Exergy Analysis of Data Center Thermal Management Systems

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

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

Exergy-Based Optimization Strategies for Multi-Component Data Center Thermal Management: Part I — Analysis

2005 ◽  
Author(s):  
Amip J. Shah ◽  
Van P. Carey ◽  
Cullen E. Bash ◽  
Chandrakant D. Patel
Keyword(s):  
Thermal Management ◽  
Data Center ◽  
Air Conditioning ◽  
Data Centers ◽  
Heat Dissipation ◽  
Real Data ◽  
Management Systems ◽  
Prior Work ◽  
Operating Strategy ◽  
Air Space

As heat dissipation in data centers rises by orders of magnitude, inefficiencies such as recirculation will have an increasingly significant impact on the thermal manageability and energy efficiency of the cooling infrastructure. For example, prior work has shown that for simple data centers with a single Computer Room Air-Conditioning (CRAC) unit, an operating strategy that fails to account for inefficiencies in the air space can result in suboptimal performance. To enable system-wide optimality, an exergy-based approach to CRAC control has previously been proposed. However, application of such a strategy in a real data center environment is limited by the assumptions inherent to the single-CRAC derivation. This paper addresses these assumptions by modifying the exergy-based approach to account for the additional interactions encountered in a multi-component environment. It is shown that the modified formulation provides the framework necessary to evaluate performance of multi-component data center thermal management systems under widely different operating circumstances.

Exergy Analysis of Data Center Thermal Management Systems

2012 ◽  
pp. 383-446 ◽  
Author(s):  
Amip J. Shah ◽  
Van P. Carey ◽  
Cullen E. Bash ◽  
Chandrakant D. Patel ◽  
Ratnesh K. Sharma
Keyword(s):  
Thermal Management ◽  
Data Center ◽  
Exergy Analysis ◽  
Management Systems

Perimeter Cooling Unit and Localized Row-Based Cooling Unit Transient Air Flow Effects Modeling and Characterization in Data Centers

2015 ◽  
Author(s):  
Tianyi Gao ◽  
James Geer ◽  
Bahgat G. Sammakia ◽  
Russell Tipton ◽  
Mark Seymour
Keyword(s):  
Thermal Management ◽  
Data Center ◽  
Data Centers ◽  
Cooling System ◽  
Air Flow ◽  
Cooling Systems ◽  
Dynamic Thermal Management ◽  
Hybrid Cooling ◽  
Cooling Unit ◽  
Cooling Air

Cooling power constitutes a large portion of the total electrical power consumption in data centers. Approximately 25%∼40% of the electricity used within a production data center is consumed by the cooling system. Improving the cooling energy efficiency has attracted a great deal of research attention. Many strategies have been proposed for cutting the data center energy costs. One of the effective strategies for increasing the cooling efficiency is using dynamic thermal management. Another effective strategy is placing cooling devices (heat exchangers) closer to the source of heat. This is the basic design principle of many hybrid cooling systems and liquid cooling systems for data centers. Dynamic thermal management of data centers is a huge challenge, due to the fact that data centers are operated under complex dynamic conditions, even during normal operating conditions. In addition, hybrid cooling systems for data centers introduce additional localized cooling devices, such as in row cooling units and overhead coolers, which significantly increase the complexity of dynamic thermal management. Therefore, it is of paramount importance to characterize the dynamic responses of data centers under variations from different cooling units, such as cooling air flow rate variations. In this study, a detailed computational analysis of an in row cooler based hybrid cooled data center is conducted using a commercially available computational fluid dynamics (CFD) code. A representative CFD model for a raised floor data center with cold aisle-hot aisle arrangement fashion is developed. The hybrid cooling system is designed using perimeter CRAH units and localized in row cooling units. The CRAH unit supplies centralized cooling air to the under floor plenum, and the cooling air enters the cold aisle through perforated tiles. The in row cooling unit is located on the raised floor between the server racks. It supplies the cooling air directly to the cold aisle, and intakes hot air from the back of the racks (hot aisle). Therefore, two different cooling air sources are supplied to the cold aisle, but the ways they are delivered to the cold aisle are different. Several modeling cases are designed to study the transient effects of variations in the flow rates of the two cooling air sources. The server power and the cooling air flow variation combination scenarios are also modeled and studied. The detailed impacts of each modeling case on the rack inlet air temperature and cold aisle air flow distribution are studied. The results presented in this work provide an understanding of the effects of air flow variations on the thermal performance of data centers. The results and corresponding analysis is used for improving the running efficiency of this type of raised floor hybrid data centers using CRAH and IRC units.

