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More than ever before, data centers must deploy robust thermal solutions to adequately host the high-density and high-performance computing that is in high demand. The newer generation of central processing units (CPUs) and graphics processing units (GPUs) has substantially higher thermal power densities than previous generations. In recent years, more data centers rely on liquid cooling for the high-heat processors inside the servers and air cooling for the remaining low-heat information technology equipment. This hybrid cooling approach creates a smaller and more efficient data center. The deployment of direct-to-chip cold plate liquid cooling is one of the mainstream approaches to providing concentrated cooling to targeted processors. In this study, a processor-level experimental setup was developed to evaluate the cooling performance of a novel computer numerical control (CNC) machined nickel-plated impinging cold plate on a 1 in. × 1 in. mock heater that represents a functional processing unit. The pressure drop and thermal resistance performance curves of the electroless nickel-plated cold plate are compared to those of a pure copper cold plate. A temperature uniformity analysis is done using compuational fluid dynamics and compared to the actual test data. Finally, the CNC machined pure copper one is compared to other reported cold plates to demonstrate its superiority of the design with respect to the cooling performance.

An increasingly common power saving practice in data center thermal management is to swap out air cooling unit blower fans with electronically commutated plug fans, Although, both are centrifugal blowers. The blade design changes: forward versus backward curved with peak static efficiencies of 60% and 75%, respectively, which results in operation power savings. The side effects of which are not fully understood. Therefore, it has become necessary to develop an overall understanding of backward curved blowers and compare the resulting flow, pressure, and temperature fields with forwarding curved ones in which the induced fields are characterized, compared, and visualized in a reference data center which may aid data center planning and operation when making the decisions of which computer room air handler (CRAH) technology to be used. In this study, experimental and numerical characterization of backward curved blowers is introduced. Then, a physics-based computational fluid dynamics model is built using the 6sigmaroom tool to predict/simulate the measured fields. Five different scenarios were applied at the room level for the experimental characterization of the cooling units and another two scenarios were applied for comparison and illustration of the interaction between different CRAH technologies. Four scenarios were used to characterize a CRAH with backward curved blowers, during which a CRAH with forwarding curved was powered off. An alternate arrangement was examined to quantify the effect of possible flow constraints on the backward curved blower's performance. Then parametric and sensitivity of the baseline modeling are investigated and considered. Different operating conditions are applied at the room level for experimental characterization, comparison, and illustration of the interaction between different CRAH technologies. The measured data is plotted and compared with the computational fluid dynamics (CFD) model assessment to visualize the fields of interest. The results show that the fields are highly dependent on CRAH technology. The tile to CRAH airflow ratios for the flow constraints of scenarios 1, 2, 3, and 4 are 85.5%, 83.9%, 61%, and 59%, respectively. The corresponding leakage ratios are 14.5%, 16%, 38.9%, and 41%, respectively. Furthermore, the validated CFD model was used to investigate and compare the airflow pattern and plenum pressure distribution. Lastly, it is notable that a potential side effect of backward curved technology is the creation of an airflow dead zone.

The practice of commissioning data centers (DCs) is necessary to confirm the compliance of the cooling system to the information technology equipment (ITE) load (design capacity). In a typical DC, there are different types of ITE, each having its physical characteristics. Considering these geometrical and internal differences among ITE, it is infeasible to use the actual ITE as a self-simulator. Hence, a separate device called load bank is employed for that purpose. Load banks create a dummy thermal load to analyze, test, and stress the cooling infrastructure. Available commercial load banks do not accurately replicate a server's airflow patterns and transient heat signatures which are governed by thermal inertia, energy dissipation, flow resistance, and fan system behavior. In this study, a novel prototype of the server called server simulator was designed and built with different components to be used as a server mockup. The server simulator accurately captured air resistance, heat dissipation, and the functionality of actual server behavior. Experimental data showed up to 93% improvement in ITE passive and active flow curves using the designed server simulator compared to the commercial load bank. Furthermore, the experimental results demonstrated a below 5% discrepancy on the critical back pressure and free delivery point between the actual ITE and the designed server simulator. In addition, experimental data indicated that the developed server simulator improved the actual ITE thermal mass by 27% compared to the commercial load bank.

As heterogeneous integration evolves, the diversity and density of devices that combine multiple functionalities has significantly increased. The subsequent increase in power usage and reduced size of components, specifically of Central Processing Units (CPUs), underlines the limitations of traditional cooling and reveals the need for significant improvements in thermal management. In this study, an innovative fluid-thermal cooling solution that addresses high density and non-uniform heat dissipation in a CPU package will be presented. The solution design includes jet impingement, which is used to directly cool four electronic chips simultaneously, as well as chip-attached micro pin fins. The copper micro pin fins have been additively manufactured onto the surface of the silicon chip using Selective Laser Melting (SLM), thus eliminating the need for thermal interface materials (TIMs). The effects of jet nozzle size and jet-to-chip distance on heat transfer and fluid flow are numerically investigated. The presented solution shows the potential to improve thermal performance with a lower level of system complexity and lower overhead for coolant and fabrication. To the author’s knowledge, the thermal resistance results are the lowest reported (0.015 K/W) in the area of single-phase cooling research.

Organophosphate poisoning by self-injection is rare. Current case report describes a man with subcutaneous self-injected OP. poisoning presenting with delayed. He was treated with pralidoxime. Through the observation, dose and the time between poisoning until time to start treatment we can conclude different presentations and outcomes of OP poisoning.

It is well known that fans have been widely used in many applications for cooling and ventilation purposes. However, in a considerable portion of these applications, fans are being operated in highly resistive environments such as ITE (Information Technology Equipment) in which the fan will be installed in a narrow space surrounded by many obstacles. These obstructions lead to increased vibration and degradation in fan performance. As the fans’ pressure-flow rate (P-Q) curve is used to indicate the fan's performance, previous studies have investigated the blockage effect on the fan's P-Q curve using a flow test chamber. However, these studies measured the pressure from a considerable distance from the fan. Hence, developing a new technique that can measure the pressure closer to the fan will help in conducting a better understanding of how fans react to the presence of obstruction. In this work, pressure readings were taken through pressure taps that were drilled in a plexiglass sheet an experimental setup was designed to study the server chassis blockage effect on the fan performance by getting a multiple pressure reading right across the fans. These measurements were compared with pressure measurements that were collected from the flow test chamber at a considerable distance from the fan.

