Assessment on rack intake flowrate uniformity of data center with cold aisle containment configuration

2020 ◽  
Vol 30 ◽  
pp. 101331 ◽  
Author(s):  
Wen-Xiao Chu ◽  
Rui Wang ◽  
Po-Hao Hsu ◽  
Chi-Chuan Wang
Keyword(s):  
Data Center ◽  
Cold Aisle Containment

Energy Conservation Measures of a Primary Data Center on an Academic Campus

2013 ◽  
Author(s):  
Kyosung Choo ◽  
Renan Manozzo Galante ◽  
Michael Ohadi
Keyword(s):  
Energy Conservation ◽  
Data Center ◽  
Power Saving ◽  
Primary Data ◽  
University Of Maryland ◽  
Conservation Measures ◽  
Air Temperatures ◽  
Cold Aisle Containment ◽  
The University ◽  
Energy Conservation Measures

Energy Conservation Measures (ECMs) of the primary data center at the University of Maryland are developed. Measurement and simulation are performed to validate the developed ECMs. Three ECMs — 1) Increase in the return temperature at Computer Room Air Conditionings (CRACs) 2) Cold aisle containment 3) Elimination of unnecessary CRACs — are suggested to reduce energy consumption by optimizing the thermo-fluid flow in the data center. Power savings of 12.7 kW – 17.4 kW and 14.1 kW are obtained by increasing the return air temperatures at the CRACs and performing the cold aisle containment, respectively. In addition, a power saving of 11.2 kW is obtained by turning off CRACs 3 and 8 which have an adverse effect on the data center cooling.

Improved Zonal Model for Data Center Analysis

2013 ◽  
Author(s):  
Zhihang Song ◽  
Bruce T. Murray ◽  
Bahgat Sammakia
Keyword(s):  
Thermal Analysis ◽  
Data Center ◽  
Inlet Temperature ◽  
Analysis Tool ◽  
Zonal Model ◽  
Viscous Loss ◽  
Model Predictions ◽  
Basic Power ◽  
Cold Aisle Containment ◽  
Good Agreement

A newly constructed zonal model based on the velocity propagation method (VPM) was developed as a thermal analysis tool for data centers. A viscous loss model is included, to better account for airflow momentum instead of using the basic power law method (PLM). The zonal model is implemented in the equation-based and object-oriented environment SPARK. A CFD model for a single cold aisle server room configuration was built and analyzed using the commercial software FloTHERM. Cold aisle containment was studied. Results from the zonal model, including both the plenum flow field and rack inlet temperature distributions were compared with those from the CFD package. Good agreement (within 10% average relative error) was obtained between the zonal model predictions and the CFD results. A primary goal of the study is to develop an effective real-time thermal analysis tool based on the zonal approach.

Load Capacity and Thermal Efficiency Optimization of a Research Data Center Using Computational Modeling

2015 ◽  
Author(s):  
Joseph R. H. Schaadt ◽  
Kamran Fouladi ◽  
Aaron P. Wemhoff ◽  
Joseph G. Pigeon
Keyword(s):  
Flow Rate ◽  
Data Center ◽  
Air Conditioning ◽  
Data Centers ◽  
Load Capacity ◽  
Research Data ◽  
Optimal Operating ◽  
Cold Aisle Containment ◽  
Operating Points ◽  
The Ideal

Data centers are most commonly cooled by air delivered to electronic equipment from centralized cooling systems. The research presented here is motivated by the need for strategies to improve and optimize the load capacity and thermal efficiency of data centers by using computational fluid dynamics (CFD). Here, CFD is used to model and optimize the Villanova Steel Orca Research Center (VSORC). VSORC, presently in the design stages, will provide a testing environment as well as the capability to investigate best practices and state of the art strategies including hybrid cooling, IT load distribution, density zones, and hot aisle and cold aisle containment. The results of this study will be used in the overall design and construction of the aforementioned research data center. The objective of this study is to find the optimal operating points and design layout of a data center while still meeting certain design constraints. A focus is on finding both the ideal total supply flow rate of the air conditioning units and the ideal chilled water supply temperature (CHWST) setpoint under different data center design configurations and load capacities. The total supply flow rate of the air conditioning units and the supply temperature setpoint of the chilled water system are varied as design parameters in order to systematically determine the optimal operating points. The study also examines the influence of hot aisle and cold aisle containment strategies in full containment, half containment, and no containment configurations on the determined optimal operating conditions for the modeled research data center.

