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.

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.

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

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

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

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.

Improved CFD modeling of a small data center test cell

2010 ◽  
Author(s):  
Waleed A. Abdelmaksoud ◽  
H. Ezzat Khalifa ◽  
Thong Q. Dang ◽  
Roger R. Schmidt ◽  
Madhusudan Iyengar
Keyword(s):  
Data Center ◽  
Test Cell ◽  
Cfd Modeling ◽  
Small Data

Cluster of High-Powered Racks Within a Raised-Floor Computer Data Center: Effect of Perforated Tile Flow Distribution on Rack Inlet Air Temperatures

2004 ◽  
Vol 126 (4) ◽  
pp. 510-518 ◽  
Author(s):  
Roger Schmidt ◽  
Ethan Cruz
Keyword(s):  
Data Center ◽  
Control Volume ◽  
Flow Distribution ◽  
Computer Code ◽  
Cfd Model ◽  
Computer Data ◽  
Air Temperatures ◽  
Finite Control ◽  
Computational Fluid Dynamics Cfd ◽  
Tile Flow

This paper focuses on the effect on rack inlet air temperatures as a result of maldistribution of airflows exiting the perforated tiles located adjacent to the fronts of the racks. The flow distribution exiting the perforated tiles was generated from a computational fluid dynamics (CFD) tool called Tileflow (trademark of Innovative Research, Inc.). Both raised floor heights and perforated tile-free areas were varied in order to explore the effect on rack inlet temperatures. The flow distribution exiting the perforated tiles was used as boundary conditions to the above-floor CFD model. A CFD model was generated for the room with electronic equipment installed on a raised floor. Forty racks of data processing (DP) equipment were arranged in rows in a data center cooled by chilled air exhausting from perforated floor tiles. The chilled air was provided by four A/C units placed inside a room 12.1 m wide×13.4 m long. Because the arrangement of the racks in the data center was symmetric, only half of the data center was modeled. The numerical modeling for the area above the raised floor was performed using a commercially available finite control volume computer code called Flotherm (trademark of Flomerics, Inc.). The flow was modeled using the k-e turbulence model. Results are displayed to provide some guidance on the design and layout of a data center.

Cluster of High Powered Racks Within a Raised Floor Computer Data Center: Effect of Perforated Tile Flow Distribution on Rack Inlet Air Temperatures

2003 ◽  
Author(s):  
Roger Schmidt ◽  
Ethan Cruz
Keyword(s):  
Data Center ◽  
Control Volume ◽  
Flow Distribution ◽  
Computer Code ◽  
Cfd Model ◽  
Computer Data ◽  
Air Temperatures ◽  
Finite Control ◽  
Computational Fluid Dynamics Cfd ◽  
Tile Flow

This paper focuses on the effect on inlet rack air temperatures as a result of maldistribution of airflows exiting the perforated tiles located adjacent to the fronts of the racks. The flow distribution exiting the perforated tiles was generated from a computational fluid dynamics (CFD) tool called Tileflow (Trademark of Innovative Research, Inc.). Both raised floor heights and perforated tile free area were varied in order to explore the effect on rack inlet temperatures. The flow distribution exiting the perforated tiles was used as boundary conditions to the above floor CFD model. A CFD model was generated for the room with electronic equipment installed on a raised floor. Fourty racks of data processing (DP) equipment were arranged in rows in a data center cooled by chilled air exhausting from perforated floor tiles. The chilled air was provided by four A/C units placed inside a room 12.1 m wide × 13.4 m long. Since the arrangement of the racks in the data center was symmetric only one-half of the data center was modeled. The numerical modeling for above the raised floor was performed using a commercially available finite control volume computer code called Flotherm (Trademark of Flomerics, Inc.). The flow was modeled using the k-e turbulence model. Results are displayed to provide some guidance on the design and layout of a data center.