Data center power consumption has grown substantially in the past 20 years. According to the United States Data Center Energy Usage Report, the data center consumption in 2014 was estimated at 70 billion kWh, which accounted for 1.8% of the total U.S. electricity. The present effort investigates the effects of various data center parameters on a new set of metrics called the performance indicator to help assess and optimize the cooling performance of data centers. The three metrics in the performance indicator include power usage effectiveness ratio (PUEr), thermal conformance, and thermal resilience. The data center parameters investigated include computer room air handler (CRAH) setpoints, room configuration layouts, and containment strategies. The results show that the CRAH setpoint significantly influences the PUEr with higher setpoint values resulting in lower PUEr values. Room configuration layout changes and containment strategies showed substantial effects on thermal conformance and thermal resilience. The thermal conformance was increased approximately 10% with room configuration changes without changing the PUEr. Full hot aisle containment also improved the thermal conformance by 7.4%.

In most data centers, performance reliability is often ensured by setting the amount of airflow provided by the cooling units to substantially exceed that which is needed by the IT equipment. This overly conservative strategy requires additional energy expenditure, which inevitably results in a huge amount of energy being wasted by the cooling system. To eliminate adopting such wasteful policies, conducting proper management of airflow, temperature, and energy is critical. To that end, this work proposes a novel approach to developing a compact IT equipment model at off-design conditions. This model is designed to support thermal and energy management functions in data centers. The benefit of this model is that it can accurately predict not only the IT equipment power consumption, but also the amount of flowrate required for the equipment and the air temperature leaving the equipment. While the compact model’s power consumption was derived as a function of CPU utilization, its flowrate demand and exhaust temperature were obtained from a dynamic detailed CFD model. Results from the compact model were validated with experiments where the maximum mismatch was found to be 5.7% in the outlet temperature field and 11.4% in flowrate. Compared to a state-of-the-art IT equipment compact model, the developed model was found to reduce the prediction error of the equipment’s flowrate and outlet air temperature by up to 5.2% and 9.3 % that of the state-of-the-art IT equipment compact model, respectively.

This study reports on the essential forced air-cooled electronics issue of fan performance deterioration caused by the presence of obstructions inside Information Technology Equipment (ITE). Fan performance was characterized based on the fan's static pressure and flowrate. Three different experimental techniques (flow test chamber, pressure probe, and pressure taps) were used to measure the fan static pressure at different locations. Moreover, Computational Fluid Dynamics (CFD) models were built considering different fan working environments. Multi Reference Frame (MRF) and Lumped Fan (LF) model CFD techniques were employed. The experimental results were used to evaluate the modeling techniques whilst implemented in different working environments and to better understand how fans react to blockages inside ITE. Experiments showed that compared to the Free Environment (FE) readings, placing the fan inside a specific ITE reduced the flowrate delivered by the fan by 57.2% and decreased static pressure by 76.3%, which affects the thermal performance of the ITE cooling system. Moreover, comparing numerical results with the experimental ones showed that the MRF approach predicted the flowrate delivered by the fan with a relative error of 3.9%, while the LF approach overestimated the flowrate by 70.3%. The results and conclusions reported in this work can be expanded to cover many other applications in which fans are operating inside enclosed environments and surrounded by many obstructions.

The accelerated growth of heat load in high-density data centers presents challenges to the design of effective cooling solutions. Both energy efficiency and the information technology (IT) equipment reliability are key requirements. Localized hybrid air-water cooling systems such as Rear Door Heat eXchangers (RDHXs) are an effective means to achieve these requirements. In this paper, the transient aerodynamic and thermal performance of a commercial RDHX was investigated experimentally. The RDHX was attached to an isolated server cabinet with a controllable heat load. A localized containment system was used to direct the airflow to the equipment in the cabinet that emanates from a single perforated tile within the enclosure. The water flow rate and supply water temperature to the RDHX was controlled, and a grid of 36 air velocity/temperature sensors was employed to monitor the airside of the cooling system. The cooling performance of the RDHX in an air blower failure scenario was investigated. The failure scenario was designed to diminish different parts of the overall system. The impact on the IT equipment and the cabinet outlet temperatures was assessed. Also, there was a significant reduction in the airflow to the IT equipment. The impact of the reduced airflow on different parts of the cabinet as well as the cooling performance of the heat exchanger was characterized during both failure and recovery.

There are various designs for segregating hot and cold air in data centers such as cold aisle containment (CAC), hot aisle containment (HAC), and chimney exhaust rack. These containment systems have different characteristics and impose various conditions on the information technology equipment (ITE). One common issue in HAC systems is a pressure build-up inside the HAC (known as backpressure). Backpressure also can be present in CAC systems in case of airflow imbalances. Hot air recirculation, limited cooling airflow rate in servers, and reversed flow through ITE with weaker fan systems (e.g., network switches) are some known consequences of backpressure. Currently, there is a lack of experimental data on the interdependency between overall performance of ITE and its internal design when backpressure is imposed on ITE. In this paper, three commercial 2-rack unit (RU) servers with different internal designs from various generations and performance levels are tested and analyzed under various environmental conditions. Smoke tests and thermal imaging are implemented to study the airflow patterns inside the tested equipment. In addition, the impact of hot air leakage into the servers through chassis perforations on the fan speed and the power consumption of the servers are studied. Furthermore, the cause of the discrepancy between measured inlet temperatures by the intelligent platform management interface (IPMI) and external sensors is investigated. It is found that arrangement of fans, segregation of space upstream and downstream of fans, leakage paths, the location of baseboard management controller (BMC) sensors, and the presence of backpressure can have a significant impact on ITE power and cooling efficiency.

