CFD Modeling of Indirect/Direct Evaporative Cooling Unit for Modular Data Center Applications

2013 ◽  
Author(s):  
Betsegaw Gebrehiwot ◽  
Nikhil Dhiman ◽  
Kasturi Rajagopalan ◽  
Dereje Agonafer ◽  
Naveen Kannan ◽  
...  
Keyword(s):  
Data Center ◽  
Cooling System ◽  
Evaporative Cooling ◽  
Cfd Modeling ◽  
Published Data ◽  
Cfd Model ◽  
Cold Air ◽  
Cooling Unit ◽  
Direct Evaporative Cooling ◽  
Modular Data

An information technology (IT) container needs to be supplied with cold air to cool IT equipment housed in it. The type of cooling system to be used depends on many factors including geographical location of the modular data center. Data centers located in regions where the climate is cold benefit from use of air-side economization (ASE) and those located in hot and dry climate benefit from use of direct and/or indirect evaporative cooling (DIEC) systems. In terms of energy saving, ASE, direct evaporative cooling (DEC) system, and indirect evaporative (IEC) systems are better than compressor based cooling systems such as computer room air conditioning (CRAC) units and air handling units (AHU). In this study, an existing DIEC unit which can also be operated in ASE mode is modeled in a computational fluid dynamics (CFD) tool. The cooling unit is intended to be used for supplying cold air to a containerized data center with specified volume flow rate, dry-bulb temperature and relative humidity. The CFD model is compared with published data of the cooling unit to see how well the CFD model represents the actual system and few design improvement ideas are tested by modifying the CFD model and running simulations. Results show that supplying air horizontally or as a downdraft to an IT container has negligible effect on the overall system. Results also show that orientation of dampers and placement of blanking panels inside the mixing chamber could affect the lifespan of air filters.

Neural Network Based Bin Analysis for Indirect/Direct Evaporative Cooling of Modular Data Centers

2018 ◽  
Author(s):  
Abhishek Walekar ◽  
Ashwin Siddarth ◽  
Abhishek Guhe ◽  
Nikita Sukthankar ◽  
Dereje Agonafer
Keyword(s):  
Neural Network ◽  
Data Center ◽  
Climatic Condition ◽  
Data Centers ◽  
Evaporative Cooling ◽  
Ann Model ◽  
Cooling Mode ◽  
Direct Evaporative Cooling ◽  
Modular Data ◽  
Psychrometric Chart

With an increase in the need for energy efficient data centers, a lot of research is being done to maximize the use of Air Side Economizers (ASEs), Direct Evaporative Cooling (DEC), Indirect Evaporative Cooling (IEC) and multistage Indirect/Direct Evaporative Cooling (I/DEC). The selection of cooling configurations installed in modular cooling units is based on empirical/analytical studies and domain knowledge that fail to account for the nonlinearities present in an operational data center. In addition to the ambient conditions, the attainable cold aisle temperature and humidity is also a function of the control strategy and the cooling setpoints in the data center. The primary objective of this study is to use Artificial Neural Network (ANN) modelling and Psychrometric bin analysis to assess the applicability of various cooling modes to a climatic condition. Training dataset for the ANN model is logged from the monitoring sensor array of a modular data center laboratory with an I/DEC module. The data-driven ANN model is utilized for predicting the cold aisle humidity and temperatures for different modes of cooling. Based on the predicted cold aisle temperature and humidity, cold aisle envelopes are represented on a psychrometric chart to evaluate the applicability of each cooling mode to the territorial climatic condition. Subsequently, outside air conditions favorable to each cooling mode in achieving cold aisle conditions, within the ASHRAE recommended environmental envelope, is also visualized on a psychrometric chart. Control strategies and opportunities to optimize the cooling system are discussed.

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.

An experimental evaluation of indirect direct evaporative cooling unit for hot climate

2021 ◽  
Vol 24 (3/4) ◽  
pp. 237
Author(s):  
Bourhan Tashtoush ◽  
Nelson Chilengwe ◽  
Mohamed Musthafa ◽  
Yousef Al Horr
Keyword(s):  
Experimental Evaluation ◽  
Evaporative Cooling ◽  
Hot Climate ◽  
Cooling Unit ◽  
Direct Evaporative Cooling

Steady State and Transient Comparison of Perimeter and Row-Based Cooling Employing Controlled Cooling Curves

2015 ◽  
Author(s):  
Husam A. Alissa ◽  
Kourosh Nemati ◽  
Bahgat Sammakia ◽  
Alfonso Ortega ◽  
David King ◽  
...  
Keyword(s):  
Steady State ◽  
Heat Exchanger ◽  
Data Center ◽  
Cooling System ◽  
Air Flow ◽  
Thermal Inertia ◽  
Small Data ◽  
Cfd Model ◽  
Controlled Cooling ◽  
Failure Scenario

The perpetual increase of data processing has led to an ever increasing need for power and in turn to greater cooling challenges. High density (HD) IT loads have necessitated more aggressive and direct approaches of cooling as opposed to the legacy approach by the utilization of row-based cooling. In-row cooler systems are placed between the racks aligned with row orientation; they offer cool air to the IT equipment more directly and effectively. Following a horizontal airflow pattern and typically occupying 50% of a rack’s width; in-row cooling can be the main source of cooling in the data center or can work jointly with perimeter cooling. Another important development is the use of containment systems since they reduce mixing of hot and cold air in the facility. Both in-row technology and containment can be combined to form a very effective cooling solution for HD data centers. This current study numerically investigates the behavior of in-row coolers in cold aisle containment (CAC) vs. perimeter cooling scheme. Also, we address the steady state performance for both systems, this includes manufacturer’s specifications such as heat exchanger performance and cooling coil capacity. A brief failure scenario is then run, and duration of ride through time in the case of row-based cooling system failure is compared to raised floor perimeter cooling with containment. Non-raised floor cooling schemes will reduce the air volumetric storage of the whole facility (in this small data center cell it is about a 20% reduction). Also, the varying thermal inertia between the typical in-row and perimeter cooling units is of decisive importance. The CFD model is validated using a new data center laboratory at Binghamton University with perimeter cooling. This data center consists of one main Liebert cooling unit, 46 perforated tiles with 22% open area, 40 racks distributed on three main cold aisles C and D. A computational slice is taken of the data center to generalize results. Cold aisle C consists of 16 rack and 18 perforated tiles with containment installed. In-row coolers are then added to the CFD model. Fixed IT load is maintained throughout the simulation and steady state comparisons are built between the legacy and row-based cooling schemes. An empirically obtained flow curve method is used to capture the flow-pressure correlation for flow devices. Performance scenarios were parametrically analyzed for the following cases: (a) Perimeter cooling in CAC, (b) In-row cooling in CAC. Results showed that in-row coolers increased the efficiency of supply air flow utilization since the floor leakage was eliminated, and higher pressure build up in CAC were observed. This reduced the rack recirculation when compared to the perimeter cooled case. However, the heat exchanger size demonstrated the limitation of the in-row to maintain controlled set point at increased air flow conditions. For the pump failure scenario, experimental data provided by Emerson labs were used to capture the thermal inertia effect of the cooling coils for in-row and perimeter unit, perimeter cooled system proved to have longer ride through time.

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.

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