Please use this identifier to cite or link to this item:
|Title:||Investigation of diverse cold air inlet configurations for Sun HPC data center||Authors:||Liu, Zhao||Keywords:||Engineering::Mechanical engineering||Issue Date:||2020||Publisher:||Nanyang Technological University||Project:||P-B023||Abstract:||The data center acts a significant part in recent years due to the rapid growth of cloud computing. Many organizations are running these data centers for their routine operations all year round and the excessive heat generated by the servers will have an adverse effect on the electronic components of the computing devices. Further more, the energy consumption and cooling demand in the data center have remarkably increased. The mainstream method of traditional air cooling is not efficient enough to remove the extra heat promptly and consumes a large amount of power as well. Therefore, with energy costs increasing, there is now a need to design the data center adequately to maintain the proper temperature with higher cooling efficiency. This project is undertaken with the purpose to investigate and study the efficiency of passive cooling cabinets in data center by comparing diverse cold air inlet configurations. The results are accomplished by using the commercial CFD software, ANSYS FLUENT, to simulate the thermal distribution and airflow around the server cabinets in the data center. The crucial problems are identified, such as over cooling ares at some parts of the data center and re-circulation of the hot air, and so on. The parameters used in the simulation are achieved from previous research of Sun HPC data center. This project indicates that it is possible to improve the cooling efficiency and achieve faster heat dissipation via investigating the best combination of different sizes, locations and orientations of cold air inlet. It is suggested that further studies should include different server layouts as well as the diverse conditions of the air outlets into the research to improve the reliability of the findings.||URI:||https://hdl.handle.net/10356/141218||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||MAE Student Reports (FYP/IA/PA/PI)|
Updated on Jun 26, 2022
Updated on Jun 26, 2022
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.