Cooling failure in data centers (DCs) is a complex phenomenon due to the many interactions between the cooling infrastructure and the information technology equipment (IT). To fully understand it, a system integration philosophy is vital to the testing and design of experiment. In this paper, a facility-level DC cooling failure experiment is run and analyzed. An airside cooling failure is introduced to the facility during two different cooling set points as well as in open and contained environments. Quantitative instrumentation includes pressure differentials, tile airflow, external contour and discrete air inlet temperature, intelligent platform management interface (IPMI), and cooling system data during failure recovery. Qualitative measurements include infrared imaging and airflow visualization via smoke trace. To our knowledge of current literature, this is the first experimental study in which an actual multi-aisle facility cooling failure is run with real IT (compute, network, and storage) load in the white space. This will establish a link between variations from the facility to the central processing unit (CPU). The results show that using the external IT inlet temperature sensors, the containment configuration shows a longer available uptime (AU) during failure. However, the IPMI data show the opposite. In fact, the available uptime is reduced significantly when the external sensors are compared to internal IT analytics. The response of the IT power, CPU temperature, and fan speed shows higher values during the containment failure. This occurs because of the instantaneous formation of external impedances in the containment during failure, which renders the contained aisle to be less resilient than the open aisle. The tradeoffs between PUE, OPEX, and AU are also explained.

This article reports experimental and numerical testing performed to characterize the operation and reliability of the open compute (OC) storage system in contained environment from server to aisle levels. The study is comprised of three parts. The first part is an experimental analysis of the high density (HD) 3D array storage unit thermal and utilization responses during airflow imbalances. This is done with the stress test proposed for IT in containment to mimic possible mismatch and cascade failure scenarios. It is found that downstream HDDs are most prone to overheating and loss in utilization during an airflow imbalance. This was proven to undermine the storage capacity of the hard disk drives. An IT level airflow prediction model is discussed for the storage unit and validated for different fan speeds. In the second part, a computational fluid dynamics model is created for a high density open rack based on the active flow curve method. Here, the measured airflow response curves for the open compute IT (storage and compute servers) are used to build compact models and run rack level testing for IT air systems sensitivity and create a rack level AFC (active flow curve) airflow demand prediction model. Finally, the experimental characterization data is used to build an aisle level model (POD) that incorporates IT fan control systems (FCS). This modeling approach yields shorter uptime during chiller failure due to increased recirculation induced by increased IT airflow demand during cases such as chiller failure or high economizer temperatures.

We developed a generalized testing methodology in which IT fans’ internal and external impedance effects are collapsed into a single curve (i.e., flow curve). Such curves can give accurate flow rate predictions of the IT equipment based on RPM logging. Flow curves cover the three possible airflow regions for IT in a contained environment. The experimental procedure is introduced to rank IT equipment based on its air systems, and the flow regions are correlated with the CPU performance. The strength of the IT air system is characterized by the free delivery and the critical pressure points. In addition, the experimentally obtained active flow curves can be used as a numerical boundary condition in various containment designs. Accordingly, for the first time in the literature, the aerodynamic interaction of IT with different air systems in the containment (i.e., BladeCenters, servers, and switches) can numerically be investigated. It is found that stacking IT in a contained environment with no physical consideration can lead to radical reliability problems. The region of reverse flow is discovered to be very possible upon events in the data center. In such a case, the weak IT (e.g., 1U switch) behaves as an open leakage into the sealed containment. On the other hand, at the critical pressure point, minimum forced convection occurs in the weak IT, leading to CPU overheating.

Impingement micro-channel heat sinks are in general preferred over parallel flow micro-channel heat sinks owing to the reduced pressure drop. Splitting the flow in two branches cuts the flow rate and path in half, which leads to lower pressure drop through the channels in impingement heat sinks compared to a parallel flow heat sink. A numerical model was developed to predict the heat sink performance. Because of the significant effect that inlet and outlet manifolds (distributor and collector) have on the heat sink hydraulic and thermal performance, the numerical model includes them. The model was validated both for hydraulic and thermal performance using experimental data. The model was used for shape optimization of the heat sink in constant chip power, coolant inlet temperature and flow rate as well distributor and collector geometry. A parametric study was performed to estimate the effect of the geometric design parameters on the hydraulic and thermal resistances as the response parameters. The chip-base interface temperature profile was very different from typical parallel heat sinks. The coefficient of performance as a measure of the heat sink overall performance (hydraulic and thermal) was measured experimentally. Furthermore, the sensitivity of the heat sink coefficient of performance to chip power, coolant inlet temperature and flow rate was estimated using a regression model fitted on the obtained experimental result.

There are various designs for segregating hot and cold air in data centers such as cold aisle containment (CAC), hot aisle containment (HAC), and chimney exhaust rack. These containment systems have different characteristics and impose various conditions on the information technology equipment (ITE). One common issue in HAC systems is the pressure buildup inside the HAC (known as backpressure). Backpressure also can be present in CAC systems in case of airflow imbalances. Hot air recirculation, limited cooling airflow rate in servers, and reversed flow through ITE with weaker fan systems (e.g. network switches) are some known consequences of backpressure. Currently there is a lack of experimental data on the interdependency between overall performance of ITE and its internal design when a backpressure is imposed on ITE. In this paper, three commercial 2-rack unit (RU) servers with different internal designs from various generations and performance levels are tested and analyzed under various environmental conditions. Smoke tests and thermal imaging are implemented to study the airflow patterns inside the tested equipment. In addition, the impact leak of hot air into ITE on the fan speed and the power consumption of ITE is studied. Furthermore, the cause of the discrepancy between measured inlet temperatures by internal intelligent platform management interface (IPMI) and external sensors is investigated. It is found that arrangement of fans, segregation of space upstream and downstream of fans, leakage paths, location of sensors of baseboard management controller (BMC) and presence of backpressure can have a significant impact on ITE power and cooling efficiency.

