Open and Contained Cold Aisle Experimentally Validated CFD Model Implementing CRAC and Server Fan Curves for a Data Center Test Laboratory

2013 ◽  
Author(s):  
Sami A. Alkharabsheh ◽  
Bharathkrishnan Muralidharan ◽  
Mahmoud Ibrahim ◽  
Saurabh K. Shrivastava ◽  
Bahgat G. Sammakia
Keyword(s):  
Data Center ◽  
Average Error ◽  
Inlet Temperature ◽  
Cfd Model ◽  
Flow Measurements ◽  
Flow Rates ◽  
System Calibration ◽  
Equivalent Models ◽  
Tile Flow ◽  
Good Agreement

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). Open and contained cold aisle systems are considered experimentally and numerically. This work is divided into open (uncontained) cold aisle system calibration and validation, and fully contained cold aisle system calibration and leakage characterization. In the open system, the CRAC unit is calibrated using the manufacturer fan curve. Tiles flow measurements are used to calibrate the floor leakage. The fan curves of the load banks are generated experimentally. A full physics based model of the system is validated with two different CRAC fan speeds. The results showed a very good agreement with the tile flow measurements, with an approximate average error of 5%, indicating that the average model prediction of the tile flow is five percent lower that the measured values. In the fully contained cold aisle system, a detailed containment CFD model based on experimental measurements is developed. The model is validated by comparing the flow rate through the perforated floor tiles with the experimental measurements. The CFD results are in a good agreement with the experimental data. The average error is about 6.7%. Temperature measurements are used to calibrate other sources of containment and racks leaks including mounting rails and clearance between racks. The temperature measurements and the CFD results agree well with average error less than 2%. Detailed and equivalent modeling methods for the floor and containment system are investigated. It is found that the simple equivalent models are able to predict the flow rates however they did not succeed in providing detailed fluid flow information. While the detailed models succeeded in explaining the physical phenomena and predicting the flow rates with noticeable tradeoffs regarding the computational time. Important conclusions can be drawn from this study. In order to accurately model the containment system, both the CRAC and the load banks fan curves should be simulated in the numerical model. Unavoidable racks and containment leaks could cause inlet temperature increase even if the cold aisle is overprovisioned with cold air. It is also noted that heat conduction through the floor tiles causes a slight increase the inlet temperature of the cold aisles. Finally, it is noteworthy that using detailed modeling is necessary to understand the details of the thermal systems, however simpler and faster to compute equivalent models can be used in extended optimization studies that show relative rankings of different designs.

Experimentally Validated Computational Fluid Dynamics Model for Data Center With Active Tiles

2018 ◽  
Vol 140 (1) ◽  
Author(s):  
Jayati Athavale ◽  
Yogendra Joshi ◽  
Minami Yoda
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Flow Rate ◽  
Data Center ◽  
Hot Spot ◽  
Volume Flow Rate ◽  
Optimal Number ◽  
Inlet Temperature ◽  
Cfd Model ◽  
Level Model

Abstract This paper presents an experimentally validated room-level computational fluid dynamics (CFD) model for raised-floor data center configurations employing active tiles. Active tiles are perforated floor tiles with integrated fans, which increase the local volume flow rate by redistributing the cold air supplied by the computer room air conditioning (CRAC) unit to the under-floor plenum. The numerical model of the data center room consists of one cold aisle with 12 racks arranged on both sides and three CRAC units sited around the periphery of the room. The commercial CFD software package futurefacilities6sigmadcx is used to develop the model for three configurations: (a) an aisle populated with ten (i.e., all) passive tiles; (b) a single active tile and nine passive tiles in the cold aisle; and (c) an aisle populated with all active tiles. The predictions from the CFD model are found to be in good agreement with the experimental data, with an average discrepancy between the measured and computed values for total flow rate and rack inlet temperature less than 4% and 1.7 °C, respectively. The validated models were then used to simulate steady-state and transient scenarios following cooling failure. This physics-based and experimentally validated room-level model can be used for temperature and flow distributions prediction and identifying optimal number and locations of active tiles for hot spot mitigation in data centers.

