Numerical Evaluation of Hot Air Recirculation in Server Rack
Source abstract
Abstract
In air-cooled data centers, hot aisle containment is used to separate hot and cold air from mixing to improve cooling effectiveness. However, this creates a significant pressure imbalance between the cold and hot aisles, with the latter being high. The hot aisle high pressure creates bac pressure that pushes against the server-unit fan system, which subsequently results in hot recirculation and insufficient server-unit cooling. This study examines the application of series-configured server fans with the intention of increasing the system pressure head to overcome the hot aisle containment back pressure and eliminate server hot air recirculation. A detailed computational fluid dynamics model for the Dell 2950 2U server is calibrated and validated using existing experimental test results. Furthermore, the impact of changing the server fan system to a series configuration by adding four or more server fans is investigated under different hot-aisle pressure conditions. It was found that changing the server fan system configuration from parallel to series arrangement positively improved the available system static pressure, but it did not result in the elimination of hot air recirculation. The server with the series-configured fan system experienced an average inlet air temperature increase of 9% when compared to the original server under similar conditions. This study serves as a base for integrating liquid and air-cooling systems to form hybrid cooling systems for high-density racks in legacy data centers.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Cyclone Separators and Fluid Dynamics · Rocket and propulsion systems research · Aerosol Filtration and Electrostatic Precipitation
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Mechanical and Industrial Engineering Technology, University of Johannesburg, Doornfontein Campus, Corner of Siemert and Beit Streets, Johannesburg 2028, South Africa
References (34)
Show source-provided references
1. Azari, R., and Rashed-Ali, H. (2021). Research Methods in Building Science and Technology, Springer Nature.10.1007/978-3-030-73692-7 ↗
2. Wu, C., and Buyya, R. (2015). Cloud Data Centers and Cost Modeling: A Complete Guide to Planning, Designing and Building a Cloud Data Center, Morgan Kaufmann Publishers Inc.. [1st ed.].10.1016/B978-0-12-801413-4.00005-2 ↗
3. Experimentally Validated Computational Fluid Dynamics Model for a Data Center With Cold Aisle Containment10.1115/1.4029344 ↗
4. Implications of Historical Trends in the Electrical Efficiency of Computing10.1109/MAHC.2010.28 ↗
5. Zhou, R., Wang, Z., Bash, C.E., and McReynolds, A. (2011, January 11–17). Modeling and Control for Cooling Management of Data Centers with Hot Aisle Containment. Proceedings of the ASME 2011 International Mechanical Engineering Congress and Exposition, Denver, CO, USA.10.1115/IMECE2011-62506 ↗
6. Thermal aware workload placement with task-temperature profiles in a data center10.1007/s11227-011-0635-z ↗
7. Cooling systems in data centers: State of art and emerging technologies10.1016/j.egypro.2015.12.168 ↗
8. Impact of server thermal design on the cooling efficiency: Chassis design10.1115/1.4042983 ↗
9. Exergy Analysis of Data Center Thermal Management Systems10.1115/1.2787024 ↗
10. Khalili, S., Alissa, H., Nemati, K., Seymour, M., Curtis, R., Moss, D., and Sammakia, B. (2018, January 27–30). Impact of Internal Design on the Efficiency of IT Equipment in a Hot Aisle Containment System: An Experimental Study. Proceedings of the ASME 2018 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems, San Francisco, CA, USA.10.1115/IPACK2018-8422 ↗
11. A critical review on the thermal management of data center for local hotspot elimination
12. Imbalance of CPU temperatures in a blade system and its impact for power consumption of fans10.1007/s10586-011-0174-7 ↗
13. Khalili, S., Tradat, M., Sammakia, B., Alissa, H., and Chen, C. (2019, January 28–31). Impact of Fans Location on the Cooling Efficiency of IT Servers. Proceedings of the 2019 18th IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (ITherm), Las Vegas, NV, USA.10.1109/ITHERM.2019.8756504 ↗
14. Experimental evaluation of direct-to-chip cold plate liquid cooling for high-heat-density data centers10.1016/j.applthermaleng.2023.122122 ↗
15. Wilkinson, M.B., Louw, F.G., van der Spuy, S.J., and von Backström, T.W. (2016, January 13–17). A Comparison of Actuator Disc Models for Axial Flow Fans in Large Air-Cooled Heat Exchangers. Proceedings of the ASME Turbo Expo 2016: Turbomachinery Technical Conference and Exposition, Seoul, Republic of Korea.10.1115/GT2016-56491 ↗
16. Main rotor-body action for virtual blades model10.1051/epjconf/201818002050 ↗
17. CFD simulation of helicopter rotor flow based on unsteady actuator disk model10.1016/j.cja.2020.03.021 ↗
18. A review on airflow management in data centers10.1016/j.apenergy.2019.02.041 ↗
19. Proposal for standard compact server model for transient data center simulations
20. Vangilder, J., Vaishnani, Y., Tian, W., and Condor, M. (2020, January 21–23). A Compact Rack Model for Data Center CFD Modeling. Proceedings of the 2020 19th IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (ITherm), Orlando, FL, USA.10.1109/ITherm45881.2020.9190187 ↗
21. A compact server model for transient data center simulations
22. Noise source analysis for two identical small axial-flow fans in series under operating condition10.1016/j.apacoust.2017.07.010 ↗
23. An adaptive mesh refinement approach for solving non-Hertzian elastic contact problems10.1007/s11012-017-0806-y ↗
24. Korpela, S.A. (2019). Principles of Turbomachinery, John Wiley & Sons.
25. Large-eddy simulation: Past, present and the future10.1016/j.cja.2014.12.007 ↗
26. LES of wall-bounded flows using a new subgrid scale model based on energy spectrum dissipation10.1115/1.2775499 ↗
27. Leishman, J.G. (2011). Aerodynamics of horizontal axis wind turbines. Advances in Wind Energy Conversion Technology, Springer.10.1007/978-3-540-88258-9_1 ↗
28. Helma, S. (2020). Surprising Behaviour of the Wageningen B-Screw Series Polynomials. J. Mar. Sci. Eng., 8.10.20944/preprints201912.0140.v2 ↗
29. Grid convergence study on flow past a circular cylinder for beginners10.1063/5.0036230 ↗
30. Teschner, T.-R. (2024, September 01). Grid Convergence Study {pyGCS}. 2021, PyPI: pyGCS 0.2.0. Mar. 10, 2021, PyPI: pyGCS 0.2.0. Available online: https://pypi.org/project/pyGCS/0.2.0/.
31. Procedure for estimation and reporting of uncertainty due to discretization in CFD applications
32. Persperctive: A method for uniform reporting of grid refinement studies10.1115/1.2910291 ↗
33. Ahmadi, M., Ghaderi, A., Nezhad, H.M., Kuriqi, A., and Di Francesco, S. (2021). Numerical investigation of hydraulics in a vertical slot fishway with upgraded configurations. Water, 13.10.3390/w13192711 ↗
34. Kinetic consistent MHD algorithm for incompressible conductive fluids10.1016/j.compfluid.2022.105724 ↗