Power Usage Effectiveness (PUE™) has been proposed by The Green Grid (TGG) about a decade ago and it became a popular indicator of data center energy efficiency performance. Although, the definition of PUE is simple and straight forward, it can be misleading because it only considers the effectiveness of energy delivery rather that the resulting cooling performance or IT productivity that results. In addition, the measurement has fundamental limitations such as the inclusion of IT fan power in IT equipment power rather than cooling power and so the results can be skewed. Representing the thermal performance of a data center by a single PUE number is incomplete and a more holistic metric is required. The Green Grid (TGG) has developed a new view of multiple metrics (TGG Performance Indicator (PI)) that beside energy efficiency evaluate facility cooling performance based on IT thermal standards during normal and redundant cooling system failure. TGG PI defines the thermal conformance and resilience of IT as measures of cooling effectiveness along with PUE as a measure of cooling efficiency and displays them in a single view. This view allows the business, not just the technical teams, to observe the trade-off between adjusting thermal performance based on standards and striving energy efficiency and choose the balance that best fits the business need. The data center community is becoming increasingly aware of the need to provide efficient and effective data center. However, beside the publicized PUE figures for high profile hyperscale data centers what cooling performance can a data center operator realistically expect? The introduction of TGG PI offers a view to evaluate not just energy efficiency but the effectiveness of cooling delivery as well. However, does the view of the metrics tell us whether the data center performance is good or bad? This paper shows the PI values for a number of existing data centers and discusses the need for performance data to understand what performance might be expected for different data center types, cooling infrastructures, locations and associated climates.

In raised floor data centers, tiles with high open area ratio or complex understructure are used to fulfill the demand of today's high-density computing. Using more open tiles reduces the pressure drop across the raised floor with the potential advantages of increased airflow and lower noise. However, it introduces the disadvantage of increased nonuniformity of airflow distribution. In addition, there are various tile designs available on the market with different opening shapes or understructures. Furthermore, a physical separation of cold and hot aisles (containment) has been introduced to minimize the mixing of cold and hot air. In this study, three types of floor tiles with different open area, opening geometry, and understructure are considered. Experimentally validated detail models of tiles were implemented in computational fluid dynamics (CFD) simulations to address the impact of tile design on the cooling of information technology (IT) equipment in both open and enclosed aisle configurations. Also, impacts of under-cabinet leakage on the IT equipment inlet temperature in the provisioned and under-provisioned scenarios are studied. In addition, a predictive equation for the critical under-provisioning point that can lead to a no-flow condition in IT equipment with weaker airflow systems is presented. Finally, the impact of tile design on thermal performance in a partially enclosed aisle with entrance doors is studied and discussed.

In raised floor data centers, tiles with high open area ratio or complex understructure are used to fulfill the demand of today’s high-density computing. Using more open tiles reduces pressure drop across the raised floor with the potential advantages of increased airflow and lower noise. However, it introduces the disadvantage of increased non-uniformity of airflow distribution. In addition, there are various tile designs available on the market with different opening shapes or understructures. Furthermore, a physical separation of cold and hot aisles (containment) has been introduced to minimize the mixing of cold and hot air. In this study, three types of floor tiles with different open area, opening geometry, and understructure are considered. Experimentally validated detail models of tiles were implemented in CFD simulations to address the impact of tile design on the cooling of IT equipment in both open and enclosed aisle configurations. Also, impacts of under-cabinet leakage on the IT equipment inlet temperature in the provisioned and under-provisioned scenarios are studied. Finally, a predictive equation for the critical under-provisioning point that can lead to a no-flow condition in IT equipment with weaker airflow systems is presented.

The operation of today’s data centers increasingly relies on environmental data collection and analysis to operate the cooling infrastructure as efficiently as possible and to maintain the reliability of IT equipment. This in turn emphasizes the importance of the quality of the data collected and their relevance to the overall operation of the data center. This study presents an experimentally based analysis and comparison between two different approaches for environmental data collection; one using a discrete sensor network, and another using available data from installed IT equipment through their Intelligent Platform Management Interface (IPMI). The comparison considers the quality and relevance of the data collected and investigates their effect on key performance and operational metrics. The results have shown the large variation of server inlet temperatures provided by the IPMI interface. On the other hand, the discrete sensor measurements showed much more reliable results where the server inlet temperatures had minimal variation inside the cold aisle. These results highlight the potential difficulty in using IPMI inlet temperature data to evaluate the thermal environment inside the contained cold aisle. The study also focuses on how industry common methods for cooling efficiency management and control can be affected by the data collection approach. Results have shown that using preheated IPMI inlet temperature data can lead to unnecessarily lower cooling set points, which in turn minimizes the potential cooling energy savings. It was shown in one case that using discrete sensor data for control provides 20% more energy savings than using IPMI inlet temperature data.

The constant increase in data center computational and processing requirements has led to increases in the IT equipment power demand and cooling challenges of high-density (HD) data centers. As a solution to this, the hybrid and liquid systems are widely used as part of HD data centers thermal management solutions. This study presents an experimental based investigation and analysis of the transient thermal performance of a stand-alone server cabinet. The total heat load of the cabinet is controllable remotely and a rear door heat exchanger is attached with controllable water flow rate. The cooling performances of two different failure scenarios are investigated. One is in the water chiller and another is in the water pump for the Rear Door Heat eXchanger (RDHX). In addition, the study reports the impact of each scenario on the IT equipment thermal response and on the cabinet outlet temperature using a mobile temperature and velocity mesh (MTVM) experimental tool. Furthermore, this study also addresses and characterizes the heat exchanger cooling performance during both scenarios.

The transient modeling of cross flow heat exchangers requires the use of complicated analytical solutions or complex numerical schemes to solve the set of coupled partial differential equations representing the air, coolant and wall temperatures. Since most of the dynamic mass flow or temperature perturbations encountered in data center environment are slow compared with the timescale of the heat exchanger, using a simpler quasi-steady model instead of a complex transient solution represents a good alternative. The present work shows the use of a quasi-steady heat exchanger model to recreate the transient response of a 12×12 in heat exchanger core under ramp and sinusoidal perturbations. A criteria to identify the regimes where the quasi-steady model is valid is developed. Finally the model is used to model a rear door heat exchanger and the results compared with experimental results.

