Cold Aisle Research Articles

An experimental and theoretical investigation of the extent of bypass air within data centres employing aisle containment, and its impact on power consumption

A combination of laboratory experiments and a system model are used to carry out the first investigation into the potential for cold air to bypass IT equipment within data centres (DCs) employing aisle containment, and the effect of this bypass on DC electricity consumption. The laboratory experiments involved applying a differential pressure across commercially available server racks and aisle containment systems and measuring the resulting air flow. The potential to minimise bypass by sealing leakage paths and redesigning racks was investigated and quantified experimentally. A new system model is developed using a combination of manufacturer data, empirical relationships and experimental results to predict the impact of bypass on the power consumption of the various components of a DC’s cooling infrastructure. The results show that, at typical cold aisle pressures, as much as 20% of the supplied air may bypass servers by finding alternate paths through the server rack itself. This increases the required flow rate from air conditioning units (ACUs). The system model predicts that: (i) practical measures undertaken to reduce this bypass could reduce total power consumption by up to 8.8% and (ii) excessive pressure differentials across the containment system could also increase power consumption, by up to 16%.

CFD investigations of data centers’ thermal performance for different configurations of CRACs units and aisles separation

The thermal performance of data centers is numerically studied for different configurations of computer room air conditioning (CRAC) units and physical separations of cold and hot aisles. Temperature distribution, air flow characteristics and thermal management of data centers racks array are predicted and evaluated for the different arrangements. Measureable performance indices: supply/return heat index (SHI/RHI), return temperature index (RTI) and return cooling index (RCI) are used to measure the thermal management effectiveness of data center racks. The results showed that: (i) hot air recirculation, cold air bypass and the measurable performance indices of the racks strongly depend on the racks location in the racks array, (ii) the CRACs units layout affects the thermal managements of the racks array especially the sides and middle racks in the array, and (iii) using cold aisle containments enhances the thermal performance of the data center.

Numerical investigation and parametric study for thermal and energy management enhancements in data centers' buildings

A CFD numerical investigation of air flow and temperature distribution in data centers is presented for different operating and geometric conditions. Numerical experiments were conducted to parametrically study the effects of perforated tiles opening ratio, data center power density and locations of Computer Room Air Conditioning (CRAC) on the data center performance. Temperature distribution especially hot spot points, air flow characteristics particularly air recirculation and bypass and thermal management in data centers are evaluated in terms of the measureable overall performance parameters: supply/return heat indices (SHI/RHI), return temperature indices (RTI) and return cooling indices (RCI). Techniques of using cold aisle containments for enhancing the cooling effectiveness of data centers are investigated and evaluated. The results showed that (i) increasing the perforation ratio of perforated tails decreases the recirculation and bypass of air flow around the rack, (ii) increasing data centers' power density and supplied air flow rates increases the air bypass and air re-circulation, (iii) changing the spacing between the CRAC units and cold aisle slightly changes of air recirculation and bypass around the racks, and (iv) using appropriate cold aisle containment improves the performance of cooling of data centers, especially at high power density.

Experimental investigations of thermal managements solutions in data centers buildings for different arrangements of cold aisles containments

Cold aisles containments are used in data centers buildings to improve the thermal managements of the IT servers. In the present study, an experimental investigation of air flow and thermal management of data center buildings is conducted for different arrangements of cold aisles containments. A scaled physical model simulating real data centers is designed using scale modeling theory and constructed for the sake of the present experimental work. The data center scaled model accommodate a row of three racks; each rack included four servers for testing purposes. Three arrangements of cold aisles are tested: (i) free open cold aisle, (ii) semi-enclosed cold aisles where the aisles are enclosed from the sides, and (iii) full enclosed cold aisles, where the aisles are enclosed from sides and top. Front and rear racks temperatures profile, servers temperatures and performance measuring parameters Supply/Return Heat Index (SHI/RHI) are used to evaluate the thermal management/performance of the data centers racks. Experiments were conducted at different racks power densities. The results showed that (i) increasing data centers power density and supplied air flow rates improves SHI but increases servers temperature, (ii) using semi-enclosed cold aisles relatively improve the thermal performance of the data centers, (iii) using full enclosed cold aisles dramatically improve the thermal performance of the data center servers, and (vi) the percentage of enhancement in data centers performance due to using cold aisle containments dramatically increases with increasing the power density.