Evaluation of a Data Center Recirculation Non-Uniformity Metric Using Computational Fluid Dynamics

2011 ◽  
Author(s):  
Dustin W. Demetriou ◽  
H. Ezzat Khalifa
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Simple Model ◽  
Temperature Rise ◽  
Data Center ◽  
Large Temperature ◽  
Inlet Temperature ◽  
Temperature Pattern ◽  
Cfd Analysis ◽  
Tile Flow

The work presented in this paper is an extension of the companion work by the authors on a simplified thermodynamic model for data center optimization, in which a recirculation non-uniformity metric, θ, was introduced and used in a parametric analysis to highlight the deleterious effect of recirculation non-uniformity at the inlet of racks on the data center cooling infrastructure power consumption. In this work, several studies are done using a commercial computational fluid dynamics (CFD) package to verify many of the assumptions necessary in the development of the simplified model and to understand the degree of recirculation non-uniformity present in typical data center configurations. A number of CFD simulations are used to quantify the ability of the simple model at predicting θ. The results show that the simple model provides a fairly accurate estimate of θ, with a standard deviation in the prediction error of ∼10–15%. The CFD analysis are also to understand the effect of row length and server temperature rise (ΔTs) temperature non-uniformity. The simulations show that reasonable values of θ range from 2–6 for open aisle data centers depending on operating strategy and data center layout. As a means to understand the effect of buoyancy, a data center Archimedes number (Ar), the ratio of buoyancy to inertia forces, is introduced as a function of tile flow rate and server temperature rise. For servers with modest temperature rise (∼ 10.0°C), Ar is ∼0.1; however, for racks with large temperature rise (∼20°C), Ar > 1.0, meaning buoyancy needs to be considered important. Through CFD analysis the significant effect buoyancy has on the inlet rack temperature patterns is highlighted. The Capture Index (ψ), the ratio of cold air ingested by the racks to the required rack flow, is used to investigate its relationship to the ratio of server flow to tile flow (Y), as the inlet rack temperature patterns are changed by increased Ar. The results show that although the rack inlet temperature patterns are extremely different, ψ does not change significantly as a function of Ar. Lastly, the effect of buoyancy on the assumption of linearity of the temperature field is considered for a range of Ar. The results show the emergence of a stratified temperature pattern at the inlet of the racks as Ar increases and buoyancy becomes more important. It is concluded that under these conditions, a δT change in tile temperature does not produce a δT change in temperature everywhere in the field.

scholarly journals Numerical and Experimental Investigations of the Cavitating Behavior of an Inducer

2004 ◽  
Vol 10 (1) ◽  
pp. 15-25 ◽  
Author(s):  
F. Bakir ◽  
R. Rey ◽  
A. G. Gerber ◽  
T. Belamri ◽  
B. Hutchinson
Keyword(s):  
Bubble Dynamics ◽  
Three Dimensional ◽  
Experimental Investigations ◽  
Cfd Model ◽  
Flow Rates ◽  
Solution Approach ◽  
Robust Solutions ◽  
Density Ratios ◽  
Scalar Equations ◽  
Good Agreement

A robust CFD model is described, suitable for general three-dimensional flows with extensive cavitation at large density ratios. The model utilizes a multiphase approach, based on volume-scalar-equations, a truncated Rayleigh-Plesset equation for bubble dynamics, and specific numerical modifications (in a finite-volume solution approach) to promote robust solutions when cavitation is present. The model is implemented in the CFD software CFX TASCflow 2.12. The validation of the model was done on an inducer designed and tested at LEMFI. First, The physical model and the numerical aspects are described. Then, the experimental and numerical methodologies, at cavitating regime, are presented. Finally, for several flow rates, the comparisons between experimental and simulated results on the overall performances, head drop and cavitation figures, are discussed. For a range of flow rates, good agreement between experiment and prediction was found.

