Predictive Model Development and Validation for Raised Floor Plenum Data Center

2020 ◽  
Vol 142 (2) ◽  
Author(s):  
Yogesh Fulpagare ◽  
Atul Bhargav ◽  
Yogendra Joshi
Keyword(s):  
Data Center ◽  
Data Centers ◽  
Model Development ◽  
Operating Conditions ◽  
System Level ◽  
Predictive Tool ◽  
Air Temperatures ◽  
Computational Fluid Dynamics Cfd ◽  
The Cost ◽  
Development And Validation

Abstract With the explosion in digital traffic, the number of data centers as well as demands on each data center, continue to increase. Concomitantly, the cost (and environmental impact) of energy expended in the thermal management of these data centers is of concern to operators in particular, and society in general. In the absence of physics-based control algorithms, computer room air conditioning (CRAC) units are typically operated through conservatively predetermined set points, resulting in suboptimal energy consumption. For a more optimal control algorithm, predictive capabilities are needed. In this paper, we develop a data-informed, experimentally validated and computationally inexpensive system level predictive tool that can forecast data center behavior for a broad range of operating conditions. We have tested this model on experiments as well as on (experimentally) validated transient computational fluid dynamics (CFD) simulations for two different data center design configurations. The validated model can accurately forecast temperatures and air flows in a data center (including the rack air temperatures) for 10–15 min into the future. Once integrated with control aspects, we expect that this model can form an important building block in a future intelligent, increasingly automated data center environment management systems.

Influence of Experimental Uncertainty on Prediction of Holistic Multi-Scale Data Center Energy Efficiency

2011 ◽  
Author(s):  
Thomas J. Breen ◽  
Ed J. Walsh ◽  
Jeff Punch ◽  
Amip J. Shah ◽  
Niru Kumari ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Experimental Analysis ◽  
Data Center ◽  
Data Centers ◽  
Operating Conditions ◽  
Coefficient Of Performance ◽  
System Level ◽  
Scale Model ◽  
Multi Scale ◽  
Scale Data

As the energy footprint of data centers continues to increase, models that allow for “what-if” simulations of different data center design and management paradigms will be important. Prior work by the authors has described a multi-scale energy efficiency model that allows for evaluating the coefficient of performance of the data center ensemble (COPGrand), and demonstrated the utility of such a model for purposes of choosing operational set-points and evaluating design trade-offs. However, experimental validation of these models poses a challenge because of the complexity involved with tailoring such a model for implementation to legacy data centers, with shared infrastructure and limited control over IT workload. Further, test facilities with dummy heat loads or artificial racks in lieu of IT equipment generally have limited utility in validating end-to-end models owing to the inability of such loads to mimic phenomena such as fan scalability, etc. In this work, we describe the experimental analysis conducted in a special test chamber and data center facility. The chamber, focusing on system level effects, is loaded with an actual IT rack, and a compressor delivers chilled air to the chamber at a preset temperature. By varying the load in the IT rack as well as the air delivery parameters — such as flow rate, supply temperature, etc. — a setup which simulates the system level of a data center is created. Experimental tests within a live data center facility are also conducted where the operating conditions of the cooling infrastructure are monitored — such as fluid temperatures, flow rates, etc. — and can be analyzed to determine effects such as air flow recirculation, heat exchanger performance, etc. Using the experimental data a multi-scale model configuration emulating the data center can be defined. We compare the results from such experimental analysis to a multi-scale energy efficiency model of the data center, and discuss the accuracies as well as inaccuracies within such a model. Difficulties encountered in the experimental work are discussed. The paper concludes by discussing areas for improvement in such modeling and experimental evaluation. Further validation of the complete multi-scale data center energy model is planned.

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.

scholarly journals A Comparative CFD Study of Two Air Distribution Systems with Hot Aisle Containment in High-Density Data Centers

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 6147
Author(s):  
Jinkyun Cho ◽  
Jesang Woo ◽  
Beungyong Park ◽  
Taesub Lim
Keyword(s):  
Thermal Performance ◽  
Data Center ◽  
Distribution Systems ◽  
Data Centers ◽  
High Density ◽  
Operating Conditions ◽  
Air Distribution ◽  
Density Data ◽  
Computational Fluid Dynamics Analysis ◽  
Hard Floor

