling Problems in Data Centers By Kevin Dunlap White Paper #40 Revision 2 Executive Summary The compaction of information technology equipment and simultaneous
More informationUnique Airflow Visualization Techniques for the Design and Validation of AbovePlenum Data Center CFD Models
Unique Airflow Visualization Techniques for the Design and Validation of AbovePlenum Data Center CFD Models The MIT Faculty has made this article openly available. Please share how this access benefits
More informationData Center Cooling: Fend Off The Phantom Meltdown Of Mass Destruction. 670 Deer Road n Cherry Hill, NJ 08034 n 877.429.7225 n
Data Center Cooling: Fend Off The Phantom Meltdown Of Mass Destruction How To Preserve Your Servers And Prevent Overheating Your highperformance, multiprocessor servers are working hard, computing tons
More informationModule 1 : Conduction. Lecture 5 : 1D conduction example problems. 2D conduction
Module 1 : Conduction Lecture 5 : 1D conduction example problems. 2D conduction Objectives In this class: An example of optimization for insulation thickness is solved. The 1D conduction is considered
More informationVerizon SMARTS Data Center Design Phase 1 Conceptual Study Report Ms. Leah Zabarenko Verizon Business 2606A Carsins Run Road Aberdeen, MD 21001
Verizon SMARTS Data Center Design Phase 1 Conceptual Study Report Ms. Leah Zabarenko Verizon Business 2606A Carsins Run Road Aberdeen, MD 21001 Presented by: Liberty Engineering, LLP 1609 Connecticut Avenue
More informationServer Room Thermal Assessment
PREPARED FOR CUSTOMER Server Room Thermal Assessment Analysis of Server Room COMMERCIAL IN CONFIDENCE MAY 2011 Contents 1 Document Information... 3 2 Executive Summary... 4 2.1 Recommendation Summary...
More informationFanplusHeatsink Optimization Mechanical and Thermal Design with Reality
FanplusHeatsink Optimization Mechanical and Thermal Design with Reality Catharina R. Biber, Ph.D. InFocus Systems, Inc. 277B SW Parkway Avenue Wilsonville, OR 977 536858654 voice 536858842 fax Crbiber@alum.mit.edu
More informationIT@Intel. Thermal Storage System Provides Emergency Data Center Cooling
White Paper Intel Information Technology Computer Manufacturing Thermal Management Thermal Storage System Provides Emergency Data Center Cooling Intel IT implemented a lowcost thermal storage system that
More informationME 315  Heat Transfer Laboratory. Experiment No. 7 ANALYSIS OF ENHANCED CONCENTRIC TUBE AND SHELL AND TUBE HEAT EXCHANGERS
ME 315  Heat Transfer Laboratory Nomenclature Experiment No. 7 ANALYSIS OF ENHANCED CONCENTRIC TUBE AND SHELL AND TUBE HEAT EXCHANGERS A heat exchange area, m 2 C max maximum specific heat rate, J/(s
More informationImproving Data Center Efficiency with Rack or Row Cooling Devices:
Improving Data Center Efficiency with Rack or Row Cooling Devices: Results of ChillOff 2 Comparative Testing Introduction In new data center designs, capacity provisioning for everhigher power densities
More informationHigh Density Data Centers Fraught with Peril. Richard A. Greco, Principal EYP Mission Critical Facilities, Inc.
