Airflow and Cooling Performance of Data Centers: Two Performance Metrics

被引:0
|
作者
Herrlin, Magnus K. [1 ]
机构
[1] ANCIS Inc, San Francisco, CA USA
来源
关键词
D O I
暂无
中图分类号
O414.1 [热力学];
学科分类号
摘要
This paper focuses on the use of performance metrics for analyzing air-management systems in data centers. Such systems are important for adequately cooling the electronic equipment and controlling the associated energy costs. Computational Fluid Dynamics (CFD) modeling has the capacity to help understand how a cooling solution will perform prior to being built. However modeling also has the capacity to generate an unwieldy amount of data. The crux of the matter is to know what to look for and then objectively characterize and report the performance. Performance metrics provide a great opportunity for the data center industry at large. They could form the foundation for a standardized way of specifying and reporting various cooling solutions. This paper specifically demonstrates the use of two metrics: The Rack Cooling Index (RCI) is a measure of how well the system cools the electronics within the manufacturers' specifications, and the Return Temperature Index (RTI) is a measure of the energy performance of the air-management system. Combined, they provide an opportunity to judge the performance of the air-management system in an objective way subsequent to comprehensive CFD modeling. A real-world example is given for demonstrating the use of these metrics to design a high-density data center The analysis was designed to answer whether a fairly conventional raised-floor system could support significantly higher heat densities than was previously thought. By enclosing the cold equipment aisles, it is demonstrated that the cooling capacity can indeed be greatly increased. This should provide a welcome relief for many data centers that are currently running out of capacity due to a low raised floor.
引用
收藏
页码:182 / 187
页数:6
相关论文
共 50 条
  • [1] Servers and data centers energy performance metrics
    Beitelmal, A. H.
    Fabris, D.
    [J]. ENERGY AND BUILDINGS, 2014, 80 : 562 - 569
  • [2] Servers and data centers energy performance metrics
    [J]. Beitelmal, A.H., 1600, Elsevier Ltd (80):
  • [3] Servers and data centers energy performance metrics
    [J]. Beitelmal, A.H. (abeitelmal@scu.edu), 1600, Elsevier Ltd (80):
  • [4] Cooling performance of a pump-driven two phase cooling system for free cooling in data centers
    Ma, Yuezheng
    Ma, Guoyuan
    Zhang, Shuang
    Zhou, Feng
    [J]. APPLIED THERMAL ENGINEERING, 2016, 95 : 143 - 149
  • [5] Optimization of cluster cooling performance for data centers
    Shrivastava, Saurabh K.
    VanGilder, James W.
    Sammakia, Bahgat G.
    [J]. 2008 11TH IEEE INTERSOCIETY CONFERENCE ON THERMAL AND THERMOMECHANICAL PHENOMENA IN ELECTRONIC SYSTEMS, VOLS 1-3, 2008, : 1161 - +
  • [6] A review on evaluation metrics of thermal performance in data centers
    Gong, Xiaoming
    Zhang, Zhongbin
    Gan, Sixuan
    Niu, Baolian
    Yang, Liu
    Xu, Haijin
    Gao, Manfang
    [J]. BUILDING AND ENVIRONMENT, 2020, 177
  • [7] Optical Switching Performance Metrics for Scalable Data Centers
    Bergman, Keren
    Rumley, Sibastien
    [J]. 2016 21ST OPTOELECTRONICS AND COMMUNICATIONS CONFERENCE (OECC) HELD JOINTLY WITH 2016 INTERNATIONAL CONFERENCE ON PHOTONICS IN SWITCHING (PS), 2016,
  • [8] Performance Comparison between Data Centers with Different Airflow Management Technologies
    Li, Xueqiang
    Zhang, Zhongyao
    Wang, Qihui
    Yang, Xiaohu
    Hooman, Kamel
    Liu, Shengchun
    [J]. HEAT TRANSFER ENGINEERING, 2024, 45 (11) : 1011 - 1027
  • [9] Review of performance metrics for green data centers: a taxonomy study
    Lizhe Wang
    Samee U. Khan
    [J]. The Journal of Supercomputing, 2013, 63 : 639 - 656
  • [10] Review of performance metrics for green data centers: a taxonomy study
    Wang, Lizhe
    Khan, Samee U.
    [J]. JOURNAL OF SUPERCOMPUTING, 2013, 63 (03): : 639 - 656