Removing heat from high-density information technology (IT) equipment is essential for data centers. Maintaining the proper operating environment for IT equipment can be expensive. Rising energy cost and energy consumption has prompted data centers to consider hot aisle and cold aisle containment strategies, which can improve the energy efficiency and maintain the recommended level of inlet air temperature to IT equipment. It can also resolve hot spots in traditional uncontained data centers to some degree. This study analyzes the IT environment of the hot aisle containment (HAC) system, which has been considered an essential solution for high-density data centers. The thermal performance was analyzed for an IT server room with HAC in a reference data center. Computational fluid dynamics analysis was conducted to compare the operating performances of the cooling air distribution systems applied to the raised and hard floors and to examine the difference in the IT environment between the server rooms. Regarding operating conditions, the thermal performances in a state wherein the cooling system operated normally and another wherein one unit had failed were compared. The thermal performance of each alternative was evaluated by comparing the temperature distribution, airflow distribution, inlet air temperatures of the server racks, and recirculation ratio from the outlet to the inlet. In conclusion, the HAC system with a raised floor has higher cooling efficiency than that with a hard floor. The HAC with a raised floor over a hard floor can improve the air distribution efficiency by 28%. This corresponds to 40% reduction in the recirculation ratio for more than 20% of the normal cooling conditions. The main contribution of this paper is that it realistically implements the effectiveness of the existing theoretical comparison of the HAC system by developing an accurate numerical model of a data center with a high-density fifth-generation (5G) environment and applying the operating conditions.

Raised Floor Hybrid Cooled Data Center: Effect on Rack Inlet Air Temperatures When In Row Cooling Units are Installed Between the Racks

2015 ◽  
Author(s):  
Tianyi Gao ◽  
James Geer ◽  
Russell Tipton ◽  
Bruce Murray ◽  
Bahgat G. Sammakia ◽  
...  
Keyword(s):  
Flow Rate ◽  
Data Center ◽  
Heat Load ◽  
Data Centers ◽  
Cooling System ◽  
Air Flow ◽  
Inlet Temperature ◽  
Air Flow Rate ◽  
Air Temperatures ◽  
Cooling Unit

The heat dissipated by high performance IT equipment such as servers and switches in data centers is increasing rapidly, which makes the thermal management even more challenging. IT equipment is typically designed to operate at a rack inlet air temperature ranging between 10 °C and 35 °C. The newest published environmental standards for operating IT equipment proposed by ASHARE specify a long term recommended dry bulb IT air inlet temperature range as 18°C to 27°C. In terms of the short term specification, the largest allowable inlet temperature range to operate at is between 5°C and 45°C. Failure in maintaining these specifications will lead to significantly detrimental impacts to the performance and reliability of these electronic devices. Thus, understanding the cooling system is of paramount importance for the design and operation of data centers. In this paper, a hybrid cooling system is numerically modeled and investigated. The numerical modeling is conducted using a commercial computational fluid dynamics (CFD) code. The hybrid cooling strategy is specified by mounting the in row cooling units between the server racks to assist the raised floor air cooling. The effect of several input variables, including rack heat load and heat density, rack air flow rate, in row cooling unit operating cooling fluid flow rate and temperature, in row coil effectiveness, centralized cooling unit supply air flow rate, non-uniformity in rack heat load, and raised floor height are studied parametrically. Their detailed effects on the rack inlet air temperatures and the in row cooler performance are presented. The modeling results and corresponding analyses are used to develop general installation and operation guidance for the in row cooler strategy of a data center.

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.

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.

Achieving Ultra-Low Energy Consumption in Data Center Mechanical Systems Through Indirect Airside Economization

2016 ◽  
Author(s):  
Dan Comperchio ◽  
Sameer Behere
Keyword(s):  
Information Technology ◽  
Energy Consumption ◽  
Data Center ◽  
Energy Use ◽  
Data Centers ◽  
Mechanical Systems ◽  
Electrical Energy ◽  
Vapor Compression ◽  
Ambient Conditions ◽  
Air Temperatures

