Improving Cooling Efficiency by Using Mixed Tiles to Control Airflow Uniformity of Perforated Tiles in a Data Center Model

2017 ◽  
Author(s):  
Long Phan ◽  
Sadhana Bhusal ◽  
Cheng-Xian Lin
Keyword(s):  
Power Density ◽  
Simulation Study ◽  
Data Center ◽  
Data Centers ◽  
Industrial Sector ◽  
Cooling Efficiency ◽  
Direct Impact ◽  
Flow Through ◽  
Energy Consumptions ◽  
Heat Loads

Data centers in recent years have grown so fast so that their energy consumptions become a big issue in the industrial sector. One of the strategies to make better use of energy in data centers is to improve the efficiency in cooling. As the load density in data centers increases dramatically over the years, the number of computer room air handlers (CRAHs) are also increased to accommodate the high cooling demands. However, the number of CRAH units and their layouts really affect the air flow through the perforated tiles. Non-uniform airflow distributions in the perorated tiles in the cold aisles cause inefficient cooling of all the servers mounted in racks in data centers. Application of necessary strategies to minimize airflow non-uniformity is therefore very important because of its direct impact on the power density capacity. In this paper, a simulation study to examine how computer room air handler (CRAH) positions, the number of operating units, and tile types affect the airflow uniformity in selected data center models. Also, the placement of mixed tiles in cold aisles to regulate the airflow through the perforated tiles to accommodate greater heat loads from server racks is evaluated.

Introducing Energy Efficiency Metrics for Server and Data Centers

2011 ◽  
Author(s):  
Abdlmonem H. Beitelmal ◽  
Drazen Fabris
Keyword(s):  
Energy Efficiency ◽  
Data Center ◽  
Data Centers ◽  
Cooling Efficiency ◽  
Idle Power ◽  
Relevant Variables ◽  
The Cost ◽  
Evaluation Of Data

New servers and data center metrics are introduced to facilitate proper evaluation of data centers power and cooling efficiency. These metrics will be used to help reduce the cost of operation and to provision data centers cooling resources. The most relevant variables for these metrics are identified and they are: the total facility power, the servers’ idle power, the average servers’ utilization, the cooling resources power and the total IT equipment power. These metrics can be used to characterize and classify servers and data centers performance and energy efficiency regardless of their size and location.

Research on Intelligent Air Conditioning System of Data Center

2014 ◽  
Vol 602-605 ◽  
pp. 928-932
Author(s):  
Min Li ◽  
Yun Wang ◽  
Zheng Qian Feng ◽  
Wang Li
Keyword(s):  
Heat Exchange ◽  
Energy Saving ◽  
Data Center ◽  
Air Conditioning ◽  
Data Centers ◽  
Cooling Efficiency ◽  
Exchange System ◽  
Air Conditioning System ◽  
Running Time ◽  
Heat Exchange System

By studying the energy-saving technologies of air-conditioning system in data centers, we designed a intelligent air conditioning system, improved the cooling efficiency of air conditioning system through a reasonable set of hot and cold aisles, reduced the running time of HVAC by using the intelligent heat exchange system, an provided a reference for energy saving research of air conditioning system of data centers.

Optimization of Data Center Cooling Efficiency Using Reduced Order Flow Modeling Within a Flow Network Modeling Approach

2014 ◽  
Author(s):  
K. Fouladi ◽  
A. P. Wemhoff ◽  
L. Silva-Llanca ◽  
A. Ortega
Keyword(s):  
Thermal Efficiency ◽  
Data Center ◽  
Data Centers ◽  
Network Models ◽  
Cooling Efficiency ◽  
Exergy Destruction ◽  
Cfd Simulations ◽  
Flow Network ◽  
Reduced Order ◽  
Efficiency Optimization

