A Hybrid Methodology for the Optimization of Data Center Room Layout

2003 ◽  
Author(s):  
Shrishail Guggari ◽  
Dereje Agonafer ◽  
Christian Belady ◽  
Lennart Stahl
Keyword(s):  
Data Center ◽  
Data Centers ◽  
Flow Distribution ◽  
High Heat ◽  
Complex Data ◽  
Efficient Design ◽  
Modeling And Analysis ◽  
Improve Energy Efficiency ◽  
Computational Fluid Dynamics Cfd ◽  
Analytical Tools

Today’s data centers are designed for handling heat densities of 1000W/m2 at the room level. Trends indicate that these heat densities will exceed 3000W/m2 in the near future. As a result, cooling of data centers has emerged as an area of increasing importance in electronics thermal management. With these high heat loads, data center layout and design cannot rely on intuitive design of air distribution and requires analytical tools to provide the necessary insight to the problem. These tools can also be used to optimize the layout of the room to improve energy efficiency in the data center. In this paper, first an under floor analysis is done to find an optimized layout based on flow distribution through perforated tiles, then a complete Computational Fluid Dynamics (CFD) model of the data center facility is done to check for desired cooling and air flow distribution throughout the room. A robust methodology is proposed which helps for fast, easy, efficient modeling and analysis of data center design. Results are displayed to provide some guidance on the layout and design of data center. The resulting design approach is very simple and well suited for the energy efficient design of complex data centers and server farms.

Parametric Study of Hybrid Cooling Solution for Thermal Management of Data Centers

2007 ◽  
Author(s):  
Veerendra Mulay ◽  
Saket Karajgikar ◽  
Dereje Agonafer ◽  
Roger Schmidt ◽  
Madhusudan Iyengar
Keyword(s):  
Thermal Management ◽  
Data Center ◽  
Parametric Study ◽  
Heat Load ◽  
Data Centers ◽  
High Heat ◽  
Inlet Temperature ◽  
Air Cooling ◽  
Air Conditioners ◽  
Hybrid Cooling

The power trend for Server systems continues to grow thereby making thermal management of Data centers a very challenging task. Although various configurations exist, the raised floor plenum with Computer Room Air Conditioners (CRACs) providing cold air is a popular operating strategy. The air cooling of data center however, may not address the situation where more energy is expended in cooling infrastructure than the thermal load of data center. Revised power trend projections by ASHRAE TC 9.9 predict heat load as high as 5000W per square feet of compute servers’ equipment footprint by year 2010. These trend charts also indicate that heat load per product footprint has doubled for storage servers during 2000–2004. For the same period, heat load per product footprint for compute servers has tripled. Amongst the systems that are currently available and being shipped, many racks exceed 20kW. Such high heat loads have raised concerns over limits of air cooling of data centers similar to air cooling of microprocessors. A hybrid cooling strategy that incorporates liquid cooling along with air cooling can be very efficient in these situations. A parametric study of such solution is presented in this paper. A representative data center with 40 racks is modeled using commercially available CFD code. The variation in rack inlet temperature due to tile openings, underfloor plenum depths is reported.

Expanded Assessment of a Practical Thermally Aware Energy-Optimized Load Placement Strategy for Open-Aisle, Air-Cooled Data Centers

2013 ◽  
Vol 135 (3) ◽  
Author(s):  
Dustin W. Demetriou ◽  
H. Ezzat Khalifa
Keyword(s):  
Real Time ◽  
Data Center ◽  
Data Centers ◽  
Thermal Environment ◽  
Inlet Temperature ◽  
Airflow Rate ◽  
Time Data ◽  
Improve Energy Efficiency ◽  
Air Temperatures ◽  
Holistic Optimization

This paper expands on the work presented by Demetriou and Khalifa (Demetriou and Khalifa, 2013, “Thermally Aware, Energy-Based Load Placement in Open-Aisle, Air-Cooled Data Centers,” ASME J. Electron. Packag., 135(3), p. 030906) that investigated practical IT load placement options in open-aisle, air-cooled data centers. The study found that a robust approach was to use real-time temperature measurements at the inlet of the racks to remove IT load from the servers with the warmest inlet temperature. By considering the holistic optimization of the data center load placement strategy and the cooling infrastructure optimization, for a range of data center IT utilization levels, this study investigated the effect of ambient temperatures on the data center operation, the consolidation of servers by completely shutting them off, a complementary strategy to those presented by Demetriou and Khalifa (Demetriou and Khalifa, 2013, “Thermally Aware, Energy-Based Load Placement in Open-Aisle, Air-Cooled Data Centers,” ASME J. Electron. Packag., 135(3), p. 030906) for increasing the IT load beginning with servers that have the coldest inlet temperature and finally the development of load placement rules via either static (i.e., during data center benchmarking) or dynamic (using real-time data from the current thermal environment) allocation. In all of these case studies, by using a holistic optimization of the data center and associated cooling infrastructure, a key finding has been that a significant amount of savings in the cooling infrastructure's power consumption is seen by reducing the CRAH's airflow rate. In many cases, these savings can be larger than providing higher temperature chilled water from the refrigeration units. Therefore, the path to realizing the industry's goal of higher IT equipment inlet temperatures to improve energy efficiency should be through both a reduction in air flow rate and increasing supply air temperatures and not necessarily through only higher CRAH supply air temperatures.