Data center cooling systems have long been burdened by high levels of redundancy requirements, resulting in inefficient system designs to satisfy a risk-adverse operating environment. As attitudes, technologies, and sustainability awareness change within the industry, data centers are beginning to realize higher levels of energy efficiency without sacrificing operational security. By exploiting the increased temperature and humidity tolerances of the information technology equipment (ITE), data center mechanical systems can leverage ambient conditions to operate in economization mode for increased times during the year. Economization provides one of the largest methodologies for data centers to reduce their energy consumption and carbon footprint. As outside air temperatures and conditions become more favorable for cooling the data center, mechanical cooling through vapor-compression cycles is reduced or entirely eliminated. One favorable method for utilizing low outside air temperatures without sacrificing indoor air quality is through deploying rotary heat wheels to transfer heat between the data center return air and outside air without introducing outside air into the white space. A metal corrugated wheel is rotated through two opposing airstreams with varying thermal gradients to provide a net cooling effect at significantly reduced electrical energy over traditional mechanical cooling topologies. To further extend the impacts of economization, data centers are also able to significantly raise operating temperatures beyond what is traditionally found in comfort cooling applications. The increase in the dry bulb temperature provided to the inlet of the information technology equipment, as well as an elevated temperature rise across the equipment significantly reduces the energy use within a data center.

Development of a Technique to Measure Deliquescent Relative Humidity of Particulate Contaminants and Determination of the Operating Relative Humidity of a Data Center

2019 ◽  
Author(s):  
Jimil M. Shah ◽  
Roshan Anand ◽  
Satyam Saini ◽  
Rawhan Cyriac ◽  
Dereje Agonafer ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Relative Humidity ◽  
Data Center ◽  
Printed Circuit Boards ◽  
Data Centers ◽  
Operating Conditions ◽  
Test Method ◽  
Dust Particles ◽  
Circuit Boards ◽  
Printed Circuit

Abstract A remarkable amount of data center energy is consumed in eliminating the heat generated by the IT equipment to maintain and ensure safe operating conditions and optimum performance. The installation of Airside Economizers, while very energy efficient, bears the risk of particulate contamination in data centers, hence, deteriorating the reliability of IT equipment. When RH in data centers exceeds the deliquescent relative humidity (DRH) of salts or accumulated particulate matter, it absorbs moisture, becomes wet and subsequently leads to electrical short circuiting because of degraded surface insulation resistance between the closely spaced features on printed circuit boards. Another concern with this type of failure is the absence of evidence that hinders the process of evaluation and rectification. Therefore, it is imperative to develop a practical test method to determine the DRH value of the accumulated particulate matter found on PCBs (Printed Circuit Boards). This research is a first attempt to develop an experimental technique to measure the DRH of dust particles by logging the leakage current versus RH% (Relative Humidity percentage) for the particulate matter dispensed on an interdigitated comb coupon. To validate this methodology, the DRH of pure salts like MgCl2, NH4NO3 and NaCl is determined and their results are then compared with their published values. This methodology was therefore implemented to help lay a modus operandi of establishing the limiting value or an effective relative humidity envelope to be maintained at a real-world data center facility situated in Dallas industrial area for its continuous and reliable operation.

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).

Transient Analysis for Contained-Cold-Aisle Data Center

2012 ◽  
Author(s):  
Sami A. Alkharabsheh ◽  
Mahmoud Ibrahim ◽  
Saurabh Shrivastava ◽  
Roger Schmidt ◽  
Bahgat Sammakia
Keyword(s):  
Steady State ◽  
Temperature Distribution ◽  
Data Center ◽  
Transient Analysis ◽  
Operating Conditions ◽  
Cfd Modeling ◽  
Base Case ◽  
Air Temperatures ◽  
Air Supply ◽  
Final Steady State

The objective of this paper is to conduct a transient analysis for a contained-cold-aisle data center using Computational Fluid Dynamics (CFD) modeling. Containing the cold aisle reduces the inherent challenges of predictability and energy consumption of data center cooling systems by separating the hot and cold air streams. Transient analysis is crucial to further show the benefits of this methodology and investigate the potential drawbacks. In this work, we investigate the effect of variable power and flow rate in time on a raised-floor data center with specific geometry. First, a base case numerical model is established. Then, we conduct a transient analysis for the uncontained base case and the three containment configurations. The containment configurations under consideration are ceiling-only, doors-only, and fully-contained cold aisle. We hold a comparison between different geometrical configurations of the containment system under certain transient operating conditions. Computer Room Air Conditioning (CRAC) failure and change in IT-demand are chosen to represent conventional transient scenarios in a data center. The transient analysis shows overshoots of cabinet inlet air temperatures beyond the final steady state, which cannot predicted through a simple steady state analysis. In addition, the uniform temperature distribution inside the cold aisle is affected by the change in air supply and level of containment. The temperature distribution in the cold aisle changes with time. Guidelines can be recommended based on the conclusion of this study.

Sign in / Sign up

Export Citation Format

Share Document