High Density Data Centers Fraught with Peril Richard A. Greco, Principal EYP Mission Critical Facilities, Inc. Microprocessors Trends Reprinted with the permission of The Uptime Institute from a white
More information White Paper  Data Centre Cooling. Best Practice
 White Paper  Data Centre Cooling Best Practice Release 2, April 2008 Contents INTRODUCTION... 3 1. AIR FLOW LEAKAGE... 3 2. PERFORATED TILES: NUMBER AND OPENING FACTOR... 4 3. PERFORATED TILES: WITH
More informationAir, Fluid Flow, and Thermal Simulation of Data Centers with Autodesk Revit 2013 and Autodesk BIM 360
Autodesk Revit 2013 Autodesk BIM 360 Air, Fluid Flow, and Thermal Simulation of Data Centers with Autodesk Revit 2013 and Autodesk BIM 360 Data centers consume approximately 200 terawatt hours of energy
More informationModelling and Evaluation of Distributed Airflow Control in Data Centers
Modelling and Evaluation of Distributed Airflow Control in Data Centers Modellering och utvärdering av styrning för luftflödesfördelning i datorhallar Therese Lindberg Faculty of Health, Science and Technology
More informationAn Introduction to Cold Aisle Containment Systems in the Data Centre
An Introduction to Cold Aisle Containment Systems in the Data Centre White Paper October 2010 By Zac Potts MEng Mechanical Engineer Sudlows October 2010 An Introduction to Cold Aisle Containment Systems
More informationVAV Laboratory Room Airflow The Lowdown on Turndown
Technology Report March, 2003 VAV Laboratory The Lowdown on Turndown Turndown comparison of these two turndown ratios. Note the small actual airflow difference between them. control ranges are normally
More informationSealing Gaps Under IT Racks: CFD Analysis Reveals Significant Savings Potential
TECHNICAL REPORT Sealing Gaps Under IT Racks: CFD Analysis Reveals Significant Savings Potential By Lars Strong, P.E., Upsite Technologies, Inc. Bruce Long, Upsite Technologies, Inc. +1.888.982.7800 upsite.com
More informationIntegrated Cabinets and Thermal Systems May 15, 2014 Panduit Korea Technical System Engineer Chester Ki
1 Integrated Cabinets and Thermal Systems May 15, 2014 Panduit Korea Technical System Engineer Chester Ki 4/10/2014 2 Agenda Market Trends Thermal Architectures Data Centre Cabinet Systems NetAccess Cabinet
More informationTHE PSEUDO SINGLE ROW RADIATOR DESIGN
International Journal of Mechanical Engineering and Technology (IJMET) Volume 7, Issue 1, JanFeb 2016, pp. 146153, Article ID: IJMET_07_01_015 Available online at http://www.iaeme.com/ijmet/issues.asp?jtype=ijmet&vtype=7&itype=1
More informationCombining Cold Aisle Containment with Intelligent Control to Optimize Data Center Cooling Efficiency
A White Paper from the Experts in BusinessCritical Continuity TM Combining Cold Aisle Containment with Intelligent Control to Optimize Data Center Cooling Efficiency Executive Summary Energy efficiency
More informationAir distribution effectiveness with stratified air distribution systems
Lee, K.S., Jiang, Z., and Chen, Q. 2009 Air distribution effectiveness with stratified air distribution systems, ASHRAE Transactions, 115(2). Air distribution effectiveness with stratified air distribution
More informationNews in Data Center Cooling
News in Data Center Cooling Wednesday, 8th May 2013, 16:00h Benjamin Petschke, Director Export  Products Stulz GmbH News in Data Center Cooling Almost any News in Data Center Cooling is about increase
More informationEðlisfræði 2, vor 2007
[ Assignment View ] [ Print ] Eðlisfræði 2, vor 2007 30. Inductance Assignment is due at 2:00am on Wednesday, March 14, 2007 Credit for problems submitted late will decrease to 0% after the deadline has
More informationOPTIMIZATION OF DATA CENTER CHILLED WATER COOLING SYSTEM ACCORDING TO ANNUAL POWER CONSUMPTION CRITERION
OPTIMIZATION OF DATA CENTER CHILLED WATER COOLING SYSTEM ACCORDING TO ANNUAL POWER CONSUMPTION CRITERION Piotr Kowalski 1, Mieczysław Porowski 2 1 Poznan University of Technology Piotrowo 5 60695 Poznan,
More informationElements of Energy Efficiency in Data Centre Cooling Architecture
Elements of Energy Efficiency in Data Centre Cooling Architecture Energy Efficient Data Center Cooling 1 STULZ Group of Companies Turnover 2006 Plastics Technology 400 Mio A/C Technology 200 Mio Total
More informationCold Logik. ColdLogik Water Cooled Cabinet Solution. Reduce Your Cooling Energy Consumption. Potential Savings In Excess of 60%
1 ColdLogik Water Cooled Cabinet Solution Reduce Your Cooling Energy Consumption Potential Savings In Excess of 60% CL20 Rear Door Heat Exchanger RDHx RDHx Principle Fitted to the rear of the cabinet the