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

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

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

Circulating Fluidized Beds

2010 ◽  
pp. 316-358
Author(s):  
Ray Cocco ◽  
S.B. Reddy Karri ◽  
Ted Knowlton
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Large Scale ◽  
Cfd Modeling ◽  
Circulating Fluidized Beds ◽  
Cfd Models ◽  
Unit Operations ◽  
Computational Fluid Dynamics Cfd

In the last 20 years, significant improvements in the computational fluid dynamics (CFD) modeling have been made that allow the simulation of large-scale, commercial CFBs. Today, commercial codes are available that can model some of this behavior in large-scale, commercial units in a reasonable amount of time. However, the hydrodynamics in a riser or fluidized bed are complex with both micro and macroscale features. From particle clustering to large streamers to the core-annulus profile, the particle behavior in these unit operations rarely behaves as a “continuous fluid.” Even the role of particle size distribution is often neglected and models that do consider particle size distribution don’t always consider the role of particle size on granular temperature. Many models use insufficient boundary conditions by assuming uniform or symmetric profiles, which is rarely the case. Furthermore, grid sizing is usually based on computer limitations instead of model limitations, and many models of commercial systems extend beyond the capability of the constitutive equations being used. Successful application of today’s CFD models requires a good understanding of the equations behind the code, the assumptions used for those equations and the capability or limitations of the code. CFD is nothing more than a guess without an understanding of the fundamentals, underlying assumptions and code limitations that are part of every model.

On the Computations of Flow Regimes and Thermal Patterns in Large Scale High Compute Density Data Centers

2013 ◽  
Author(s):  
Essam E. Khalil ◽  
Mena H. Aziz
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
High Power ◽  
Data Center ◽  
Power Dissipation ◽  
Large Scale ◽  
Data Centers ◽  
Computer Systems ◽  
Cfd Modelling ◽  
Density Data

High power dissipation from microprocessors, support chips, memory chips and mass storage has resulted in large overall power dissipation from computer systems. The deployment of these computer systems in large numbers and in very dense configurations in a data center had resulted in very high power densities at room level. These computer systems are deployed in a rack. A standard 2-meter high rack can accommodate an equivalent of 34 thin desktop systems. If the maximum power dissipation from each system is 300W, a single rack in a data center can be assumed to dissipate 7.2 KW. A data center can have hundreds of these 7.2 KW racks. Due to such high heat loads, designing the air conditioning system in a data center using simple energy balance is no longer adequate. Moreover, the data center design cannot rely on intuitive design of air distribution. It is necessary to model the airflow and temperature distribution in a data center. In this paper, a computational fluid dynamics model of a prototype data center is presented to make the case for such modeling. The present paper is devoted to investigate the air flow patterns, temperatures and relative humidity in large compute density data centers. Computational fluid dynamics software is utilized to simulate the data center flow pattern. The paper used the simulation techniques as embedded in the commercially available CFD code (FLUENT 6.2). The CFD modelling techniques solved the continuity, momentum and energy conservation equations in addition to standard k–ε model equations for turbulence closure.

scholarly journals HTPC: heterogeneous traffic-aware partition coding for random packet spraying in data center networks

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Jiawei Huang ◽  
Shiqi Wang ◽  
Shuping Li ◽  
Shaojun Zou ◽  
Jinbin Hu ◽  
...  
Keyword(s):  
Data Center ◽  
Large Scale ◽  
Network Performance ◽  
Rooted Tree ◽  
Heterogeneous Traffic ◽  
Data Center Networks ◽  
Packet Reordering ◽  
Traffic Characteristics ◽  
Network Utilization ◽  
The Impact

AbstractModern data center networks typically adopt multi-rooted tree topologies such leaf-spine and fat-tree to provide high bisection bandwidth. Load balancing is critical to achieve low latency and high throughput. Although the per-packet schemes such as Random Packet Spraying (RPS) can achieve high network utilization and near-optimal tail latency in symmetric topologies, they are prone to cause significant packet reordering and degrade the network performance. Moreover, some coding-based schemes are proposed to alleviate the problem of packet reordering and loss. Unfortunately, these schemes ignore the traffic characteristics of data center network and cannot achieve good network performance. In this paper, we propose a Heterogeneous Traffic-aware Partition Coding named HTPC to eliminate the impact of packet reordering and improve the performance of short and long flows. HTPC smoothly adjusts the number of redundant packets based on the multi-path congestion information and the traffic characteristics so that the tailing probability of short flows and the timeout probability of long flows can be reduced. Through a series of large-scale NS2 simulations, we demonstrate that HTPC reduces average flow completion time by up to 60% compared with the state-of-the-art mechanisms.

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