CFD Analysis of Data Center Hall Cooling Performance under Normal and Failure Modes with Control Strategies and Airflow Leakages
Journal of Engineering Research and Sciences, Volume 5, Issue 1, Page # 9-28, 2026; DOI: 10.55708/js0501002
Keywords: CFD, Control strategy, Data center, Leakage
(This article belongs to the Special Issue on SP7 (Special Issue on Multidisciplinary Sciences and Advanced Technology (SI-MSAT 2025)) and the Section Mechanical Engineering (MEE))
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Surwase, S. A. , Badde, S. and Balakrishnan, R. (2026). CFD Analysis of Data Center Hall Cooling Performance under Normal and Failure Modes with Control Strategies and Airflow Leakages. Journal of Engineering Research and Sciences, 5(1), 9–28. https://doi.org/10.55708/js0501002
Sushil Ashok Surwase, Suribabu Badde and R. Balakrishnan. "CFD Analysis of Data Center Hall Cooling Performance under Normal and Failure Modes with Control Strategies and Airflow Leakages." Journal of Engineering Research and Sciences 5, no. 1 (January 2026): 9–28. https://doi.org/10.55708/js0501002
S.A. Surwase, S. Badde and R. Balakrishnan, "CFD Analysis of Data Center Hall Cooling Performance under Normal and Failure Modes with Control Strategies and Airflow Leakages," Journal of Engineering Research and Sciences, vol. 5, no. 1, pp. 9–28, Jan. 2026, doi: 10.55708/js0501002.
Data centers have become the backbone of an increasingly digitized world, supporting the rapid growth of cloud computing, big data, IoT, 5G, and other emerging IT technologies, with rising demand and innovations in AI and ML reinforcing their significance. Data centers are energy intensive, with data processing and storage accounting for 3 to 4% of global energy consumption, which continues to grow annually. Improving their efficiency is therefore a major industrial challenge, offering substantial cost savings. The modern data center involves an intricate interaction between various mechanical, electrical and control systems. The many possible operating configurations and non-linear interdependencies make it challenging to understand and optimize energy efficiency. In the present study, computational fluid dynamics (CFD) analysis is used to assess the cooling performance of a dynamically controlled data center hall with non-raised floor configuration and hot aisle containment (HAC) strategy. The operation of air-cooling units (ACUs) is dynamically regulated in response to the data hall IT load through an integrated network of sensors and controllers. These controllers modulate ACU fan speed and chilled water flow rates to maintain the IT cabinet inlet air temperature within each ACU’s zone of influence and below the specified threshold. This control strategy, informed by real-time temperature and pressure sensor data, ensures desired thermal conditions within the data hall while optimizing overall cooling power consumption. This study focuses on two modes of operation for the purpose of design analysis, i.e., normal mode (NM) and failure mode (FM). Based on CFD simulation results, the present paper highlights the effects of control strategy used for ACUs, cooling airflow leakage, recirculation of hot air on the performance of the data hall cooling design. Different simulation scenarios, which accommodate all possible combinations during NM and FM of operation i.e., with & without control and with & without leakages are evaluated to understand the significance of various design parameters, leading towards the right design. Results show that the control strategy delivers approximately 9.89% energy savings in normal mode, while leakages significantly degrade performance during failure mode.
- Y. Zhang, J. Liu, “Prediction of Overall Energy Consumption of Data Centers in Different Locations,” Sensors, vol. 22, no. 10, pp. 3704, 2022, doi:10.3390/s22103704.
- E. Masanet, A. Shehabi, N. Lei, S. Smith, J. Koomey, “Recalibrating global data center energy-use estimates,” Science, vol. 367, no. 6481, pp. 984–986, 2020, doi:10.1126/science.aba3758.
- CISCO, Cisco Global Cloud Index: Forecast and Methodology, 2016–2021, 2018.
- International Energy Agency, Digitalization & Energy, 2017.
- A. Shehabi, S.J. Smith, E. Masanet, J. Koomey, “Data center growth in the United States: Decoupling the demand for services from electricity use,” Environmental Research Letters, vol. 13, no. 12, 2018, doi:10.1088/1748-9326/aaec9c.