The rapid growth in the number of data centers combined with the high-density heat dissipation of computer and telecommunications equipment has made energy efficient thermal management of data centers a key research area. Localized hybrid air–water cooling is one approach to more effectively control the cooling when there is wide variation in the amount of dissipation in neighboring racks while the traditional air cooling approach requires overprovisioning. In a closed, hybrid air–water cooled server cabinet, the generated heat is removed by a self-contained system that does not interact with the room level air cooling system. Here, a hybrid-cooled enclosed cabinet and all its internal components were characterized experimentally in steady-state mode (e.g., experimentally determined heat-exchanger effectiveness and IT characterization). Also, a comprehensive numerical model of the cabinet was developed and validated using the experimental data. The computational model employs full numerical modeling of the cabinet geometry and compact models to represent the servers and the air/water heat exchanger. The compact models were developed based on experimental flow and thermal characterization of the internal components. The cabinet level model has been used to simulate a number of operating scenarios relevant to data center applications such as the effect of air leakage within the cabinet. The effect of the air side and the water side failure of the cooling system on the IT performance were investigated experimentally. A comparison was made of the amount of time required to exceed the operating temperature limit for the two scenarios.

Today's data centers increasingly rely on environmental data collection and analysis to operate the cooling infrastructure as efficiently as possible and to maintain the reliability of IT equipment. This in turn emphasizes the importance of the quality of data collected and its relevance to the overall operation of the data center. This study presents an experiment based analysis and comparison of environmental and power data collection using two different approaches; one uses a discrete sensor network and smart PDUs, and another uses available data from the installed IT equipment (IPMI data). The comparison looks deeply into the effect of both approaches that are adopted to control data center cooling. In addition, the effect that the Supply Air Temperature (SAT) from the Computer Room Air Handler (CRAH) unit had on the IT equipment was investigated in fully sealed Cold Aisle Containment (CAC) with 100% CPU utilization. It can be observed that the difference between the discrete and IPMI inlet temperature of the IT equipment increased as SAT increased due to the IT fans increasing speed in an attempt to get more cooling and the resulting in negative pressure differential build up inside the containment. Furthermore, the authors identified a value of the supply air temperature at which IT equipment started to ramp up for both approaches of data center cooling and control. The novelty of this study may aid data center operators when making the decision of what monitoring or control scheme to use.

In most air cooled data centers the required air for cooling of IT equipment is supplied from a raised floor to server racks through perforated tiles; therefore, an understanding of tile impact on flow features is an essential step for designing an efficient air delivery scheme. In recent years, different approaches have been implemented to increase the efficiency of air delivery through tiles such as the use of directional tiles or adding understructure scoops. In such tiles, the approaching angle of the cross flow to the tile, the angle of approach, becomes very important, since it may result in different velocity stratification patterns. Although many studies have focused on the use of computational fluid dynamics (CFD) for predicting tile airflow delivery to the racks, very few controlled experimental results are available. An important factor that has been often ignored in perforated tile modeling is the direction of the flow approaching the tile. In this study, an experimental setup has been designed and built to examine the effects of the direction of the approaching airflow to the tile on the airflow rate and resulting jet of coolant for different types of perforated tiles. In the designed setup, rotating the tile on a horizontal surface changes the angle of approaching airflow. The effect of angle of approach (AoA) on the direction of the jet is visualized by creating a laser sheet and performing airflow smoke visualization tests for four different types of tiles. Visualizations showed that the airflow direction changes significantly with AoA. Furthermore, the velocity distribution of air after the tiles at various AoA are measured, presented, and compared using a vane anemometer and a velocity sensor grid. Finally, the airflow rates for each case is calculated from the measured velocities by a grid of velocity sensors and a vane anemometer, which are then compared with flow rates measured by a commercial flow hood.

In this article, the particle swarm optimization (PSO) algorithm is modified to use the learning automata (LA) technique for solving initial and boundary value problems. A constrained problem is converted into an unconstrained problem using a penalty method to define an appropriate fitness function, which is optimized using the LA-PSO method. This method analyses a large number of candidate solutions of the unconstrained problem with the LA-PSO algorithm to minimize an error measure, which quantifies how well a candidate solution satisfies the governing ordinary differential equations (ODEs) or partial differential equations (PDEs) and the boundary conditions. This approach is very capable of solving linear and nonlinear ODEs, systems of ordinary differential equations, and linear and nonlinear PDEs. The computational efficiency and accuracy of the PSO algorithm combined with the LA technique for solving initial and boundary value problems were improved. Numerical results demonstrate the high accuracy and...

Imperialist competitive algorithm (ICA) is proposed to solve initial and boundary value problems in this paper. A constrained problem is converted into an unconstrained problem through the use of a penalty method in other to define an appropriate fitness function that is optimized by means of the ICA method. The methodology adopted evaluates a large number of candidate solutions of the unconstrained problem with the ICA to minimize error measure, which quantifies how well a candidate solution satisfies the governing ordinary differential equations (ODEs) or partial differential equations (PDEs) and the boundary conditions. The method is proficient approach to solve linear and nonlinear ODEs, systems of ordinary differential equations (SODEs), linear and nonlinear PDEs. Numerical experiments demonstrate the accuracy and efficiency of the proposed method. Thus, this method is a promising tool for solving higher-dimensional problems.

One of the known methods for solving the problems with exponential time complexity such as NP-complete problems is using the brute force algorithms. Recently, a new parallel computational framework called Membrane Computing is introduced which can be applied in brute force algorithms. The usual way to find a solution for the problems with exponential time complexity with Membrane Computing techniques is byPSystem with active membrane using division rule. It makes an exponential workspace and solves the problems with exponential complexity in a polynomial (even linear) time. On the other hand, searching is currently one of the most used methods for finding solution for problems in real life, that the blind search algorithms are accurate, but their time complexity is exponential such as breadth-first search (BFS) algorithm. In this paper, we proposed a new approach for implementation of BFS by usingPsystem with division rule technique for first time. The theorem shows time complexity of BSF in this framework on randomly binary trees reduced fromO(2d)toO(d).