Much of the energy use by data centers is attributed to the energy needed to cool the data centers. Thus, improving the cooling efficiency and thermal management of data centers can translate to direct and significant economic benefits. However, data centers are complex systems containing a significant number of components or sub-systems (e.g., servers, fans, pumps, and heat exchangers) that must be considered in any synergistic data center thermal efficiency optimization effort. The Villanova Thermodynamic Analysis of Systems (VTAS) is a flow network tool for performance prediction and design optimization of data centers. VTAS models the thermodynamics, fluid mechanics, and heat transfer inherent to an entire data center system, including contributions by individual servers, the data center airspace, and the HVAC components. VTAS can be employed to identify the optimal cooling strategy among various alternatives by computing the exergy destruction of the overall data center system and the various components in the system for each alternative. Exergy or “available energy” has been used to identify components and wasteful practices that contribute significantly in cooling inefficiency of data centers including room air recirculation — premature mixing of hot and cold air streams in a data center. Flow network models are inadequate in accurately predicting the magnitude of airflow exergy destruction due to simplifying assumptions and the three-dimensional nature of the flow pattern in the room. On the other hand, CFD simulations are time consuming, making them impractical for iterative-based design optimization approaches. In this paper we demonstrate a hybrid strategy, in which a proper orthogonal decomposition (POD) based airflow modeling approach developed from CFD simulation data is implemented in VTAS for predicting the room airflow exergy destruction. The reduced order POD tool in VTAS provides higher accuracy than 1-D flow network models and is computationally more efficient than 3-D CFD simulations. The present VTAS – POD tool has been applied to a data center cell to illustrate the use of exergy destruction minimization as an objective function for data center thermal efficiency optimization.

Data Center Workload Placement for Energy Efficiency

2007 ◽  
Author(s):  
Cullen Bash ◽  
George Forman
Keyword(s):  
Energy Efficiency ◽  
Heat Production ◽  
Data Center ◽  
Data Centers ◽  
Real Data ◽  
Cooling Efficiency ◽  
The Past ◽  
Computer Power

Data center costs for computer power and cooling have been steadily increasing over the past decade. Much work has been done in recent years on understanding how to improve the delivery of cooling resources to IT equipment in data centers, but little attention has been paid to the optimization of heat production by considering the placement of application workload. Because certain physical locations inside the data center are more efficient to cool than others, this suggests that allocating heavy computational workloads onto those servers that are in more efficient places might bring substantial savings. This paper explores this issue by introducing a workload placement metric that considers the cooling efficiency of the environment. Additionally, results from a set of experiments that utilize this metric in a thermally isolated portion of a real data center are described. The results show that the potential savings is substantial and that further work in this area is needed to exploit the savings opportunity.

Multi-Scale Modeling of High Power Density Data Centers

2003 ◽  
Author(s):  
Jeffrey D. Rambo ◽  
Yogendra K. Joshi
Keyword(s):  
Power Density ◽  
Flow Rate ◽  
High Power ◽  
Data Center ◽  
Data Centers ◽  
High Power Density ◽  
Length Scales ◽  
Density Data ◽  
Multi Scale ◽  
The Cost

Data center facilities, which house thousands of servers, storage devices and computing hardware, arranged in 2 meter high racks are providing many thermal challenges. Each rack can dissipate 10–15 kW, and with facilities as large as tens of thousands of square feet, the net power dissipated is typically on the order of several MW. The cost to power these facilities alone can be millions of dollars a year, with the cost to provide adequate cooling not far behind. Significant savings can be realized for the end user by improved design methodology of these high power density data centers. The fundamental need for improved characterization is motivated by inadequacies of simple energy balances to identify local ‘hot spots’ and ultimately provide a reliable modeling framework by which the data centers of the future can be designed. Recent attempts in computational fluid dynamics (CFD) modeling of data centers have been based around a simple rack model, either as a uniform heat generator or specified temperature rise across the rack. This desensitizes the solution to variations of heat load and corresponding flow rate needed to cool the servers throughout the rack. Heat generated at the smaller scales (the chip level) produces changes in the larger length scales of the data center. Accurate simulations of these facilities should attempt to resolve the range of length scales present. In this paper, a multi-scale model where each rack is subdivided into a series of sub-models to better mimic the behavior of individual servers inside the data center is proposed. A Reynolds-averaged Navier-Stokes CFD model of a 110 m2 (1,200 ft2) representative data center with the raised floor cooling scheme was constructed around this multi-scale rack model. Each of the 28 racks dissipated 4.23 kW, giving the data center a power density of 1076 W/m2 (100 W/ft2) based on total floor space. Parametric studies of varying heat loads within the rack and throughout the data center were performed to better characterize the interactions of the sub-rack scale heat generation and the data center. Major results include 1) the presence of a nonlinear thermal response in the upper portion of each rack due to recirculation effects and 2) significant changes in the surrounding racks (up to 10% increase in maximum temperature) observed in response to changes in rack flow rate (50% decrease).