Application of Exploratory Data Analysis (EDA) Techniques to Temperature Data in a Conventional Data Center

2007 ◽  
Author(s):  
Ratnesh Sharma ◽  
Rocky Shih ◽  
Chandrakant Patel ◽  
John Sontag
Keyword(s):  
Data Analysis ◽  
Thermal Management ◽  
High Power ◽  
Data Center ◽  
Data Centers ◽  
Exploratory Data Analysis ◽  
Temperature Data ◽  
High Density ◽  
Exploratory Data ◽  
Mission Critical

Data centers are the computational hub of the next generation. Rise in demand for computing has driven the emergence of high density datacenters. With the advent of high density, mission-critical datacenters, demand for electrical power for compute and cooling has grown. Deployment of a large number of high powered computer systems in very dense configurations in racks within data centers will result in very high power densities at room level. Hosting business and mission-critical applications also demand a high degree of reliability and flexibility. Managing such high power levels in the data center with cost effective reliable cooling solutions is essential to feasibility of pervasive compute infrastructure. Energy consumption of data centers can also be severely increased by over-designed air handling systems and rack layouts that allow the hot and cold air streams to mix. Absence of rack level temperature monitoring has contributed to lack of knowledge of air flow patterns and thermal management issues in conventional data centers. In this paper, we present results from exploratory data analysis (EDA) of rack-level temperature data collected over a period of several months from a conventional production datacenter. Typical datacenters experience surges in power consumption due to rise and fall in compute demand. These surges can be long term, short term or periodic, leading to associated thermal management challenges. Some variations may also be machine-dependent and vary across the datacenter. Yet other thermal perturbations may be localized and momentary. Random variations due to sensor response and calibration, if not identified, may lead to erroneous conclusions and expensive faults. Among other indicators, EDA techniques also reveal relationships among sensors and deployed hardware in space and time. Identification of such patterns can provide significant insight into data center dynamics for future forecasting purposes. Knowledge of such metrics enables energy-efficient thermal management by helping to create strategies for normal operation and disaster recovery for use with techniques like dynamic smart cooling.

Energy Aware Grid: Global Workload Placement Based on Energy Efficiency

2003 ◽  
Author(s):  
Chandrakant Patel ◽  
Ratnesh Sharma ◽  
Cullen Bash ◽  
Sven Graupner
Keyword(s):  
Energy Efficiency ◽  
Thermal Management ◽  
Pervasive Computing ◽  
Data Center ◽  
Data Centers ◽  
Global Network ◽  
New Delhi ◽  
Energy Aware ◽  
And Storage ◽  
Grid Based

Computing will be pervasive, and enablers of pervasive computing will be data centers housing computing, networking and storage hardware. The data center of tomorrow is envisaged as one containing thousands of single board computing systems deployed in racks. A data center, with 1000 racks, over 30,000 square feet, would require 10 MW of power to power the computing infrastructure. At this power dissipation, an additional 5 MW would be needed by the cooling resources to remove the dissipated heat. At $100/MWh, the cooling alone would cost $4 million per annum for such a data center. The concept of Computing Grid, based on coordinated resource sharing and problem solving in dynamic, multi-institutional virtual organizations, is emerging as the new paradigm in distributed and pervasive computing for scientific as well as commercial applications. We envision a global network of data centers housing an aggregation of computing, networking and storage hardware. The increased compaction of such devices in data centers has created thermal and energy management issues that inhibit sustainability of such a global infrastructure. In this paper, we propose the framework of Energy Aware Grid that will provide a global utility infrastructure explicitly incorporating energy efficiency and thermal management among data centers. Designed around an energy-aware co-allocator, workload placement decisions will be made across the Grid, based on data center energy efficiency coefficients. The coefficient, evaluated by the data center’s resource allocation manager, is a complex function of the data center thermal management infrastructure and the seasonal and diurnal variations. A detailed procedure for implementation of a test case is provided with an estimate of energy savings to justify the economics. An example workload deployment shown in the paper aspires to seek the most energy efficient data center in the global network of data centers. The locality based energy efficiency in a data center is shown to arise from use of ground coupled loops in cold climates to lower ambient temperature for heat rejection e.g. computing and rejecting heat from a data center at nighttime ambient of 20°C. in New Delhi, India while Phoenix, USA is at 45°C. The efficiency in the cooling system in the data center in New Delhi is derived based on lower lift from evaporator to condenser. Besides the obvious advantage due to external ambient, the paper also incorporates techniques that rate the efficiency arising from internal thermo-fluids behavior of a data center in workload placement decision.