Improved Zonal Model for Data Center Analysis

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

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

Effect of Supply Air Temperature on Rack Cooling in a High Density Raised Floor Data Center Facility

2011 ◽  
Author(s):  
Pramod Kumar ◽  
Vikneshan Sundaralingam ◽  
Yogendra Joshi ◽  
Michael K. Patterson ◽  
Robin Steinbrecher ◽  
...  
Keyword(s):  
Flow Field ◽  
Air Temperature ◽  
Data Center ◽  
Flow Distribution ◽  
High Density ◽  
Flow Measurements ◽  
Air Inlet ◽  
Air Temperatures ◽  
Tile Flow ◽  
Temperature Maps

In this paper we experimentally investigate the effect of supply air temperature on rack cooling in a high density raised floor data center facility. A series of experiments are performed on a 42 U (1-U = 4.45 cm) rack populated with 1-U servers. Desired rack heat loads are achieved by managing the distribution of server compute load within the rack. During the present experiments, temperatures at various locations in the hot and cold aisle corresponding to the rack air inlet and outlet are recorded. The temperatures are measured using a grid consisting of 256 thermocouples. The temperature measurements are further complimented with the flow field at the rack inlet. Particle Image Velocimetry (PIV) technique is used to capture the flow field at the rack inlet. The temperature maps in concert with the PIV flow field help in quantifying the rack cooling effectiveness. The temperature and flow measurements are measured for various cases by altering the supply air temperatures and perforated tile flow rates. The results are analyzed and compared with the ASHRARE recommended guidelines to arrive at the optimum supply air temperature. A perceptible change in the temperature and flow distribution is observed for the six cases investigated.

Creating a Calibrated CFD Model of a Midsize Data Center

2015 ◽  
Author(s):  
Zachary M. Pardey ◽  
James W. VanGilder ◽  
Christopher M. Healey ◽  
David W. Plamondon
Keyword(s):  
Data Center ◽  
Real Data ◽  
Measured Data ◽  
Cfd Modeling ◽  
Design Stage ◽  
Cfd Model ◽  
Modeling Techniques ◽  
Room Model ◽  
Tile Flow ◽  
Level Of Agreement

Calibrating a CFD model against measured data is the first step to successfully utilizing this technology for change-management and the optimization of an existing data center. To date, there has been very little published on this calibration process; more focus has been placed on the use of CFD at the design stage and the development of modeling techniques and solvers. Further, few studies which feature comprehensive comparisons of CFD-predicted and measured data have been published for real data centers, and many that have, demonstrated only modest agreement at best. This study provides another such comparison — for a 7,400 ft2 (687 m2), 138-rack, raised-floor facility. The goals of the study are to benchmark the level of agreement that can be practically obtained and also to investigate the level of modeling detail required. Additionally, specific practical advice covering both CFD modeling and experimental measurements is provided. A plenum-only CFD model is compared to measured tile airflow rates and a room-model, which uses measured tile flow rates as boundary conditions, is compared to temperatures measured at each rack inlet. The level of agreement is among the best published to date and demonstrates that a CFD model can be adequately calibrated against measured data and is of value for ongoing data center operation.

Reduced Order Thermal Modeling of Data Centers via Distributed Sensor Data

2012 ◽  
Vol 134 (4) ◽  
Author(s):  
Emad Samadiani ◽  
Yogendra Joshi ◽  
Hendrik Hamann ◽  
Madhusudan K. Iyengar ◽  
Steven Kamalsy ◽  
...  
Keyword(s):  
Temperature Field ◽  
Data Center ◽  
Data Centers ◽  
Sensor Data ◽  
Temperature Fields ◽  
Average Error ◽  
Local Error ◽  
Flow Rates ◽  
Reduced Order ◽  
Distributed Sensor

In this paper, an effective and computationally efficient proper orthogonal decomposition (POD) based reduced order modeling approach is presented, which utilizes selected sets of observed thermal sensor data inside the data centers to help predict the data center temperature field as a function of the air flow rates of computer room air conditioning (CRAC) units. The approach is demonstrated through application to an operational data center of 102.2 m2 (1100 square feet) with a hot and cold aisle arrangement of racks cooled by one CRAC unit. While the thermal data throughout the facility can be collected in about 30 min using a 3D temperature mapping tool, the POD method is able to generate temperature field throughout the data center in less than 2 s on a high end desktop personal computer (PC). Comparing the obtained POD temperature fields with the experimentally measured data for two different values of CRAC flow rates shows that the method can predict the temperature field with the average error of 0.68 °C or 3.2%. The maximum local error is around 8 °C, but the total number of points where the local error is larger than 1 °C, is only ∼6% of the total domain points.