- ABB, Data centers energy efficiency and management, 2023.
- M. Law, “Energy efficiency predictions for data centres in 2023,” 2022.
- Y. Liu, X. Wei, J. Xiao, Z. Liu, Y. Xu, Y. Tian, “Energy consumption and emission mitigation prediction based on data center traffic and PUE for global data centers,” Global Energy Interconnection, vol. 3, no. 3, pp. 272–282, 2020, doi:10.1016/j.gloei.2020.07.008.
- P. Sharma, P. Pegus II, D. Irwin, P. Shenoy, J. Goodhue, J. Culbert, “Design and Operational Analysis of a Green Data Center,” IEEE Internet Computing, vol. 21, no. 4, pp. 16–24, 2017, doi:10.1109/MIC.2017.2911421.
- J. Gao, “Machine Learning Applications for Data Center Optimization,” 2014.
- Sullivan R, Alternating Cold and Hot Aisles Provides More Reliable Cooling for Server Farms, 2000.
- C.D. Patel, C.E. Bash, L. Stahl, D. Sullivan, “Computational Fluid Dynamics Modeling of High Compute Density Data Centers to Assure System Inlet Air Specifications,” in IPACK, ASME, 2001.
- S. Patankar, “Airflow and Cooling in a Data Center,” ASME Journal of Heat Transfer, vol. 132, no. 7, 2010, doi:10.1115/1.4000703.
- S. Pogorelskiy, I. Kocsis, “BIM and Computational Fluid Dynamics Analysis for Thermal Management Improvement in Data Centres,” Buildings, vol. 13, no. 10, 2023, doi:10.3390/buildings13102636.
- D. Jiang, “Effects and optimization of airflow on the thermal environment in a data center,” Frontiers in Built Environment, vol. 10, , 2024, doi:10.3389/fbuil.2024.1362861.
- J. Cho, C. Park, W. Choi, “Numerical and experimental study of air containment systems in legacy data centers focusing on thermal performance and air leakage,” Case Studies in Thermal Engineering, vol. 26, , 2021, doi:10.1016/j.csite.2021.101084.
- J. Cho, J. Woo, B. Park, T. Lim, “A comparative CFD study of two air distribution systems with hot aisle containment in high-density data centers,” Energies, vol. 13, no. 22, 2020, doi:10.3390/en13226147.
- C. Zhou, Y. Hu, R. Liu, Y. Liu, M. Wang, H. Luo, Z. Tian, “Energy Performance Study of a Data Center Combined Cooling System Integrated with Heat Storage and Waste Heat Recovery System,” Buildings, vol. 15, no. 3, 2025, doi:10.3390/buildings15030326.
- Y. Guo, C. Zhao, H. Gao, C. Shen, X. Fu, “Improving Thermal Performance in Data Centers Based on Numerical Simulations,” Buildings, vol. 14, no. 5, 2024, doi:10.3390/buildings14051416.
- Kao Data, Using Simulation to Validate Cooling Design, 2021.
- AKCP, Computational Fluid Dynamics to Improve the Performance of Data Centers, 2021.
- B. Zhan, S. Shao, M. Lin, H. Zhang, C. Tian, Y. Zhou, “Experimental investigation on ducted hot aisle containment system for racks cooling of data center,” International Journal of Refrigeration, vol. 127, pp. 137–147, 2021, doi:10.1016/j.ijrefrig.2021.02.006.
- M. Tatchell-Evans, N. Kapur, J. Summers, H. Thompson, D. Oldham, “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, vol. 186, pp. 457–469, 2017, doi:10.1016/j.apenergy.2016.03.076.
- S.A. Alkharabsheh, B.G. Sammakia, S.K. Shrivastava, “Experimentally Validated Computational Fluid Dynamics Model for a Data Center with Cold Aisle Containment,” Journal of Electronic Packaging, vol. 137, no. 2, pp. 21010, 2015, doi:10.1115/1.4029344.