More informationEnergy Performance Optimization of Server Room HVAC System
International Journal of Thermal Technologies EISSN 2277 4114 2 INPRESSCO, All Rights Reserved Available at http://inpressco.com/category/ijtt/ Research Article Manoj Jadhav * and Pramod Chaudhari Department
More informationTHERMAL LOSSES Thermal Losses Calculations
Calculations 1 THERMAL LOSSES Thermal Losses Calculations Employer : 4M SA Project Location : ASHRAE Office Room : Example from ASHRAE 2013 Handbook  Fundamentals : Chapter 18, Single Room Example Peak
More informationSaving Heating Costs In Warehouses
2005, American Society of Heating, Refrigerating and AirConditioning Engineers, Inc. (www.ashrae.org). Reprinted by permission from ASHRAE Journal, (Vol. 47, No. 12, December 2005). This article may not
More informationUnified Physical Infrastructure SM (UPI) Strategies for Smart Data Centers
Unified Physical Infrastructure SM (UPI) Strategies for Smart Data Centers Deploying a Vertical Exhaust System www.panduit.com WP09 September 2009 Introduction Business management applications and rich
More informationDesigning an Expert System For Critical Facility Energy Management and Maintenance
Designing an Expert System For Critical Facility Energy Management and Maintenance Dr. Izuh Obinelo senergy Thermal LLC 71 Spitbrook Rd, Suite 308, Nashua, NH 03060 Heat Density Trends in Data Centers
More informationThe New Data Center Cooling Paradigm The Tiered Approach
Product Footprint  Heat Density Trends The New Data Center Cooling Paradigm The Tiered Approach Lennart Ståhl Amdahl, Cisco, Compaq, Cray, Dell, EMC, HP, IBM, Intel, Lucent, Motorola, Nokia, Nortel, Sun,
More informationChoosing CloseCoupled IT Cooling Solutions
W H I T E P A P E R Choosing CloseCoupled IT Cooling Solutions Smart Strategies for Small to MidSize Data Centers Executive Summary As highdensity IT equipment becomes the new normal, the amount of
More informationSERVER ROOM CABINET INSTALLATION CONCEPTS
SERVER ROOM CABINET INSTALLATION CONCEPTS SERVER ROOM CABINET INSTALLATION CONCEPTS SERVER ROOM CABINET INSTALLATION CONCEPTS ZPAS 169 EXAMPLES OF SERVER ROOMS PROJECTS WITH ZPAS CABINETS Data Box in the
More informationComparing Air Cooler Ratings Part 1: Not All Rating Methods are Created Equal
Technical Bulletin By Bruce I. Nelson, P.E., President, Colmac Coil Manufacturing, Inc. Comparing Air Cooler Ratings Part 1: Not All Rating Methods are Created Equal SUMMARY Refrigeration air coolers (evaporators)
More informationHow to Build a Data Centre Cooling Budget. Ian Cathcart
How to Build a Data Centre Cooling Budget Ian Cathcart Chatsworth Products Topics We ll Cover Availability objectives Space and Load planning Equipment and design options Using CFD to evaluate options
More informationRittal White Paper 305: Selecting Air Conditioners for Industrial Enclosures By: Judith Koetzsch Mark Corcoran, Editor
Rittal White Paper 305: Selecting Air Conditioners for Industrial Enclosures By: Judith Koetzsch Mark Corcoran, Editor Executive Summary Choosing the right air conditioners for enclosures can have a tremendous
More informationPractice Problems on Conservation of Energy. heat loss of 50,000 kj/hr. house maintained at 22 C
COE_10 A passive solar house that is losing heat to the outdoors at an average rate of 50,000 kj/hr is maintained at 22 C at all times during a winter night for 10 hr. The house is to be heated by 50 glass
More informationAirflow and Cooling Performance of Data Centers: Two Performance Metrics
2008, American Society of Heating, Refrigerating and AirConditioning Engineers, Inc. (www.ashrae.org). Published in ASHRAE Transactions, Vol. 114, Part 2. For personal use only. Additional reproduction,
More informationHow Rowbased Data Center Cooling Works
How Rowbased Data Center Cooling Works White Paper 208 Revision 0 by Paul Lin and Victor Avelar Executive summary Rowbased data center cooling is normally regarded as a cold air supply architecture that
More informationDataCenter 2020: first results for energyoptimization at existing data centers
DataCenter : first results for energyoptimization at existing data centers July Powered by WHITE PAPER: DataCenter DataCenter : first results for energyoptimization at existing data centers Introduction
More informationANCIS I N C O R P O R A T E D
RoomLevel Energy and Thermal Management in Data Centers: The DOE Air Management Tool Presentation at IMAPS Advanced Technology Workshop on Thermal Management Palo Alto, CA, September 30, 2010 Magnus K.