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.

Data Center Cooling Efficiency With Simulation-Based Optimization

2015 ◽  
Author(s):  
Laurent M. Billet ◽  
Christopher M. Healey ◽  
James W. VanGilder ◽  
Zachary M. Pardey
Keyword(s):  
Energy Consumption ◽  
Data Center ◽  
Data Centers ◽  
Real Life ◽  
Economic Importance ◽  
Cooling Efficiency ◽  
Simulation Based ◽  
Data Center Cooling ◽  
Efficient Control

The efficient control of cooling for data centers is an issue of broad economic importance due to the significant energy consumption of data centers. Many solutions attempt to optimize the control of the cooling equipment with temperature, pressure, or airflow sensors. We propose a simulation-based approach to optimize the cooling energy consumption and show how this approach can be implemented with simple power-consumption models. We also provide a real-life case study to demonstrate how energy saving cooling setpoints can be found using calibrated simulations and smooth metamodels of the system.

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.

Distributed Leakage Flow in Raised-Floor Data Centers

2005 ◽  
Author(s):  
Amir Radmehr ◽  
Roger R. Schmidt ◽  
Kailash C. Karki ◽  
Suhas V. Patankar
Keyword(s):  
Computational Model ◽  
Data Center ◽  
Data Centers ◽  
Quantitative Relationship ◽  
Leakage Flow ◽  
Typical Data ◽  
Leakage Area ◽  
Flow Through ◽  
Cooling Air ◽  
Plenum Pressure

In raised-floor data centers, distributed leakage flow—the airflow through seams between panels on the raised floor—reduces the amount of cooling air available at the inlets of the computer equipment. This airflow must be known to determine the total cooling air requirement in a data center. The amount of distributed leakage flow depends on the area of the seams and the plenum pressure, which, in turn, depends on the amount of airflow into the plenum and the total open area (combined area of perforated tiles, cutouts, and seams between panels) on the raised floor. The goal of this study is to outline a procedure to measure leakage flow, to provide data on the amount of the distributed leakage flow, and to show the quantitative relationship between the leakage flow and the leakage area. It also uses a computational model to calculate the distributed leakage flow, the flow through perforated tiles, and the plenum pressure. The results obtained from the model are verified using the measurements. Such a model can be used for design and maintenance of data centers. The measurements show that the leakage flow in a typical data center is between 5–15% of the available cooling air. The measured quantities were used to estimate the area of the seams; for this data center, it was found to be 0.35% of the floor area. The computational model represents the actual physical scenarios very well. The discrepancy between the calculated and measured values of leakage flow, flow through perforated tiles, and plenum pressure is less than 10%.

Optimization of Enclosed Aisle Data Centers Using Bypass Recirculation

2012 ◽  
Vol 134 (2) ◽  
Author(s):  
Dustin W. Demetriou ◽  
H. Ezzat Khalifa
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Energy Consumption ◽  
Data Center ◽  
Data Centers ◽  
Total Power ◽  
Total Energy Consumption ◽  
Air Conditioners ◽  
Data Center Cooling ◽  
Flow Through

The work presented in this paper describes a simplified thermodynamic model that can be used for exploring optimization possibilities in air-cooled data centers. The model is used to evaluate parametrically the total energy consumption of the data center cooling infrastructure for data centers that utilize aisle containment. The analysis highlights the importance of reducing the total power required for moving the air within the computer room air conditioners (CRACs), the plenum, and the servers, rather than focusing primarily or exclusively on reducing the refrigeration system’s power consumption. In addition, the benefits of introducing a bypass recirculation branch in enclosed aisle configurations are shown. The analysis shows a potential for as much as a 60% savings in cooling infrastructure energy consumption by utilizing an optimized enclosed aisle configuration with bypass recirculation, instead of a traditional enclosed aisle in which all the data center exhaust is forced to flow through the CRACs. Furthermore, computational fluid dynamics is used to evaluate practical arrangements for implementing bypass recirculation in raised floor data centers. A configuration where bypass tiles, with controllable low-lift fans, are placed close to the discharge of CRACs results in increased mixing and is shown to be a suitable method for providing nearly thermally uniform conditions to the inlet of the servers in an enclosed cold aisle. Other configurations of bypass implementation are also discussed and explored.

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