Aisle containment is increasingly being used in data center cooling solutions because of the benefits of segregating the cold and hot air streams which reduces mixing and enhances energy savings. Containment can be integrated into legacy raised floor or non-raised floor local cooling systems such as in-row coolers. However, containment is not always entirely effective due to leakage. Although containment systems providing better sealing are becoming available, significant leakage exists in currently operational sites. The impact of leakage can be significant leading to backflow, the Venturi effect or entrainment. Comparisons between Cold Aisle Containment (CAC) and Hot Aisle Containment (HAC) indicate that there is a slight advantage of the latter in terms of ambient room temperature, failure scenarios and heat exchanger efficiency, although CAC systems can be easier to install. Detailed comparisons between both containment solutions are not widely available. Each containment approach has different behavior characteristics and air flow paths. For instance, leakage can introduce different flow and temperature conditions at server inlets depending on whether CAC or HAC is being used. An experimental characterization of containment was carried out at the ES2 research data center lab at Binghamton University [1] along with detailed numerical modeling. The numerical model was validated based on the experimentally measured flow rate of the perforated tiles in the cold aisles. Also, for the different types of IT equipment modeled in the simulations, experimentally measured flow impedance and fan curves were utilized. The details of the containment including leakage at the bottom and sides of the racks, the mounting rails, blanking panels and door seams were characterized experimentally and then incorporated in the computational model. Fan curves for the three CRAH blowers were used to accurately represent the targeted flow rates. This study focuses on three containment configurations: cold aisle containment and hot aisle containment and chimney (with a drop ceiling). In first two cases, the CRAH flow rate is controlled based on the pressure difference that was measured by three sensors inside and outside of the containment and for the third case, the CRAH flow rate was controlled based on IT required air flow. The water flow rate of the CRAH unit is also controlled based on the air return temperature and total heat load in the room so as to maintain the supply air temperature set point. The temperature and pressure fields in the aisles and at the server inlets and outlets are monitored for all the cases with leakage.

In this experimental study a unique configuration of a isolated cabinet with IBM Rear Door Heat exchanger was utilized. This experimental test setup is located in the ES2 data center laboratory at Binghamton University. The cabinet was populated by 16 servers (2 RU) and one 9 RU server simulator. With this equipment a maximum of about 15.9 kW can be generated. Localized cold aisle containment was employed in order to provide a more uniform inlet air temperature to the IT equipment. A single perforated tile is located in front of the cabinet within the containment enclosure. Two types of tiles with 65% and 22% open perforation area were used in different experiments. On the water side of the heat exchanger, a control system maintains the water temperature (by controlling three-way valve) and the water flow rate (by controlling pump speed). The control system also can monitor and collect water supply and return temperature data. For the experimental air side measurements a Mobile Temperature/Velocity Mesh (MTVM) was developed in order to measure air temperature/velocity at the front and rear of the cabinet. This sensor system obtains measurements on a grid in a 2D plane and the data is transferred via a network connection.

In this investigation, we utilize a new method of characterization in which IT airflow systems are ranked from a 1RU ToR switches, xRU servers to 9RU Blade Center. The free delivery (FD) and the critical pressure (Pc) are unique properties of each IT airflow system, satisfying its active flow curve (AFC). Those curves are used in previously validated models to investigate the interaction of IT with different air systems in a confined space. A validated model of containment is studied of a CAC aisle from Binghamton University data center lab. It is shown that reverse flow can take place in an operating piece of IT with weaker air system; this can endanger IT reliability and up time at different data center events. This can also change previous conclusions about the ride through time in well-sealed fully contained systems. Another important finding is that design containment systems based on the assumption of uniform load in the aisle/cabinet is a misconception that can endanger facility operation. In general, the reduction in airflow rate upon events in the data center (DC) is a function of each IT air system. To our knowledge, this is the first time in literature where both recent models of IT active flow curves and black box thermal inertia are combined to yield realistic failure analysis of contained solutions.

Data Centers are prone to power outages and cooling failures. During such events, complex transport interactions take place between the cooling system and the IT. Empirical data on this phenomenon is scarce in the current literature due to the complexity and size of such experiments. In this study, a facility level data center blowers cooling failure experiment is run and analyzed. Quantitative instrumentation includes pressure differentials, tile airflow, point air inlet temperature, contours air inlet temperature and IT IPMI data during failure-recovery. Qualitative measurements include IR imaging and airflow visualization via smoke trace. To our knowledge, this is the first experimental study in literature in which an actual multi aisle facility cooling failure is run with real IT (compute, Network and storage) load in the white space. This will enable a link between variations from the facility to the chip levels. Results show that by using external air inlet temperature sensors the containment configuration has a longer uptime during failure. However, the IPMI data shows the opposite. In fact, the RTT is reduced by ∼70% when the external and internal sensors are compared. This occurs due external impedances formed by the containment during failure degrading IT airflow systems. The inconsistency between IT IPMI inlet sensors and externally placed IT or rack inlet sensors (based on best practices) are expected to increase as the airflow imbalances increase.

In traditional data centers chilled air flow is delivered to the IT equipment through the raised floor plenum and perforated tiles. Variation of power load in different racks in the same aisle increases the possibility of over cooling of some IT and hot spots in others. Additional solutions like cold and hot aisle containment, chimneys, etc are employed to prevent the mixture of hot and cold air in data centers. In order to avoid this problem, localized hybrid cooling solutions are used in recently designed data centers. By putting the cooling source closer to the heat load, the localized cooling capacity is more controllable and this significantly increases the energy efficiency. On the other hand, data center energy efficiency is not the only consideration, but other operational conditions need to be considered. In the current study, a commercial hybrid cooled, enclosed server cabinet is studied empirically and numerically. The CFD numerical model used here has been validated with different steady-state cases in an earlier study. In the model, the cabinet is made up of different parts such as: IT equipment (servers and server simulator), multifunction rear door, heat exchanger box, recirculation deflector and side panels. Each part is characterized and validated based on experimental results. The total heat that was generated by the IT is removed by a V-shaped heat exchanger that is located within the cabinet. The performance of the system was investigated at different operational stages.