More informationAisleLok Modular Containment vs. Legacy Containment: A Comparative CFD Study of IT Inlet Temperatures and Fan Energy Savings
WH I TE PAPE R AisleLok Modular Containment vs. : A Comparative CFD Study of IT Inlet Temperatures and Fan Energy Savings By Bruce Long, Upsite Technologies, Inc. Lars Strong, P.E., Upsite Technologies,
More informationChillerless Facilities: They May Be Closer Than You Think
Chillerless Facilities: They May Be Closer Than You Think A Dell Technical White Paper Learn more at Dell.com/PowerEdge/Rack David Moss Jon Fitch Paul Artman THIS WHITE PAPER IS FOR INFORMATIONAL PURPOSES
More informationEffect of Rack Server Population on Temperatures in Data Centers
Effect of Rack Server Population on Temperatures in Data Centers Rajat Ghosh, Vikneshan Sundaralingam, Yogendra Joshi G.W. Woodruff School of Mechanical Engineering Georgia Institute of Technology, Atlanta,
More informationImpacts of Perforated Tile Open Areas on Airflow Uniformity and Air Management Performance in a Modular Data Center
Impacts of Perforated Tile Open Areas on Airflow Uniformity and Air Management Performance in a Modular Data Center SangWoo Ham 1, HyeWon Dong 1, JaeWeon Jeong 1,* 1 Division of Architectural Engineering,
More informationCase Study: Opportunities to Improve Energy Efficiency in Three Federal Data Centers
Case Study: Opportunities to Improve Energy Efficiency in Three Federal Data Centers Prepared for the U.S. Department of Energy s Federal Energy Management Program Prepared By Lawrence Berkeley National
More informationBest Practices for Wirefree Environmental Monitoring in the Data Center
White Paper 11800 Ridge Parkway Broomfiled, CO 80021 18006382638 http://www.42u.com sales@42u.com Best Practices for Wirefree Environmental Monitoring in the Data Center Introduction Monitoring for
More informationAirflow Simulation Solves Data Centre Cooling Problem
Airflow Simulation Solves Data Centre Cooling Problem The owner s initial design for a data centre in China utilized 40 equipment racks filled with blade servers spread out in three rows along the length
More informationAnalysis of data centre cooling energy efficiency
Analysis of data centre cooling energy efficiency An analysis of the distribution of energy overheads in the data centre and the relationship between economiser hours and chiller efficiency Liam Newcombe
More informationRack Cooling Effectiveness in Data Centers and Telecom Central Offices: The Rack Cooling Index (RCI)
2005. American Society of Heating, Refrigerating and AirConditioning Engineers, Inc. Reprinted by permission from ASHRAE Transactions, Vol. 111, Part 2. This material may not be copied nor distributed
More informationBest Practices for Wirefree Environmental Monitoring in the Data Center
White Paper Best Practices for Wirefree Environmental Monitoring in the Data Center April 2012 Introduction Monitoring for environmental threats in the data center is not a new concept. Since the beginning
More informationUpgrading the PRS datacentres: space requirement. S. S. Mathur, GMIT, CRIS
Upgrading the PRS datacentres: space requirement S. S. Mathur, GMIT, CRIS PRS / UTS scenario: then and now Year 2000 PRS: 600 locations UTS: 0 locations Year 2008 PRS 1600 locations Eticketing Passengers
More informationA Comparative Study of Various High Density Data Center Cooling Technologies. A Thesis Presented. Kwok Wu. The Graduate School
A Comparative Study of Various High Density Data Center Cooling Technologies A Thesis Presented by Kwok Wu to The Graduate School in Partial Fulfillment of the Requirements for the Degree of Master of
More informationDATA CENTER COOLING INNOVATIVE COOLING TECHNOLOGIES FOR YOUR DATA CENTER
DATA CENTER COOLING INNOVATIVE COOLING TECHNOLOGIES FOR YOUR DATA CENTER DATA CENTERS 2009 IT Emissions = Aviation Industry Emissions Nations Largest Commercial Consumers of Electric Power Greenpeace estimates
More informationThermal Modeling of NiMH Battery Powering Electric Vehicles
Proceedings of the 5th WSEAS Int. Conf. on System Science and Simulation in Engineering, Tenerife, Canary Islands, Spain, December 1618, 06 5 Thermal ing of NiMH Battery Powering Electric Vehicles H.