A Comparison of Parametric and Multivariable Optimization Techniques in a Raised-Floor Data Center

2013 ◽  
Vol 135 (3) ◽  
Author(s):  
Srinarayana Nagarathinam ◽  
Babak Fakhim ◽  
Masud Behnia ◽  
Steve Armfield
Keyword(s):  
Data Center ◽  
Air Conditioning ◽  
Data Centers ◽  
Parametric Optimization ◽  
Flow Distribution ◽  
Optimization Procedure ◽  
Optimization Techniques ◽  
Maximum Temperature ◽  
Response Surface Optimization ◽  
Ceiling Height

It is well known that the flow distribution in data centers can be effected by a variety of parameters such as rack and computer room air conditioning (CRAC) positions, raised-floor height, ceiling height, and percentage opening of perforated tiles. In the present paper, numerical simulations are conducted to optimize the layout of a raised-floor data center with respect to these parameters. Two different approaches have been used: parametric optimization; and a multivariable approach using response surface optimization. In the parametric optimization procedure, the data center is optimized with respect to the maximum temperature in the room. While in the multivariable approach, a cost function is constructed from all the rack inlet temperatures and is minimized. The results show that the multivariable approach is computationally economical and the optimized layout gives a better thermal performance compared to that of parametric optimization.

Energy-Efficient Air Cooling of Data Centers at 2000 W/ft2

2009 ◽  
Author(s):  
Magnus K. Herrlin ◽  
Michael K. Patterson
Keyword(s):  
Energy Efficiency ◽  
Data Center ◽  
Energy Efficient ◽  
Data Centers ◽  
High Heat ◽  
High Density ◽  
Cfd Modeling ◽  
Air Cooling ◽  
Capital Costs ◽  
Design Considerations

Increased Information and Communications Technology (ICT) capability and improved energy-efficiency of today’s server platforms have created opportunities for the data center operator. However, these platforms also test the ability of many data center cooling systems. New design considerations are necessary to effectively cool high-density data centers. Challenges exist in both capital costs and operational costs in the thermal management of ICT equipment. This paper details how air cooling can be used to address both challenges to provide a low Total Cost of Ownership (TCO) and a highly energy-efficient design at high heat densities. We consider trends in heat generation from servers and how the resulting densities can be effectively cooled. A number of key factors are reviewed and appropriate design considerations developed to air cool 2000 W/ft2 (21,500 W/m2). Although there are requirements for greater engineering, such data centers can be built with current technology, hardware, and best practices. The density limitations are shown primarily from an airflow management and cooling system controls perspective. Computational Fluid Dynamics (CFD) modeling is discussed as a key part of the analysis allowing high-density designs to be successfully implemented. Well-engineered airflow management systems and control systems designed to minimize airflow by preventing mixing of cold and hot airflows allow high heat densities. Energy efficiency is gained by treating the whole equipment room as part of the airflow management strategy, making use of the extended environmental ranges now recommended and implementing air-side air economizers.

Data Center Cooling Efficiency Improvement Through Localized and Optimized Cooling Resources Delivery

2012 ◽  
Author(s):  
Rongliang Zhou ◽  
Cullen Bash ◽  
Zhikui Wang ◽  
Alan McReynolds ◽  
Thomas Christian ◽  
...  
Keyword(s):  
Steady State ◽  
Data Center ◽  
Data Centers ◽  
Air Flow ◽  
Flow Distribution ◽  
Resource Provisioning ◽  
Cooling Power ◽  
Optimization Approach ◽  
Cooling Efficiency ◽  
Efficiency Improvement

