IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i3p644-d136181.html
   My bibliography  Save this article

Computational Fluid Dynamics Modeling and Validating Experiments of Airflow in a Data Center

Author

Listed:
  • Emelie Wibron

    (Division of Fluid and Experimental Mechanics, Luleå University of Technology, SE-971 87 Luleå, Sweden)

  • Anna-Lena Ljung

    (Division of Fluid and Experimental Mechanics, Luleå University of Technology, SE-971 87 Luleå, Sweden)

  • T. Staffan Lundström

    (Division of Fluid and Experimental Mechanics, Luleå University of Technology, SE-971 87 Luleå, Sweden)

Abstract

The worldwide demand on data storage continues to increase and both the number and the size of data centers are expanding rapidly. Energy efficiency is an important factor to consider in data centers since the total energy consumption is huge. The servers must be cooled and the performance of the cooling system depends on the flow field of the air. Computational Fluid Dynamics (CFD) can provide detailed information about the airflow in both existing data centers and proposed data center configurations before they are built. However, the simulations must be carried out with quality and trust. The k – ε model is the most common choice to model the turbulent airflow in data centers. The aim of this study is to examine the performance of more advanced turbulence models, not previously investigated for CFD modeling of data centers. The considered turbulence models are the k – ε model, the Reynolds Stress Model (RSM) and Detached Eddy Simulations (DES). The commercial code ANSYS CFX 16.0 is used to perform the simulations and experimental values are used for validation. It is clarified that the flow field for the different turbulence models deviate at locations that are not in the close proximity of the main components in the data center. The k – ε model fails to predict low velocity regions. RSM and DES produce very similar results and, based on the solution times, it is recommended to use RSM to model the turbulent airflow data centers.