More informationCalculating Total Cooling Requirements for Data Centers
Calculating Total Cooling Requirements for Data Centers By Neil Rasmussen White Paper #25 Revision 2 Executive Summary This document describes how to estimate heat output from Information Technology equipment
More informationBRUNSPAK Presents MARK S. EVANKO, Principal
BRUNSPAK Presents MARK S. EVANKO, Principal Data Centers of the Future and the Impact of High Density Computing on Facility Infrastructures  Trends, AirFlow, Green/LEED, Cost, and Schedule Considerations
More informationTHERMAL ANALYSIS OF A DATA CENTRE COOLING SYSTEM UNDER FAULT CONDITIONS
Eleventh International IBPSA Conference Glasgow, Scotland July 2730, 2009 THERMAL ANALYSIS OF A DATA CENTRE COOLING SYSTEM UNDER FAULT CONDITIONS Michaël Kummert 1, William Dempster 1, and Ken McLean
More informationData Centers WHAT S ONTHEHORIZON FOR NR HVAC IN TITLE 24 2013? SLIDE 1
WHAT S ONTHEHORIZON FOR NR HVAC IN TITLE 24 2013? SLIDE 1 Data Center CASE Scope Existing Title 24 2008 Scope Current scope ( 100 T242008) exempts process space from many of the requirements, however
More informationSoftware Development for Cooling Load Estimation by CLTD Method
IOSR Journal of Mechanical and Civil Engineering (IOSRJMCE) ISSN: 22781684Volume 3, Issue 6 (Nov.  Dec. 2012), PP 0106 Software Development for Cooling Load Estimation by CLTD Method Tousif Ahmed Department
More informationAdaptive strategies for office spaces in the UK climate
International Conference Passive and Low Energy Cooling 631 Adaptive strategies for office spaces in the UK climate I. Gallou Environment & Energy Studies Programme, Architectural Association Graduate
More informationElement D Services Heating, Ventilating, and Air Conditioning
PART 1  GENERAL 1.01 OVERVIEW A. This section supplements Design Guideline Element D3041 on air handling distribution with specific criteria for projects involving design of a Data Center spaces B. Refer
More informationCoupling Forced Convection in Air Gaps with Heat and Moisture Transfer inside Constructions
Coupling Forced Convection in Air Gaps with Heat and Moisture Transfer inside Constructions M. Bianchi Janetti 1, F. Ochs 1 and R. Pfluger 1 1 University of Innsbruck, Unit for Energy Efficient Buildings,
More informationAccess Server Rack Cabinet Compatibility Guide
Access Server Rack Cabinet Compatibility Guide A Guide to the Selection and Evaluation of Access Server Rack Cabinets for Compatibility and Use with Third Party Server Chassis Kalkenstraat 9193 B8800
More informationEnergy Recovery Systems for the Efficient Cooling of Data Centers using Absorption Chillers and Renewable Energy Resources
Energy Recovery Systems for the Efficient Cooling of Data Centers using Absorption Chillers and Renewable Energy Resources ALEXANDRU SERBAN, VICTOR CHIRIAC, FLOREA CHIRIAC, GABRIEL NASTASE Building Services
More informationispan, A Light Steel Floor System
ispan, A Light Steel Floor System D.M. Fox 1, R.M. Schuster 2, and M.R. Strickland 3 Abstract Described in this paper is a coldformed steel floor system called ispan. The system is comprised of multifunctional
More informationLiebert Hiross HPW The High Performance Wallmount Cooling Solutions for Telecom Mobile Remote Access Nodes
Precision Cooling for BusinessCritical Continuity Liebert Hiross HPW The High Performance Wallmount Cooling Solutions for Telecom Mobile Remote Access Nodes We re Emerson Network Power, backed by Emerson,
More informationA White Paper from the Experts in BusinessCritical Continuity TM. Data Center Cooling Assessments What They Can Do for You
A White Paper from the Experts in BusinessCritical Continuity TM Data Center Cooling Assessments What They Can Do for You Executive Summary Managing data centers and IT facilities is becoming increasingly
More informationData Center Power Consumption
Data Center Power Consumption A new look at a growing problem Fact  Data center power density up 10x in the last 10 years 2.1 kw/rack (1992); 14 kw/rack (2007) Racks are not fully populated due to power/cooling
More informationLeveraging Thermal Storage to Cut the Electricity Bill for Datacenter Cooling