Data centers are large computing facilities that can house tens of thousands of computer servers, storage and networking devices. They can consume megawatts of power and, as a result, reject megawatts of heat. For more than a decade, researchers have been investigating methods to improve the efficiency by which these facilities are cooled. One of the key challenges to maintain highly efficient cooling is to provide on demand cooling resources to each server rack, which may vary with time and rack location within the larger data center. In common practice today, chilled water or refrigerant cooled computer room air conditioning (CRAC) units are used to reject the waste heat outside the data center, and they also work together with the fans in the IT equipment to circulate air within the data center for heat transport. In a raised floor data center, the cool air exiting the multiple CRAC units enters the underfloor plenum before it is distributed through the vent tiles in the cold aisles to the IT equipment. The vent tiles usually have fixed openings and are not adapted to accommodate the flow demand that can vary from cold aisle to cold aisle or rack to rack. In this configuration, CRAC units have the extra responsibilities of cooling resources distribution as well as provisioning. The CRAC unit, however, does not have the fine control granularity to adjust air delivery to individual racks since it normally affects a larger thermal zone, which consists of a multiplicity of racks arranged into rows. To better match cool air demand on a per cold aisle or rack basis, floor-mounted adaptive vent tiles (AVT) can be used to replace CRAC units for air delivery adjustment. In this arrangement, each adaptive vent tile can be remotely commanded from fully open to fully close for finer local air flow regulation. The optimal configuration for a multitude of AVTs in a data center, however, can be far from intuitive because of the air flow complexity. To unleash the full potential of the AVTs for improved air flow distribution and hence higher cooling efficiency, we propose a two-step approach that involves both steady-state and dynamic optimization to optimize the cooling resource provisioning and distribution within raised-floor air cooled data centers with rigid or partial containment. We first perform a model-based steady-state optimization to optimize whole data center air flow distribution. Within each cold aisle, all AVTs are configured to a uniform opening setting, although AVT opening may vary from cold aisle to cold aisle. We then use decentralized dynamic controllers to optimize the settings of each CRAC unit such that the IT equipment thermal requirement is satisfied with the least cooling power. This two-step optimization approach simplifies the large scale dynamic control problem, and its effectiveness in cooling efficiency improvement is demonstrated through experiments in a research data center.

Numerical Study for Data Center Cooling Using Active Tiles

2015 ◽  
Author(s):  
Zhihang Song
Keyword(s):  
Data Center ◽  
Data Centers ◽  
Numerical Study ◽  
Thermal Design ◽  
Load Demand ◽  
Design Variables ◽  
Data Center Cooling ◽  
Floor Tiles ◽  
Flow Features ◽  
Computational Fluid Dynamics Cfd

The design of raised floor, hot/cold aisle data centers has become a widely used approach for data center cooling. However, more advanced cooling solution is still needed to achieve better managed airflow distributions and improved energy efficiency. The use of fan assisted floor tiles (i.e., active tiles) is being investigated as an evolution of Data Center cooling solutions to accommodate higher heat load demand. In this study, compact models of fan assisted tiles was imported into a basic hot aisle/cold aisle data center configuration built and analyzed using the computational fluid dynamics (CFD) technique. The significant thermal design aspects under numerical investigation include: fan curve, swirl settings, and under-floor pressure (with and without aisle containment). The flow features affected by the critical design variables are consequently compared and discussed. It might be concluded that appropriately designed fan assisted floor tiles might meet a promise of optimizing the cooling arrangement in data centers.

Energy Efficiency and Air Quality Considerations in Airside Economized Data Centers

2015 ◽  
Author(s):  
Levente J. Klein ◽  
Sergio A. Bermudez ◽  
Fernando J. Marianno ◽  
Hendrik F. Hamann ◽  
Prabjit Singh
Keyword(s):  
Energy Efficiency ◽  
Air Quality ◽  
Data Center ◽  
Data Centers ◽  
High Sensitivity ◽  
Air Cooling ◽  
Improve Energy Efficiency ◽  
Free Air ◽  
Recent Developments ◽  
Contamination Event

Many data center operators are considering the option to convert from mechanical to free air cooling to improve energy efficiency. The main advantage of free air cooling is the elimination of chiller and Air Conditioning Unit operation when outdoor temperature falls below the data center temperature setpoint. Accidental introduction of gaseous pollutants in the data center along the fresh air and potential latency in response of control infrastructure to extreme events are some of the main concerns for adopting outside air cooling in data centers. Recent developments of ultra-high sensitivity corrosion sensors enable the real time monitoring of air quality and thus allow a better understanding of how airflow, relative humidity, and temperature fluctuations affect corrosion rates. Both the sensitivity of sensors and wireless networks ability to detect and react rapidly to any contamination event make them reliable tools to prevent corrosion related failures. A feasibility study is presented for eight legacy data centers that are evaluated to implement free air cooling.

