Performance evaluation and artificial neural network based thermal modelling of multi tilted active tiles in data centres

The Journal of Engineering

Gaoxiang Cong¹  Leixiao Li¹  Jianxiong Wan¹  Zhiqiang Ma¹  Zhiyan Zhao¹  Zeeshan Rasheed¹ 

[1] School of Data Science and Application Inner Mongolia University of Technology and Inner Mongolia Autonomous Region Engineering & Technology Research Center of Big Data Based Software Service Huhhot China;

关键词: Air conditioning;    Computer facilities;    Neural nets;   

DOI  :  10.1049/tje2.12052

来源: DOAJ

【 摘 要 】

Abstract The main purpose of this paper is to improve the resilience of data center cooling system and reduce the energy consumption in data center by using the Tilted Active Tile (TATs). We deploy multiple TATs in cold aisle environment then analyze the thermal performance of racks. TATs also help to improve the reliability in case of cooling failure by increased ride through time. We observed an extended ride‐through time for data centers deployed with Tilted Active Tiles (TATs) when the CRAC blower failed. Proposed approach can maintain cooling system temperature for up to 10 minutes. We also introduced ANN based thermal models to predict the thermal performance of TATs, To train the ANN models, we collect the rack inlet and CRAC outlet temperature from Data Center. We also fixed blank panel in empty U part of racks and then analyzed that the thermal performance of racks are better and temperature distribution at bottom, middle and top of the rack were same under 30°angle. The airflow of TATs and passive tile influence on surrounding racks. That’s why we analyzed the disturbance of TATs on surrounding rack and observed that the TATs at 30°angle has positiveimpact on the surrounding racks.

【 授权许可】

Unknown