Investigation of Airflow Pattern of a Typical Data Center by CFD Simulation

Airflow pattern in a data center impacts the cooling effectiveness of the air-conditioning systems significantly, and hence impacts the energy efficiency of the whole data center. This paper presented investigation of the airflow pattern for a typical data center by CFD simulation. An under-floor air supplying system was used in the targeted data center. Cooling performance of the original and three more modified airflow pattern was simulated by CFD software. In optimizing the cooling efficiency, the measurements including blanking of the unused rack space, adding vertical partitions, and partly enclosing cold aisles were adopted to modify the original airflow pattern. The cooling performance was compared by indices like Supply Heat Index (SHI), Return Heat Index (RHI), Rack Cooling Index (RCI) and Return Temperature Index (RTI). The results indicated that partly enclosing cold aisles got most significant improvement in cooling performance. The supply air temperature could be increased by 3°C. While for the index itself, RTI was found not appropriate in evaluating of cold air by-pass or hot air re-circulation in some cases.

Airflow Management in a Contained Cold Aisle Using Active Fan Tiles for Energy Efficient Data-Center Operation

Generally, passive perforated tiles are used in a data center and the supplied airflow rate is underprovisioned; thus, the balance of the server air requirement is met by the hot air in the room, resulting in higher server inlet temperatures. Full provisioning of the supplied airflow rate and containing the cold aisle is expected to minimize the hot air leakage in the cold aisle, resulting in uniform and lower server inlet temperatures. Thus, the supply air temperature can be raised, resulting in energy savings at the chiller plant. Supplying extra air can be achieved using active perforated tiles, having multiple fans installed on them. In this paper, the underprovisioned case using passive tiles and the fully provisioned case using active tiles are investigated for both open and contained aisle conditions. Thermal field measurements suggest lower and uniform server inlet temperatures for the case with contained aisle as compared to open aisle and for the fully provisioned case using active tiles as compared to the underprovisioned case using passive tiles. System-level energy calculations suggests that containing the cold aisle results in lower (improved) power usage effectiveness (PUE); however, use of active tiles does not seem to improve the PUE.

Improvements of Airflow Distribution in a Container Data Center

Abstract The present study aims at improvements of the airflow and temperature distribution in a container data center. Simulation is carried out based on a raised floor design. It is found that the height of raised floor casts significant impact on the flow distribution. Generally, the flow rate of the perforated tile near the entrance region of CRAC unit is lower than that of the rear part of the perforated tile. The mal-distribution becomes even more severe when the height of the raised floor is reduced. The mal-distribution can be significantly improved using a smaller opening perforated tile but it also gives rise to higher pumping power and impairs the effective flow rate from CRAC. Hence, a variable opening design with a larger opening near the CRAC outlet, followed subsequently with smaller opening perforated tiles, the mal-distribution can be eliminated without additional pumping power. For improvement of the airflow/temperature distribution into the rack, we propose a drawer-type rack which can increase the effective hot aisle space and reducing the cold aisle space. Through this design, hot air recirculation and cold air bypass will be significantly reduced. As a result, the rack maximum inlet temperature of drawer-type rack can be reduced as much as 13.3 °C when compared with the traditional one.

Measurement of Air Flow Rate Sensitivity to the Differential Pressure Across a Server Rack in a Data Center

Presently, air cooling is the most common method of thermal management in data centers. In a data center, multiple servers are housed in a rack, and the racks are arranged in rows to allow cold air entry from the front (cold aisle) and hot air exit from the back (hot aisle), in what is referred as hot-aisle-cold-aisle (HACA) arrangement. If the racks are kept in an open room space, the differential pressure between the front and back of the rack is zero. However, this may not be true for some scenarios, such as, in the case of cold aisle containment, where the cold aisle is physically separated from the hot data center room space to minimize cold and hot air mixing. For an under-provisioned case (total supplied tile air flow rate < total rack air flow rate) the pressure in the cold aisle (front of the rack) will be lower than the data center room space (back of the rack). For this case, the rack air flow rate will be lower than the case without the containment. In this paper, we will present a methodology to measure the rack air flow rate sensitivity to differential pressure across the rack. Here, we use perforated covers at the back of the racks, which results in higher back pressure (and lower rack air flow rate) and the corresponding sensitivity of rack air flow rate to the differential pressure is obtained. The influence of variation and nonuniformity in the server fan speed is investigated, and it is observed that with consideration of fan laws, one can obtain results for different average fan speeds with reasonable accuracy. The measured sensitivity can be used to determine the rack air flow rate with variation in the cold aisle pressure, which can then be used as a boundary condition in computational fluid dynamics (CFD)/rapid models for data center air flow modeling. The measured sensitivity can also be used to determine the change in rack air flow rate with the use of different types of front/back perforated doors at the rack. Here, the rack air flow rate is measured using an array of thermal anemometers, pressure is measured using a micromanometer, and the fan speed is measured using an optical tachometer.

