Effect of data center servers' power density on the decision of using in-row cooling or perimeter cooling

Heat propagation and servers? temperature increase inside data centers racks is a vital issue. So, selecting the proper cooling architecture is an important step during the design of data centers. Traditional cooling systems, called perimeter cooling, consume huge amounts of electricity. A more recent effective cooling architecture of data centers, called in-row cooling where the cooling units are inserted between racks, is commercially suggested to reduce cooling power consumption. The current study numerically investigates the performance of in-row cooling architecture compared with the traditional cooling architecture of data centers of different power densities. Temperature distribution and performance parameters indices such as Supply/Return Heat Indices (SHI/ RHI), Return Temperature Index (RTI), Index of Mixing (IOM), Energy Utilization Coefficient (gr), and Beta Index (0) are used to conduct this comparative study. The study was performed at different rack?s power densities to determine the overall better cooling architecture for the different power densities. The results show that (i) in-row cooling architecture has better thermal performance as observed in temperature contours (ii) SHI, RHI, RTI, gr, 0 and IOM have better values in case of in-row cooling, especially at high power densities, which indicates less hot air recirculation and cold air bypass and completely benefit from cooling capacity of CRACs, (iii) perimeter cooling is suitable for low power densities while in-row cooling can be used for high power densities, and (iv) maximum velocity values are obtained for 10 kW rack's power which dramatically affects the thermal performance of perimeter cooling architecture as indicated by the dramatic decrease of the energy utilization coefficient to 1.4 while it increased for in-row cooling to 1.9. (C) 2021 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/ 4.0/).