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.

Effective Thermal Management of Data Centers Using Efficient Cabinet Designs

2009 ◽  
Author(s):  
Veerendra Mulay ◽  
Dereje Agonafer ◽  
Gary Irwin ◽  
Darshan Patell
Keyword(s):  
Thermal Management ◽  
Environmental Protection Agency ◽  
Data Center ◽  
Energy Use ◽  
Data Centers ◽  
Energy Usage ◽  
Protection Agency ◽  
Cold Air ◽  
New Concepts ◽  
Entire Nation

Rising heat load trends in data center facilities have raised concerns over energy usage. The environmental protection agency has reported that the energy used in 2006 by data center industry was 1.5% of the total energy usage by entire nation. The experts agree that by year 2010, this usage will approach 2% of the annual energy use nationwide. Although many new concepts such as airside economizers and cogeneration are gaining traction, many data center facilities spend considerable energy in cooling. In this study, various cabinet designs are discussed. Isolating the supplied cold air from hot exhaust air is always a challenge in thermal management of data center facilities. A cabinet design that employs chimney to aid the isolation of hot and cold air is discussed. A computational model of representative data center is created to study the effectiveness of design under various supply air fractions.

Thermal Management Issues in Operational Data Centers: Computational Fluid Dynamics Analysis and Experimental Study

2017 ◽  
Vol 9 (3) ◽  
Author(s):  
Babak Fakhim ◽  
Srinarayana Nagarathinam ◽  
Steven W. Armfield ◽  
Masud Behnia
Keyword(s):  
Thermal Management ◽  
Data Center ◽  
Data Centers ◽  
Electricity Consumption ◽  
Field Measurements ◽  
Hot Air ◽  
Computational Fluid Dynamics Analysis ◽  
Higher Power ◽  
Operational Data ◽  
Management Issues

The increase in the number of data centers in the last decade, combined with higher power density racks, has led to a significant increase in the associated total electricity consumption, which is compounded by cooling inefficiencies. Issues, such as hot air recirculation in the data center room environment, provide substantial challenges in thermal manageability. Three operational data centers have been studied to identify the cooling issues. Field measurements of temperature were obtained and were compared to numerical simulations to evaluate the overall thermal behavior of the data centers and to identify the thermal issues.

Strategies for effective use of exergy-based modeling of data center thermal management systems

2008 ◽  
Vol 39 (7) ◽  
pp. 1023-1029 ◽  
Author(s):  
Sara McAllister ◽  
Van P. Carey ◽  
Amip Shah ◽  
Cullen Bash ◽  
Chandrakant Patel
Keyword(s):  
Thermal Management ◽  
Data Center ◽  
Management Systems ◽  
Effective Use

Exergy Analysis of Data Center Thermal Management Systems

2008 ◽  
Vol 130 (2) ◽  
Author(s):  
Amip J. Shah ◽  
Van P. Carey ◽  
Cullen E. Bash ◽  
Chandrakant D. Patel
Keyword(s):  
Energy Efficiency ◽  
Thermal Management ◽  
Data Center ◽  
Experimental Validation ◽  
Irreversible Process ◽  
Exergy Analysis ◽  
Cooling System ◽  
Available Energy ◽  
Thermal Management System ◽  
Data Center Cooling

The modeling of recirculation patterns in air-cooled data centers is of interest to ensure adequate thermal management of computer racks at increased heat densities. Most metrics that describe recirculation are based exclusively on temperature inside the data center, and therefore fail to provide adequate information regarding the energy efficiency of the thermal infrastructure. This paper addresses this limitation through an exergy analysis of the data center thermal management system. The approach recognizes that the mixing of hot and cold streams in the data center airspace is an irreversible process and must therefore lead to a loss of exergy. Experimental validation in a test data center confirms that such an exergy-based characterization in the cold aisle reflects the same recirculation trends as suggested by traditional temperature-based metrics. Further, by extending the exergy-based model to include irreversibilities from other components of the thermal architecture, it becomes possible to quantify the amount of available energy supplied to the cooling system that is being utilized for thermal management purposes. The energy efficiency of the entire data center cooling system can then be collapsed into the single metric of net exergy loss. When evaluated against a ground state of the external ambience, this metric enables an estimate of how much of the energy emitted into the environment could potentially be harnessed in the form of useful work. Thus, this paper successfully demonstrates that the proposed exergy-based approach can provide a foundation upon which the data center cooling system can be simultaneously evaluated for thermal manageability and energy efficiency.

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