Impact of aisle containment on energy performance of a data center when using an integrated water-side economizer

The main purpose of this study is to analyze the impact of cold aisle containment on the thermal management performance of a data center, as well as on the amount of energy consumed for cooling. The thermal management performance of the aisle containment architecture, which has been widely employed throughout the data center industry, is demonstrated by experiment. A computational fluid dynamics (CFD) modeling strategy is used for the containment air leakage prediction validated by experiments. The thermal management performance of an uncontained and contained aisles are compared through CFD simulation. In addition, since the containment's energy performance is maximized when an economizer is incorporated, a model-based simulation of the annual cooling energy consumption of a modular data center with an integrated water-side economizer is conducted. The simulation results show that the thermal management performance is excellent in both architectures with an appropriate cooling system control, but the energy savings are much greater with the contained architecture.

Experimentally Validated Computational Fluid Dynamics Model for a Data Center With Cold Aisle Containment

This paper presents the results of an experimentally validated computational fluid dynamics (CFD) model for a data center with fully implemented fan curves on both the servers and the computer room air conditioner (CRAC). Both open and contained cold aisle systems are considered in this study. This work is divided into sections for the baseline system (prior to installing containment) calibration and the fully contained cold aisle system calibration and leakage characterization. In the open system, the fan curve of the CRAC unit is extracted from the manufacturer data, while the fan curve of the load banks is obtained through experimental measurements. The experimental results are found to be in good agreement with the average model predictions. In the fully contained cold aisle system, a detailed containment CFD model is developed based on experimental measurements. The model is validated by comparing the flow rate through the perforated floor tiles and the rack inlet temperatures with the experimental measurements. The CFD results are found to be in good agreement with the experimental data with an average relative error between the measured and computed flow rate of approximately 6.7%. Temperature measurements are used to calibrate the sources of leakage in the containment and rack mounting rails. The temperature measurements and the CFD results agree well with an average difference of less than 1 °C. This study provides important modeling guidelines for data centers. In order to predict the performance of contained cold aisle systems flow distribution, it is crucial that physics based models of fan curves, server internal resistances, detailed rack models, and other design details are all accurate and experimentally verified.

Experimental Investigation of Air Flow Through a Perforated Tile in a Raised Floor Data Center

Raised floor data centers supply cold air from a pressurized plenum to the server racks through perforated floor tiles. Hence, the design of an efficient air delivery scheme requires better understanding of the flow features, through and above the perforated tiles. Different tiles with circular pores in a staggered arrangement and with the same thickness are considered. Tile sheet porosities of 23% and 40%, air flow rates of 0.56 m3/s (1177 CFM) and 0.83 m3/s (1766 CFM), and pore sizes of 3.18 mm (1/8 in.) and 6.35 mm (1/4 in.) are investigated. Tiles with 38.1 mm (1.5 in.) region blocked along the edges is compared to the base case with 12.7 mm (0.5 in.) blocked edges. Width reduced to 0.46 m (1.5 ft) from standard width of 0.61 m (2 ft) is also examined. Reduced tile width is used to simulate 0.91 m (3 ft) cold aisle instead of standard 1.22 m (4 ft) cold aisle, with potential to save floor space. A case where the rack is recessed by 76.2 mm (3 in.) from the tile edge is also included in the investigation, as there is a possibility of having racks nonadjacent to the tile edges. Particle image velocimetry (PIV) technique is used to characterize the flow field emerging from a perforated tile and entering the adjacent rack. Experiments suggest that lower tile porosity significantly increases cold air bypass from the top, possibly due to higher air jet momentum above the tile, as compared to a tile with higher porosity. For the air flow rates investigated here, the flow field was nearly identical and influence of flow rate was nondistinguishable. The influence of pore size was non-negligible, even when the porosity and flow rate for the two cases were same. Larger blockage of the tile edges resulted in higher cold air bypass from the top. Reduction in the tile width showed improved air delivery to the rack with considerably reduced cold air bypass. Recessing the rack did not affect the flow field significantly.