Investigation of the Mechanism of Temperature Rise in a Data Center With Cold Aisle Containment

2019 ◽  
Vol 141 (4) ◽  
Author(s):  
Mingrui Zhang ◽  
Zhengwei Long ◽  
Qingsong An ◽  
Chao Sun ◽  
Hao Zhang ◽  
...  
Keyword(s):  
Temperature Rise ◽  
Data Center ◽  
Pressure Difference ◽  
Static Pressure ◽  
Dynamic Pressure ◽  
Critical Factors ◽  
Factors Affecting ◽  
Variable Space ◽  
Cold Aisle Containment ◽  
Simplified Mathematical Model

This paper theoretically investigates the relationships among factors that affect the temperature rise of server racks and experimentally tests the influence of variable space contained arrangements on the thermal performance. To express the flow and heat transfer process of cold air in servers and analyze the critical factors affecting the temperature rise, a simplified mathematical model representing servers is developed using experimental results. An experiment is conducted within a modular data center in which cold air is supplied from a raised floor. The experiment employed a variable space of cold aisle containment and measured the resulting temperature rise, as well as pressure difference of racks and other parameters, in the simplified mathematical model. By comparing the experimental results and theoretical calculation, the theoretical model is proved to be reasonable and valid. The model predicts that the critical factors affecting the temperature rise of racks consist of static and dynamic pressure difference, total pressure of the fans, geometric structure, power consumption, resistance of doors, and opening area of servers. The result shows that the factor affected by the cold aisle contained system is the static pressure, while for the dynamic pressure difference, the contained architecture has a slight positive effect. Although the average temperature rise is quite decreased in the contained system, the static pressure distribution is nonuniform. A half-contained system which reduced contained space ratio to 50% is measured to cause a 22% increase of the static pressure difference, making a more uniform temperature distribution.

Performance of Temperature Controlled Perimeter and Row-Based Cooling Systems in Open and Containment Environment

2015 ◽  
Author(s):  
Kourosh Nemati ◽  
Husam Alissa ◽  
Bahgat Sammakia
Keyword(s):  
Data Center ◽  
Heat Load ◽  
Flow Behavior ◽  
Air Flow ◽  
High Density ◽  
Computational Time ◽  
Air Cooling ◽  
Cooling Systems ◽  
Continuous Increase ◽  
Cold Aisle Containment

The continuous increase of data center usage is leading the industry to increase the load density per square foot of existing facilities. High density (HD) IT load per rack demands bringing the cooling source closer to the heat load in contrast to room level air cooling. For high density racks, the use of in-row cooling systems is becoming increasingly popular. In-row cooling can be the main source of cooling for a data center or work jointly with perimeter cooling in what is called a hybrid cooled room level system. Also, hot or cold aisle containment can be integrated with perimeter cooling and used throughout the data center to reduce the mixing of hot and cold air. Currently, there has not been much work comparing the performance of in-row cooling in open versus contained environments. The present work builds on a previous study where the interaction of perimeter and row-based cooling was evaluated for a cold-aisle containment (CAC) environment. Previously, the benefit of using row-based cooled in an aisle has not been compared with an aisle in open conditions. Here, we numerically investigate the performance of in-row coolers in both opened and cold-aisle contained environments. Groups of IT equipment that differ in air flow strength are used to provide the heat load. Empirically measured flow curves for common IT equipment are employed to provide simplified models of the IT equipment in the CFD software used. The steady state analysis includes information provided in the manufacturer’s specifications such as heat exchanger performance characteristics. The model was validated using a new data center laboratory with perimeter cooling. A single aisle of the data center is modeled to reduce the computational time, and the results are generalized. The cold aisle contains 16 racks of IT equipment distributed on both sides. In addition, the aisle contains 2 power distribution units. Full details are incorporated in the computational model. A single Liebert® CW114 CRAC unit provides the perimeter cooling in the data center. The model captures the particular air flow behavior in the cold aisle when row-based cooling is utilized. Correlations are derived to predict the ability of air cooling units to maintain set points at different air flow rates. The effect of leakage is also considered.

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