The main challenge in understanding the cooling performance in a legacy data center is the invisible transport medium (air). This emphasizes the need for smart and meticulous measurement techniques. However, the nature of measurements is finite (e.g. top, middle and bottom) and the variation between often non-linear, therefore to capture the gradients between measured points a validated CFD simulation is needed. In this paper a brief description of an experimental characterization of a new data center lab is discussed. Airflow and temperature measurements are utilized to understand the facility's performance at different operational stages, until reaching the designed capacity. Since the facility houses a wide range of different IT equipment (servers, switches, storage and blades), it is important to understand the airflow demand of each. To do that, each type of IT was tested separately and flow characteristics were obtained (i.e. free delivery, critical pressure and flow curves). In the second part, all the characterization data is integrated via compact models into a full CFD simulation. The measured points are used for validation and the full field of air temperature and flow is resolved. Both the measurements and simulation data will now be used to answer important design, deployment and operational change questions.

In cold aisle containment (CAC) the supply of cold air is separated within the contained volume. The hot air exhaust leaves the IT and increases the room’s temperature before returning to the cooling unit. On the other hand, hot aisle containment (HAC) generates a cooler environment in the data center room as a whole by segregating hot air within the containment. Hot air is routed back to the cooling unit return by a drop ceiling or a chimney. Each system has different characteristics and airflow paths. For instance, leakage introduces different effects for CACs and HACs since the hot and cold aisles are switched. This article utilizes data center measurements and containment characterization carried out circa April 2015 in the ES2 Data Center lab at Binghamton University. Details on the containment model include leakages at below racks, above racks, below CAC doors, between doors, and above doors. The model deploys the experimentally obtained flow curves approach for flow-pressure correlation. Data center operators rely on the pressure differential to measure how much the IT is provided. Hence, in this study the level of provisioning was expressed in terms of pressure differentials between the hot and cold aisles. In this manner the model reflected real-life DC thermal management practices. This was done by integrating a pressure differential based controller to the cooling unit model. Leakages in each system are quantified and ranked based on a proposed LIF (Leakage Impact Factor) metric. The LIF describes the transport contribution each leakage location has. This metric can be used by containment designers and data center operators to prioritize their sealing efforts or consider deploying the containment solution differently. Finally, a systematic approach is shown in which containment models can be used to optimize operations at the real-life site.

This paper presents the development of a neural network model of the server temperature to be used in model-based control of a data center. Data centers provide the optimal environments for operation of servers and storage devices. Conventionally, computational fluid dynamics (CFD) has been used to model the dynamic and complex environment of the data center. However, the drawback of this approach is its computational inefficiency. The effects of changing a single input may take an entire day to compute. Thus the CFD model is not well suited for model-based control. Instead, we propose to use an artificial Neural Network (NN) model which predicts server temperatures in significantly less time. In addition, this NN model has the capability of learning the environment in the data center by adapting its parameters in real time based on sensor data continuously taken from the data center. This work discusses the current development of the neural network, work being done at the University of Texas at Arlington, to include modeling of transient conditions, or time related changes, using data generated in a test bed Data Center at SUNY Binghamton.Copyright © 2015 by ASME

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.

Because of the rapid growth in the number of data centers combined with the high density heat dissipation in the IT and telecommunications equipment, energy efficient thermal management of data centers has become a key research focus in the electronics packaging community. Traditional legacy data centers still rely largely on chilled air flow delivered to the IT equipment racks through perforated tiles from the raised floor plenum. When there is large variation in the amount of heat dissipated by the racks in a given aisle, the standard air cooling approach requires over-provisioning. Localized hybrid air-water cooling is one approach to more effectively control the cooling when there is wide variation in the amount of dissipation in neighboring racks. In a closed hybrid air-water cooled server cabinet, the generated heat is removed by a self-contained system that does not interact with the room level air cooling system. In this study, a comprehensive procedure for CFD validation in a close coupled hybrid cooled enclosed cabinet is described. The commercial enclosure has been characterized experimentally in an earlier study, where the effectiveness values were applied as boundary conditions to the compact heat exchanger model. Here, the previously obtained experimental data are used to validate the results from computational modeling. Two cases with different air flow rates are compared. Very good agreement is achieved, with the maximum overall average error less than 4%. Due to relatively high pressure inside the cabinet, it is possible that air leakage from the cabinet may be responsible for the discrepancy between the model and experimental results. A sensitivity study was applied to the validated model to investigate the effect leakage had on the cabinet’s performance.

As the number of data centers is exponentially growing globally, pragmatic characterization schemes are considered to be a necessity for measuring and modeling the load capacity and flow pattern of the facility. This paper contains experimental and numerical characterization of a new data center laboratory using practical measurements methods, including tiles and CRAH flow measurements. Then a full physics based CFD model is built to simulate/predict the measured data. A rapid flow curve method is used showing high accuracy and low computational expense. Detailed descriptions of the data center structure, dimensions, layout (Appendix, A-1) and flow devices are given. Also, modeling parameters are mentioned in details to provide a baseline for any investigative parametric or sensitivity studies. Four experimental room level flow constraint scenarios are applied at which measurements were taken, (Appendix, A-2). The model is then built and calibrated then used to predict measurements. Measurements of the cooling unit were performed using hot wire anemometry with a traverse duct installed at the top of the CRAH. The tiles measurements were carried out using a flow hood with back pressure compensation. A detailed CFD model is constructed to predict the four experimental cases. For modeling the interdependency between the flow and pressure in flow devices flow curve approach is used. This is a rapid modeling technique that relies on experimentally measured (for IT) or approximated (for CRAH) flow curves. Applying the operational flow curves boundary conditions at the vents of the flow device results in a very accurate simulation model. It is also shown that the flow curves can be used to predict the real-time flow rate of servers at known RPM. This greatly simplifies flow rate measurements of IT in the data center.