Airflow Optimization In Data Centers

A good airflow management scheme is critical to any data center operation. State-of-the-art IT equipment would fail to perform its functions if not provided with the required amount of cooling. Efficient cooling systems alone will not be able to do the job. Airflow—which acts as a liaison between these systems and carries the “cooling” from cooling systems to IT equipment, needs to be paid equal attention. Poor airflow management can turn a very good cooling and IT system into a mediocre one. On the other hand, a good airflow management scheme can help even a modest IT and cooling system to realize their full potential. The intent of this publication is to look at some ways of optimizing airflow in a data center space. These include but are not limited to: 1. Component Strategies: hot and cold aisle containment, efficient floor tiles, return air plenum extensions, variable frequency drives (VFDs), blanking panels, brush guards, return air registers, floor sealants, high efficiency plug fans, electronically commutated direct drive fan motors, etc.2. Control Strategies: integrated and smart control systems, wireless and wired sensors, optimization of temperature setpoints, run sequence, VFD speeds, air- and water-side economizer setpoints, reheat and humidification controls, etc.

Experimental Characterization of Various Cold Aisle Containment Configurations for Data Centers

The data center industry has experienced significant growth over the last decade, mainly due to the increased use of the internet for our day to day activities such as e-commerce, social media, video streaming, and healthcare. This growth in demand results in higher energy costs, as data centers can be energy intensive facilities. A significant portion of the energy used in data centers is for cooling purposes. Hence, it is one of the important areas of optimization to be addressed to create more efficient data centers. Among the many ways to increase data center efficiencies, air flow management is a key solution to many existing data centers. Fundamentally, there are three main schemes: hot-aisle containment, cold-aisle containment, and exhaust chimney containment. This paper's focus is to experimentally characterize the following cold aisle configurations: open aisle, partially contained aisle, and fully contained aisles. Experimental data presented to evaluate the effectiveness of the different configurations are rack inlet contour plots, tile and rack flow rates, pressure measurements, and server central processing unit (CPU) temperatures.

Analyzing the Cooling Efficiency of the Thermal Environment in Data Centers

Given the explosive growth of data, scalability and fault tolerance have become a fundamental challenge for data center network structures. Temperature in data centers significantly affects the failure ratio of high-speed network devices. Various types of air distribution schemes influence the temperature of network equipment differently, and the cooling cost in data centers dominates the overall energy cost. On the basis of the energy efficiency of cooling systems, this study analyzes and compares the thermal load distribution in the enclosure of standard and non-standard data centers by considering the effects of the external environment. Analysis results demonstrate that the external environment significantly affects the thermal load of non-standard data centers. By leveraging on the air temperature outside data centers and on the inlet/outlet of IT equipment, the air temperature and return air temperature of air conditioning are calculated when performing hot and cold aisle containment. The calculations indicate that sealing an appropriate aisle (hot or cold aisle) can significantly reduce the energy consumption of cooling systems in terms of the external air temperature outside data centers. Furthermore, if the air temperature outside data centers is higher than the temperature at the inlet of IT equipment, sealing the cold aisle outperforms sealing the hot aisle. By contrast, the aisle to be sealed depends on the energy efficiency ratio of the air conditioning.

Research on Intelligent Air Conditioning System of Data Center

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.

Experimental Study of Airflow Designs for Data Centers

Growth in ICT has led to increased demands on data centers. Highly reliable operations of data centers require an efficient and robust air-conditioning system. In most data centers, circulating air enters at the floor level, and returns at the ceiling level (floor supply design). However, the authors have developed an airflow design in which air is both supplied and returned at the ceiling level (ceiling supply design). To compare the cooling characteristics of both designs, temperatures were measured in a full-scale model of a data center. For both designs, changes in cooling characteristics were evaluated in response to changes in heat density, supply-air volume, and supply-air temperature. In addition, the authors studied the effects of separating cold and hot aisles by hanging walls from the ceiling between aisles. Dimensionless indices, dimensionless rack-temperatures, and values of the rack-cooling index (RCI) were used to compare the cooling characteristics of the two designs. The authors confirm that ceiling supply design is more robust regarding changes in major design parameters compared to floor supply design.