Leveraging Thermal Storage to Cut the Electricity Bill for Datacenter Cooling Yefu Wang1, Xiaorui Wang1,2, and Yanwei Zhang1 ABSTRACT The Ohio State University 14 1 1 8 6 4 9 8 Time (1 minuts) 7 6 4 3
More informationHPC TCO: Cooling and Computer Room Efficiency
HPC TCO: Cooling and Computer Room Efficiency 1 Route Plan Motivation (Why do we care?) HPC Building Blocks: Compuer Hardware (What s inside my dataroom? What needs to be cooled?) HPC Building Blocks:
More informationUnderstanding How Cabinet Door Perforation Impacts Airflow by Travis North
& design deployment The first step in determining the proper perforation for an application is to understand the airflow requirements of the equipment that will be used in the cabinet. Understanding How
More informationDealing with Thermal Issues in Data Center Universal Aisle Containment
Dealing with Thermal Issues in Data Center Universal Aisle Containment Daniele Tordin BICSI RCDD Technical System Engineer  Panduit Europe Daniele.Tordin@Panduit.com AGENDA Business Drivers Challenges
More informationDriving Data Center Efficiency Through the Adoption of Best Practices
Data Center Solutions 2008 Driving Data Center Efficiency Through the Adoption of Best Practices Data Center Solutions Driving Data Center Efficiency Through the Adoption of Best Practices Executive Summary
More informationEnergy Efficient Thermal Management for Information Technology Infrastructure Facilities  The Data Center Challenges
Energy Efficient Thermal Management for Information Technology Infrastructure Facilities  The Data Center Challenges Yogendra Joshi G.W. Woodruff School of Mechanical Engineering Georgia Institute of
More informationIntegration of a fin experiment into the undergraduate heat transfer laboratory
Integration of a fin experiment into the undergraduate heat transfer laboratory H. I. AbuMulaweh Mechanical Engineering Department, Purdue University at Fort Wayne, Fort Wayne, IN 46805, USA Email: mulaweh@engr.ipfw.edu
More informationData Centre Cooling Air Performance Metrics
Data Centre Cooling Air Performance Metrics Sophia Flucker CEng MIMechE Ing Dr Robert Tozer MSc MBA PhD CEng MCIBSE MASHRAE Operational Intelligence Ltd. info@dcoi.com Abstract Data centre energy consumption
More informationData center upgrade proposal. (phase one)
Data center upgrade proposal (phase one) Executive Summary Great Lakes began a recent dialogue with a customer regarding current operations and the potential for performance improvement within the The
More informationHOW TO CONDUCT ENERGY SAVINGS ANALYSIS IN A FACILITY VALUE ENGINEERING STUDY
HOW TO CONDUCT ENERGY SAVINGS ANALYSIS IN A FACILITY VALUE ENGINEERING STUDY Benson Kwong, CVS, PE, CEM, LEED AP, CCE envergie consulting, LLC Biography Benson Kwong is an independent consultant providing
More informationANCIS I N C O R P O R A T E D
Introduction to Conference on Cutting Edge Data Center Cooling Solutions Magnus K. Herrlin, Ph.D. Principal Incorporated mherrlin@ancis.us www.ancis.us Copyright 2005 Inc. 1 The Next 30 Minutes± Some Selected
More informationComsol Laboration: Heat Conduction in a Chip
Comsol Laboration: Heat Conduction in a Chip JO, CSC January 11, 2012 1 Physical configuration A chip on a circuit board is heated inside and cooled by convection by the surrounding fluid. We consider
More informationRittal White Paper 508: Economized Data Center Cooling Defining Methods & Implementation Practices By: Daniel Kennedy
Rittal White Paper 508: Economized Data Center Cooling Defining Methods & Implementation Practices By: Daniel Kennedy Executive Summary Data center owners and operators are in constant pursuit of methods
More informationSupporting Cisco Switches In Hot Aisle/Cold Aisle Data Centers
CABINETS: ENCLOSED THERMAL MOUNTING MANAGEMENT SYSTEMS WHITE PAPER Supporting Cisco Switches In Hot Aisle/Cold Aisle Data Centers 8008344969 techsupport@chatsworth.com www.chatsworth.com All products
More informationBenefits of. Air Flow Management. Data Center
Benefits of Passive Air Flow Management in the Data Center Learning Objectives At the end of this program, participants will be able to: Readily identify if opportunities i where networking equipment
More information