- C. Gao, Z. Yu, J. Wu, “Investigation of Airflow Pattern of a Typical Data Center by CFD Simulation,” Energy Procedia, vol. 78, pp. 2687–2693, 2015, doi:10.1016/j.egypro.2015.11.350.
- S.A. Nada, M.A. Said, “Effect of CRAC units layout on thermal management of data center,” Applied Thermal Engineering, vol. 118, pp. 339–344, 2017, doi:10.1016/j.applthermaleng.2017.03.003.
- R. Zhou, Z. Wang, “Modeling and Control for Cooling Management of Data Centers with Hot Aisle Containment,” in IMECE, ASME: 739–746, 2011, doi:10.1115/IMECE2011-62506.
- C.D. Patel, C.E. Bash, R. Sharma, M. Beitelmal, R. Friedrich, “Smart cooling of data centers,” in Advances in Electronic Packaging, American Society of Mechanical Engineers: 129–137, 2003, doi:10.1115/ipack2003-35059.
- C.B. Bash, C.D. Patel, R.K. Sharma, “Dynamic thermal management of air cooled data centers,” in Thermal and Thermomechanical Proceedings 10th Intersociety Conference on Phenomena in Electronics Systems, 2006 (ITHERM 2006), pp. 8– 452, 2006, doi:10.1109/ITHERM.2006.1645377.
- S. Nagarathinam, B. Fakhim, M. Behnia, S. Armfield, “Thermal Performance of an Air-Cooled Data Center With Raised-Floor and Non-Raised-Floor Configurations,” Heat Transfer Engineering, vol. 35, pp. 384–397, 2014, doi:10.1080/01457632.2013.828559.
- K. Khankari, “Analysis of Air Leakage from Hot Aisle Containment Systems and Cooling Efficiency of Data Centers,” in ASHRAE Winter Conference, 2014.
- H. Alissa, K. Nemati, B. Sammakia, K. Ghose, M. Seymour, D. King, R. Tipton, “Ranking and Optimization of CAC and HAC Leakage Using Pressure Controlled Models,” in Proceedings of the ASME IMECE, 2015, doi:10.1115/IMECE2015-50782.
- Z. Song, B.T. Murray, B. Sammakia, “Parametric analysis for thermal characterization of leakage flow in data centers,” in Fourteenth Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (ITherm), IEEE: 778–785, 2014, doi:10.1109/ITHERM.2014.6892360.
- Y.U. Makwana, A.R. Calder, S.K. Shrivastava, “Benefits of properly sealing a cold aisle containment system,” in Fourteenth Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (ITherm), IEEE: 793–797, 2014, doi:10.1109/ITHERM.2014.6892362.
- E. Wibron, A.L. Ljung, T. Staffan Lundström, “Comparing performance metrics of partial aisle containments in hard floor and raised floor data centers using CFD,” Energies, vol. 12, no. 8, 2019, doi:10.3390/en12081473.
- Y.-T. Lee, C.-Y. Wen, Y.-C. Shih, Z. Li, A.-S. Yang, “Numerical and experimental investigations on thermal management for data center with cold aisle containment configuration,” Applied Energy, vol. 307, , pp. 118213, 2022, doi:10.1016/j.apenergy.2021.118213.
- D. Macedo, R. Godina, P.D. Gaspar, P.D. da Silva, M.T. Covas, “A parametric numerical study of the airflow and thermal performance in a real data center for improving sustainability,” Applied Sciences, vol. 9, no. 18, 2019, doi:10.3390/app9183850.
- J. Cho, T. Lim, B.S. Kim, “Measurements and predictions of the air distribution systems in high compute density (Internet) data centers,” Energy and Buildings, vol. 41, no. 10, pp. 1107–1115, 2009, doi:10.1016/j.enbuild.2009.05.017.
- S. Alkharabsheh, J. Fernandes, B. Gebrehiwot, D. Agonafer, K. Ghose, A. Ortega, Y. Joshi, B. Sammakia, “A Brief Overview of Recent Developments in Thermal Management in Data Centers,” Journal of Electronic Packaging, Transactions of the ASME, vol. 137, no. 4, pp. 40801, 2015, doi:10.1115/1.4031326.