Suggested Citation

  • Emelie Wibron & Anna-Lena Ljung & T. Staffan Lundström, 2018. "Computational Fluid Dynamics Modeling and Validating Experiments of Airflow in a Data Center," Energies, MDPI, vol. 11(3), pages 1-15, March.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:3:p:644-:d:136181
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/3/644/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/11/3/644/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tatchell-Evans, Morgan & Kapur, Nik & Summers, Jonathan & Thompson, Harvey & Oldham, Dan, 2017. "An experimental and theoretical investigation of the extent of bypass air within data centres employing aisle containment, and its impact on power consumption," Applied Energy, Elsevier, vol. 186(P3), pages 457-469.
    2. Fulpagare, Yogesh & Bhargav, Atul, 2015. "Advances in data center thermal management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 981-996.
    3. Ebrahimi, Khosrow & Jones, Gerard F. & Fleischer, Amy S., 2014. "A review of data center cooling technology, operating conditions and the corresponding low-grade waste heat recovery opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 622-638.
    4. Luigi Ventola & Gabriele Curcuruto & Matteo Fasano & Saverio Fotia & Vincenzo Pugliese & Eliodoro Chiavazzo & Pietro Asinari, 2016. "Unshrouded Plate Fin Heat Sinks for Electronics Cooling: Validation of a Comprehensive Thermal Model and Cost Optimization in Semi-Active Configuration," Energies, MDPI, vol. 9(8), pages 1-16, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Isazadeh, Amin & Ziviani, Davide & Claridge, David E., 2023. "Global trends, performance metrics, and energy reduction measures in datacom facilities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 174(C).
    2. Cho, Jinkyun & Kim, Youngmo, 2021. "Development of modular air containment system: Thermal performance optimization of row-based cooling for high-density data centers," Energy, Elsevier, vol. 231(C).
    3. Yeliang Qiu & Congfeng Jiang & Yumei Wang & Dongyang Ou & Youhuizi Li & Jian Wan, 2019. "Energy Aware Virtual Machine Scheduling in Data Centers," Energies, MDPI, vol. 12(4), pages 1-21, February.
    4. Rickard Brännvall & Jonas Gustafsson & Fredrik Sandin, 2023. "Modular and Transferable Machine Learning for Heat Management and Reuse in Edge Data Centers," Energies, MDPI, vol. 16(5), pages 1-24, February.
    5. Jinkyun Cho & Jesang Woo & Beungyong Park & Taesub Lim, 2020. "A Comparative CFD Study of Two Air Distribution Systems with Hot Aisle Containment in High-Density Data Centers," Energies, MDPI, vol. 13(22), pages 1-19, November.
    6. Emelie Wibron & Anna-Lena Ljung & T. Staffan Lundström, 2019. "Comparing Performance Metrics of Partial Aisle Containments in Hard Floor and Raised Floor Data Centers Using CFD," Energies, MDPI, vol. 12(8), pages 1-17, April.
    7. Chu, Wen-Xiao & Wang, Chi-Chuan, 2019. "A review on airflow management in data centers," Applied Energy, Elsevier, vol. 240(C), pages 84-119.
    8. Du, Yahui & Zhou, Zhihua & Yang, Xiaochen & Yang, Xueqing & Wang, Cheng & Liu, Junwei & Yuan, Jianjuan, 2023. "Dynamic thermal environment management technologies for data center: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chu, Wen-Xiao & Wang, Chi-Chuan, 2019. "A review on airflow management in data centers," Applied Energy, Elsevier, vol. 240(C), pages 84-119.
    2. Di Salvo, André L.A. & Agostinho, Feni & Almeida, Cecília M.V.B. & Giannetti, Biagio F., 2017. "Can cloud computing be labeled as “green”? Insights under an environmental accounting perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 514-526.
    3. Jerez Monsalves, Juan & Bergaentzlé, Claire & Keles, Dogan, 2023. "Impacts of flexible-cooling and waste-heat recovery from data centres on energy systems: A Danish case study," Energy, Elsevier, vol. 281(C).
    4. Zhang, Yingbo & Shan, Kui & Li, Xiuming & Li, Hangxin & Wang, Shengwei, 2023. "Research and Technologies for next-generation high-temperature data centers – State-of-the-arts and future perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 171(C).
    5. Moazamigoodarzi, Hosein & Tsai, Peiying Jennifer & Pal, Souvik & Ghosh, Suvojit & Puri, Ishwar K., 2019. "Influence of cooling architecture on data center power consumption," Energy, Elsevier, vol. 183(C), pages 525-535.
    6. Shuja, Junaid & Gani, Abdullah & Shamshirband, Shahaboddin & Ahmad, Raja Wasim & Bilal, Kashif, 2016. "Sustainable Cloud Data Centers: A survey of enabling techniques and technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 195-214.
    7. Lan, Yun Cheng & Li, Cheng & Wang, Sui Lin, 2019. "Parabolic antenna snow melting and removal using waste heat from the transmitter room," Energy, Elsevier, vol. 181(C), pages 738-744.
    8. Utlu, Zafer, 2015. "Investigation of the potential for heat recovery at low, medium, and high stages in the Turkish industrial sector (TIS): An application," Energy, Elsevier, vol. 81(C), pages 394-405.
    9. Cheng Liu & Hang Yu, 2021. "Evaluation and Optimization of a Two-Phase Liquid-Immersion Cooling System for Data Centers," Energies, MDPI, vol. 14(5), pages 1-21, March.
    10. Silva-Llanca, Luis & Ortega, Alfonso & Fouladi, Kamran & del Valle, Marcelo & Sundaralingam, Vikneshan, 2018. "Determining wasted energy in the airside of a perimeter-cooled data center via direct computation of the Exergy Destruction," Applied Energy, Elsevier, vol. 213(C), pages 235-246.
    11. Twaha, Ssennoga & Zhu, Jie & Yan, Yuying & Li, Bo, 2016. "A comprehensive review of thermoelectric technology: Materials, applications, modelling and performance improvement," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 698-726.
    12. Ljungqvist, Hampus Markeby & Mattsson, Louise & Risberg, Mikael & Vesterlund, Mattias, 2021. "Data center heated greenhouses, a matter for enhanced food self-sufficiency in sub-arctic regions," Energy, Elsevier, vol. 215(PB).
    13. Hrvoje Dorotić & Kristijan Čuljak & Josip Miškić & Tomislav Pukšec & Neven Duić, 2022. "Technical and Economic Assessment of Supermarket and Power Substation Waste Heat Integration into Existing District Heating Systems," Energies, MDPI, vol. 15(5), pages 1-29, February.
    14. Yin Bi & Yugang Wang & Xiaoli Ma & Xudong Zhao, 2017. "Investigation on the Energy Saving Potential of Using a Novel Dew Point Cooling System in Data Centres," Energies, MDPI, vol. 10(11), pages 1-21, October.
    15. Borkowski, Mateusz & Piłat, Adam Krzysztof, 2022. "Customized data center cooling system operating at significant outdoor temperature fluctuations," Applied Energy, Elsevier, vol. 306(PB).
    16. Wang, Dabiao & Ma, Yuezheng & Tian, Ran & Duan, Jie & Hu, Busong & Shi, Lin, 2018. "Thermodynamic evaluation of an ORC system with a Low Pressure Saturated Steam heat source," Energy, Elsevier, vol. 149(C), pages 375-385.
    17. Ding, Zhixiong & Wu, Wei, 2022. "Type II absorption thermal battery for temperature upgrading: Energy storage heat transformer," Applied Energy, Elsevier, vol. 324(C).
    18. Du, Han & Zhou, Xinlei & Nord, Natasa & Carden, Yale & Ma, Zhenjun, 2023. "A new data mining strategy for performance evaluation of a shared energy recovery system integrated with data centres and district heating networks," Energy, Elsevier, vol. 285(C).
    19. Cristina Ramos Cáceres & Suzanna Törnroth & Mattias Vesterlund & Andreas Johansson & Marcus Sandberg, 2022. "Data-Center Farming: Exploring the Potential of Industrial Symbiosis in a Subarctic Region," Sustainability, MDPI, vol. 14(5), pages 1-23, February.
    20. Deymi-Dashtebayaz, Mahdi & Norani, Marziye, 2021. "Sustainability assessment and emergy analysis of employing the CCHP system under two different scenarios in a data center," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:11:y:2018:i:3:p:644-:d:136181. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.