A multi-zone building energy simulation of a data center model with hot and cold aisles

Abstract In this paper, a building energy simulation code, EnergyPlus, was used to study the effects of wall boundary conditions, climatic locations, supply air temperatures, and volumetric flow rates, on the energy consumption and thermal performance of a popular data center model. The data center model having 1120 servers distributed in four rows of rack was investigated under two major climatic conditions–hot and humid (Miami, FL), and cool and humid (Chicago, IL). A multi-zone modeling approach was proposed to resolve the hot and cold aisles in the data center, and was compared to existing well-mixed single-zone model. Using the multi-zone approach that is believed more reasonable, both monthly and annual overall energy consumptions as well as cooling load were analyzed under various boundary conditions. In addition, monthly thermal behavior in the zones for hot and cold aisles within the data center was analyzed. The simulation results show that thermal performance of the data center is significantly affected by locations or climatic conditions. The effects of location and wall boundary conditions are particularly appreciable during the summer and winter seasons. An optimal supply temperature of 11.8 °C, and air flow rate of 2.5 m 3 /s were found to be most preferred selections for the data center model.

서버 컴퓨터의 발열량이 변화한 경우의 데이터센터 내의 기류 및 온도분포 특성에 대한 연구

On a large scale of data center, heat generation rates from sever computers occupy almost the entire cooling load of the building, and it is gradually increasing. The efficiency of air distribution system in data centers can be affected by heat generation rates of server computers. In this study, the distributions of airflow and temperature in a data center have been investigated by CFD simulations under various conditions of heat generation rates for server computers. From the results, air around the cold aisle which has high temperature flows tremendously into the cold aisle according to the increase of heat generation rates for server computers and the air temperature in the cold aisle becomes higher. The SHI (supply heat index) and RHI (return temperature index) show almost similar values to the cases study because the air inflow rates to server computers increase with the heat generation rates of server computers.

Energy consumption analysis of a medium-size primary data center in an academic campus

Experimental, numerical, and simulation studies were performed to evaluate the energy efficiency performance, develop energy conservation measures (ECMs), and conduct overall energy analysis of a medium-size data center at the campus of the University of Maryland, College Park. Based on the analysis, the PUE (power usage effectiveness) of the data center was found to be 2.73, suggesting ample opportunity for energy saving measures. The IT, cooling, and electrical loads consume 36.6%, 32.9%, and 21.7% of the total data center energy consumption, respectively. Four ECMs are suggested to reduce energy consumption by optimizing the thermo-fluid flow in the data center: (1) eliminate unnecessary CRACs (computer room air conditioning units); (2) increase the return air temperature at the CRACs; (3) add cold aisle containment; (4) implement fresh air cooling. In addition, a transient analysis was performed under a total power failure scenario of all cooling systems, as well as failure of individual CRACs as a separate analysis, to predict the corresponding temperature increase with time in the data center and electronics.

Room Level Modeling of Air Flow in a Contained Data Center Aisle

Cold aisle containment is used in air cooled data centers to minimize direct mixing between cold and hot air. Here, we present room level air flow field investigation for open, partially and fully contained cold aisles. Our previous investigation for rack level modeling has shown that consideration of momentum rise above the tile surface, due to acceleration of air through the pores, significantly improves the predictive capability as compared to the generally used porous jump model. The porous jump model only specifies a step pressure loss at the tile surface without any influence on the flow field. The momentum rise could be included by either directly resolving the tile's pore structure or by artificially specifying a momentum source above the tile surface. In the present work, a modified body force model is used to artificially specify the momentum rise above the tile surface. The modified body force model was validated against the experimental data as well as with the model resolving the tile pore geometry at the rack level and then implemented at the room level. With the modified body force model, much higher hot air entrainment and higher server inlet temperatures were predicted as compared to the porous jump model. Even when the rack air flow requirement is matched with the tile air flow supply, considerable hot air recirculation is predicted. With partial containment, where only a curtain at the top of the cold aisle is deployed and side doors are opened, improved cold air delivery is suggested.