- E. Wibron, A.L. Ljung, T.S. Lundström, “Computational fluid dynamics modeling and validating experiments of airflow in a data center,” Energies, vol. 11, no. 3, 2018, doi:10.3390/en11030644.
- R. Sethuramalingam, A. Asthana, Design Improvement of Water-Cooled Data Centres Using Computational Fluid Dynamics, Springer: 105–113, 2021, doi:10.1007/978-3-030-63916-7_14.
- A. Almoli, A. Thompson, N. Kapur, J. Summers, H. Thompson, G. Hannah, “Computational fluid dynamic investigation of liquid rack cooling in data centres,” Applied Energy, vol. 89, no. 1, pp. 150–155, 2012, doi:10.1016/j.apenergy.2011.02.003.
- R. Balakrishnan, M. Munirajulu, “CFD Simulation of Tier 4 Data Center for Cooling and Backup Power,” in 2023 2nd International Conference for Innovation in Technology (INOCON), 1–7, 2023, doi:10.1109/INOCON57975.2023.10101234.
- D. Pickut, Data Center Design: Raised Floor Versus Slab Floor?, 2011.
- H.K. Versteeg, W. Malalasekera, An Introduction to Computational Fluid Dynamics, Second Edition, Pearson, 2007.
- S.V. Patankar, Numerical Heat Transfer and Fluid Flow, First Edition, Hemisphere Publishing Corporation, 1980.
- J.D., Jr. Anderson, Computational Fluid Dynamics: The basics with applications, McGraw-Hill Education, 1995.
- J.H. Ferziger, M. Perić, Computational Methods for Fluid Dynamics, Third Edition, Springer, 2002.
- J. ’Tannehill, A. ’Dale, R. Pletcher, Computational Fluid Mechanics and Heat Transfer, Second Edition, Taylor&Francis, 1997.
- B.E. Launder, D.B. Spalding, “The numerical computation of turbulent flows,” Computer Methods in Applied Mechanics and Engineering, vol. 3, no. 2, pp. 269–289, 1974, doi:10.1016/0045-7825(74)90029-2.
- Ansys, Ansys CFX-Solver Modeling Guide, 2025.
- S.A. Nada, M.A. Said, M.A. Rady, “CFD investigations of data centers’ thermal performance for different configurations of CRACs units and aisles separation,” Alexandria Engineering Journal, vol. 55, no. 2, pp. 959–971, 2016, doi:10.1016/j.aej.2016.02.025.
- D.D. Gray, A. Giorgini, “The validity of the boussinesq approximation for liquids and gases,” International Journal of Heat and Mass Transfer, vol. 19, no. 5, pp. 545–551, 1976, doi:10.1016/0017-9310(76)90168-X.
- Cadence Reality DC Design, https://www.cadence.com/en_US/home/resources/product-briefs/cadence-reality-dc-design-pb.html, 2025.
- E. Frachtenberg, D. Lee, M. Magarelli, V. Mulay, J. Park, “Thermal design in the open compute datacenter,” in ITherm, IEEE: 530–538, 2012, doi:10.1109/ITHERM.2012.6231476.
- H. Alissa, K. Nemati, B. Sammakia, K. Ghose, M. Seymour, R. Schmidt, “Innovative Approaches of Experimentally Guided CFD Modeling for Data Center,” in SEMI-THERM, IEEE: 176–184, 2015, doi:10.1109/SEMI-THERM.2015.7100157.
- M.I. Tradat, Y. Manaserh, B.G. Sammakia, C.H. Hoang, H.A. Alissa, “An experimental and numerical investigation of novel solution for energy management enhancement in data centers using underfloor plenum porous obstructions,” Applied Energy, vol. 289, , 2021, doi:10.1016/j.apenergy.2021.116663.
- ASHRAE TC 9.9, 2021 Equipment Thermal Guidelines for Data Processing Environments.
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