This study illustrates basic guidelines for integrating empirical measurements to state of the art modeling approaches; that can be used to improve the accuracy of physics based data center CFD models. Experimental measurements gathered in a new research dedicated data center laboratory are used to guide an advanced approach to CFD modeling, the intent is to come up with a validated predictive model of the data center. One of the goals of this study is to provide scientists and engineers with a clear set of design guidelines; that allow for the introduction of important physical details into the model which have previously been largely overlooked. This approach will establish a valid baseline for future designs of data centers as well as future research projects in the data center laboratory. The current CFD model incorporates important physical parameters that affect the accuracy of the results. These include the plenum floor jacks' hydraulic resistance, the impact of cutouts, exact locations of supply vents, CRAH (computer room air handler) unit blower jet effects and momentum transfer through the perforated tiles. Other details of the CRAH unit such as the detailed supply vents, blower specifications, turning vent and angle of flow are included; also rack detailed structure including the mounting rails, cable penetration and PDUs (power distribution units). CFD modeling results are compared to the measured tiles flow rates from several different experimental conditions. The models were refined based on the experimental data and comparisons of the CFD versus experimental tiles flow data showed an overall average error of –3%.

A water-cooled, fully-enclosed server cabinet is one type of hybrid cooling technology used in data centers to cool high power IT equipment. These types of cabinets employ a water/air heat exchanger. External chilled water is provided to the heat exchanger and circulating air inside the cabinet is supplied to the server intakes. One advantage of this type of hybrid system is that the heat removed by the water-side can be used for other purposes, which is a potential means for increasing the overall data center energy efficiency. A specific commercial hybrid server cabinet design has been characterized experimentally in this study. The cabinet utilizes a V-shaped, unmixed-unmixed liquid-to-air cross flow heat exchanger. Three robust rear door mounted fans produce the air circulation in the cabinet. They are capable of providing an air flow rate of up to 1.321m3/s (2800 CFM) depending on the air temperature inside the cabinet. In the experiments, the air velocity is measured at different positions at the inlet and outlet of the heat exchanger using an array of velocity sensors. The contribution of each fan to the airflow distribution at the inlet of the heat exchanger is characterized using the measured air velocity data. For the water-side, the flow rate and temperature of the chilled water supply is measured using a vortex flow meter. From the measured air and water flow rates and temperatures, the effectiveness of the heat exchanger is calculated. The experimental results are presented in terms of effectiveness curves for different air and water operating flow rates and the high performance V-shaped heat exchanger is characterized in detail using these results. The heat exchanger performance data provides a better understanding of the design and operation of this type of closed cabinet, which can be used to potentially improve the operating efficiency.

Water-cooled server racks are typically closed cabinets, so no heat load is removed by the room cooling system in a raised floor data center. Instead, the cooling is provided by a closed system employing an air-water (fin-tube) heat exchanger. This kind of heat exchanger uses chilled water from a central plant, and there is the potential of using the waste heat that is returned. The goal of this study is characterize a specific sealed-door, water-cooled server cabinet under steady state and transient operation. The experimental part of the study is being performed on a Knurr CoolThermTM® rack. In this cabinet, the water/air heat exchanger is located at the bottom. Cooling air is circulated by three rear door mounted fans, the cooled air flows upward in front of the servers. The specific cabinet being tested has the capability to handle 25 kW and has a 30% cooling system energy efficiency. In the experiments, 16 1U servers and a 9U load bank are employed for generating a heat load. Over 100 thermocouples are used to monitor air temperature within different parts of the cabinet. The operating conditions monitored include: water flow rate, water inlet temperature, air flow rate through the servers, air flow rate through the heat exchanger, air temperatures and server power. The internal temperature of the servers is also monitored. From the measured data, the effectiveness is calculated for four different water flow rates and different power dissipation levels. Computational modeling of the air flow and heat transfer in a simplified model of the cabinet is also performed.

To determine the relationship between elevated liver enzymes with iron overload and viral hepatitis in thalassemic patients.This descriptive cross-sectional study was carried out in the thalassemic ward of Tonekabon Hospital, Mazandaran, Northern Iran from 20 April to 20 September of 2006. Patients were studied with respect to age, liver enzymes, anti-hepatitis C virus (anti-HCV) antibody, and hepatitis B surface antigen (HBsAg), transferrin saturation (TSAT), and blood transfusion index (multiplication of frequency and units of transfusion). Alanine aminotransferase (ALT)or =40 U/L was considered elevated.Sixty-five patients were evaluated (median age 19.51+/-8.9 years, range 4-54). Eleven patients were anti-HCV positive (16.9%). The mean serum ferritin was significantly higher in patients with ALTor =40 (2553.08 ug/L versus 1783.7750 microg/L) (p=0.012). The mean ALT was significantly higher in patients with TSATor = 60% (41.26 U/L versus 28.82 U/L) (p=0.021). The relationship between ALTor =40 and anti-HCV positivity was statistically significant. The mean ALT was 60.91 U/L in anti-HCV positive patients and 39.29 U/L in the negative group (p=0.001). The mean serum iron and transfusion index were significantly higher in anti-HCV positive versus negative patients (234.0 versus 195.4815; p=0.02), (1693.6 versus 1036.29, p=0.014).Close association between elevated ALT with iron overload, transfusion index, age, and anti-HCV positivity in thalassemic patients of Tonekabon is recommended to re-evaluate transfusion and Desferal doses and therapies other than blood transfusion.

An important issue that absorbs many attentions is studying the users’ required information and their pattern of dynamic interaction with online search. The aim of this study is to identify the relationship between users’ cognitive style and information seeking. It is to enhance the quality of information presentation and users’ interactions in the Web by adapting their preferences and specific needs. This paper specifically focuses on the use of the Internet by postgraduate engineering students. The sample of this study consists of 50 postgraduate engineering students from the Faculty of Computer Science and Information System in Universiti Teknologi Malaysia. The findings of this study reveal the linear relationship between users’ cognitive styles and information seeking.