Cluster of High-Powered Racks Within a Raised-Floor Computer Data Center: Effect of Perforated Tile Flow Distribution on Rack Inlet Air Temperatures

2004 ◽  
Vol 126 (4) ◽  
pp. 510-518 ◽  
Author(s):  
Roger Schmidt ◽  
Ethan Cruz
Keyword(s):  
Data Center ◽  
Control Volume ◽  
Flow Distribution ◽  
Computer Code ◽  
Cfd Model ◽  
Computer Data ◽  
Air Temperatures ◽  
Finite Control ◽  
Computational Fluid Dynamics Cfd ◽  
Tile Flow

This paper focuses on the effect on rack inlet air temperatures as a result of maldistribution of airflows exiting the perforated tiles located adjacent to the fronts of the racks. The flow distribution exiting the perforated tiles was generated from a computational fluid dynamics (CFD) tool called Tileflow (trademark of Innovative Research, Inc.). Both raised floor heights and perforated tile-free areas were varied in order to explore the effect on rack inlet temperatures. The flow distribution exiting the perforated tiles was used as boundary conditions to the above-floor CFD model. A CFD model was generated for the room with electronic equipment installed on a raised floor. Forty racks of data processing (DP) equipment were arranged in rows in a data center cooled by chilled air exhausting from perforated floor tiles. The chilled air was provided by four A/C units placed inside a room 12.1 m wide×13.4 m long. Because the arrangement of the racks in the data center was symmetric, only half of the data center was modeled. The numerical modeling for the area above the raised floor was performed using a commercially available finite control volume computer code called Flotherm (trademark of Flomerics, Inc.). The flow was modeled using the k-e turbulence model. Results are displayed to provide some guidance on the design and layout of a data center.

scholarly journals A Temperature-Risk and Energy-Saving Evaluation Model for Supporting Energy-Saving Measures for Data Center Server Rooms

Energies ◽  
2020 ◽  
Vol 13 (19) ◽  
pp. 5222 ◽  
Author(s):  
Kosuke Sasakura ◽  
Takeshi Aoki ◽  
Masayoshi Komatsu ◽  
Takeshi Watanabe
Keyword(s):  
Energy Saving ◽  
Data Center ◽  
Data Centers ◽  
Prediction Models ◽  
Evaluation Model ◽  
High Heat ◽  
High Accuracy ◽  
Information And Communication ◽  
Saving Effect ◽  
Efficiency And Reliability

As data centers have become increasingly important in recent years their operational management must attain higher efficiency and reliability. Moreover, the power consumption of a data center is extremely large, and it is anticipated that it will continue to increase, so energy saving has become an urgent issue concerning data centers. In the meantime, the environment of the server rooms in data centers has become complicated owing to the introduction of virtualization technology, the installation of high-heat density information and communication technology (ICT) equipment and racks, and the diversification of cooling methods. It is very difficult to manage a server room in the case of such a complicated environment. When energy-saving measures are implemented in a server room with such a complicated environment, it is important to evaluate “temperature risks” in advance and calculate the energy-saving effect after the measures are taken. Under those circumstances, in this study, two prediction models are proposed: a model that predicts the rack intake temperature (so that the temperature risk can be evaluated in support of energy-saving measures implemented in the server room) and a model that evaluates the energy-saving effect (in relation to a baseline). Specifically, the models were constructed by using machine learning. The first constructed model evaluates the temperature risk in a verification room in advance, and it was confirmed that the model can evaluate the risk beforehand with high accuracy. The second constructed model—“baseline model” hereafter—supports energy-saving measures, and it was confirmed that the model can calculate the baseline (energy consumption) with high accuracy as well. Moreover, the effect of proposal process of energy-saving measures in the verification room was verified by using the two proposed models. In particular, the effectiveness of the model for evaluating temperature risk in advance and that of a technology for visualizing the energy-saving effect were confirmed.

Liquid Cooling for Thermal Management of Data Centers

2008 ◽  
Author(s):  
Veerendra Mulay ◽  
Dereje Agonafer ◽  
Roger Schmidt
Keyword(s):  
Thermal Management ◽  
Data Center ◽  
Heat Load ◽  
Data Centers ◽  
High Heat ◽  
Air Cooling ◽  
Liquid Cooling ◽  
Air Conditioners ◽  
Server Systems ◽  
Heat Loads

The power trend for Server systems continues to grow thereby making thermal management of Data centers a very challenging task. Although various configurations exist, the raised floor plenum with Computer Room Air Conditioners (CRACs) providing cold air is a popular operating strategy. The air cooling of data center however, may not address the situation where more energy is expended in cooling infrastructure than the thermal load of data center. Revised power trend projections by ASHRAE TC 9.9 predict heat load as high as 5000W per square feet of compute servers’ equipment footprint by year 2010. These trend charts also indicate that heat load per product footprint has doubled for storage servers during 2000–2004. For the same period, heat load per product footprint for compute servers has tripled. Amongst the systems that are currently available and being shipped, many racks exceed 20kW. Such high heat loads have raised concerns over limits of air cooling of data centers similar to air cooling of microprocessors. Thermal management of such dense data center clusters using liquid cooling is presented.

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