Reduced Order Thermal Modeling of Data Centers via Distributed Sensor Data

2009 ◽  
Author(s):  
Emad Samadiani ◽  
Yogendra Joshi ◽  
Hendrik Hamann ◽  
Madhusudan K. Iyengar ◽  
Steven Kamalsy ◽  
...  
Keyword(s):  
Temperature Field ◽  
Data Center ◽  
Data Centers ◽  
Sensor Data ◽  
Temperature Fields ◽  
Average Error ◽  
Flow Rates ◽  
Reduced Order ◽  
Distributed Sensor ◽  
Mapping Tool

In this paper, an effective and computationally efficient Proper Orthogonal Decomposition (POD) based reduced order modeling approach is presented, which utilizes selected sets of observed thermal sensor data inside the data centers to help predict the data center temperature field as a function of the air flow rates of Computer Room Air Conditioning (CRAC) units. The approach is demonstrated through application to an operational data center of 102.2 m2 (1,100 square feet) with a hot and cold aisle arrangement of racks cooled by one CRAC unit. While the thermal data throughout the facility can be collected in about 30 minutes using a 3D temperature mapping tool, the POD method is able to generate temperature field throughout the data center in less than 2 seconds on a high end desktop PC. Comparing the obtained POD temperature fields with the experimentally measured data for two different values of CRAC flow rates shows that the method can predict the temperature field with the average error of 0.68 °C or 3.2%.

Numerical Modeling of Perforated Tile Flow Distribution in a Raised-Floor Data Center

2010 ◽  
Vol 132 (2) ◽  
Author(s):  
Emad Samadiani ◽  
Jeffrey Rambo ◽  
Yogendra Joshi
Keyword(s):  
Numerical Modeling ◽  
Flow Rate ◽  
Data Center ◽  
Air Conditioning ◽  
Flow Distribution ◽  
Air Flow Rate ◽  
Flow Rates ◽  
Average Change ◽  
Tile Flow ◽  
Operating Points

This paper is centered on quantifying the effect of computer room and computer room air conditioning (CRAC) unit modeling on the perforated tile flow distribution in a representative raised-floor data center. Also, this study quantifies the effect of plenum pipes and perforated tile porosity on the operating points of the CRAC blowers, total CRAC air flow rate, and its distribution. It is concluded that modeling the computer room, the CRAC units, and/or the plenum pipes could make an average change of up to 17% in the tile flow rates with a maximum of up to 135% for the facility with 56% open tiles while the average and maximum changes for the facility with 25% open tiles are 6% and 60%, respectively.

Improved Computational Fluid Dynamics Model for Open-Aisle Air-Cooled Data Center Simulations

2013 ◽  
Vol 135 (3) ◽  
Author(s):  
Waleed A. Abdelmaksoud ◽  
Thong Q. Dang ◽  
H. Ezzat Khalifa ◽  
Roger R. Schmidt
Keyword(s):  
High Power ◽  
Data Center ◽  
Large Scale ◽  
Source Model ◽  
Cfd Modeling ◽  
Small Data ◽  
Cfd Model ◽  
It Industry ◽  
Cfd Models ◽  
Tile Flow

There is a need in the IT industry for CFD models that are capable of accurately predicting the thermal distributions in high power density open-aisle air-cooled data centers for use in the design of these facilities with reduced cooling needs. A recent detailed evaluation of a small data center cell equipped with one high power rack using current CFD practice showed that the CFD results were not accurate. The simulation results exhibited pronounced hot/cold spots in the data center while the test data were much more diffused, indicating that the CFD model under-predicted the mixing process between the cold tile flow and the hot rack exhaust flow with the warm room air. In this study, a parametric study was carried out to identify CFD modeling issues that contributed to this error. Through a combined experimental and computational investigation, it was found that the boundary condition imposed at the perforated surfaces (e.g., perforated tiles and rack exhaust door) as fully open surfaces was the main source of error. This method enforces the correct mass flux but the initial jet momentum is under-specified. A momentum source model proposed for these perforated surfaces is found to improve the CFD results significantly. Another CFD modeling refinement shown to improve CFD predictions is the inclusion of some large-scale geometrical features of the perforated surfaces (e.g., lands/gaps) in the CFD model, but this refinement requires the use of grids finer than those typically used in practice.

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