Volume 11, Issue 1
Numerical Investigation into the Air Flow Distributions of the Air Conditioning System in the Modular Data Center

Adv. Appl. Math. Mech., 11 (2019), pp. 91-107.

Published online: 2019-01

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• Abstract

Data center plays an increasingly important role in everyday life. As data center is becoming more and more powerful, energy consumption is also increasing dramatically. The air conditioning system occupies at least 50 percent of the total energy consumption. Therefore, delicate analysis on the air conditioning system could help to reduce energy consumption in data center. An advanced Finite Volume Method with RNG $k-\varepsilon$ model and convective heat exchange model is used in this paper to study the airflow and the temperature distribution of modular data center under different arrangements. Specifically, the calculation formula of convective heat transfer coefficient for plate flow is adopted to simplify analysis; and fans on the back of racks are simplified to be walls with a certain pressure jump. Simulations reveal that, in the case where air conditioners are arranged face-to-face, the temperature distribution on the back of racks is not uniform, and local high temperature points emerge near the side wall of air conditioners. By analyzing the distribution of air flow and temperature, geometric model is optimized by using a diagonal rack arrangement and drilling holes on the side wall. In the same energy consumption situation, the overall maximum temperature of the optimized model is reduced by 2.3$^\circ$C compared with that of the original one, and the maximum temperature on the server surface is reduced by 1$^\circ$C. Based on the optimized model, the effect of the hot aisle distance on the temperature distribution is studied. By simulating four different cases with various distances of hot aisle of 100cm, 120cm, 130cm and 150cm, it is found that the temperature is generally lower and distributed more evenly in the case with 120cm hot aisle distance. This demonstrates that the distance of hot aisle has an effect on temperature.

58D30, 76N15, 76N25, 76B47

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@Article{AAMM-11-91, author = {Dong , HaoQin , ZiqiangLiu , ShichengLi , YaoShen , YingyingWang , HaiboZong , YitongWu , Xiaojun and Si , Haiqing}, title = {Numerical Investigation into the Air Flow Distributions of the Air Conditioning System in the Modular Data Center}, journal = {Advances in Applied Mathematics and Mechanics}, year = {2019}, volume = {11}, number = {1}, pages = {91--107}, abstract = {

Data center plays an increasingly important role in everyday life. As data center is becoming more and more powerful, energy consumption is also increasing dramatically. The air conditioning system occupies at least 50 percent of the total energy consumption. Therefore, delicate analysis on the air conditioning system could help to reduce energy consumption in data center. An advanced Finite Volume Method with RNG $k-\varepsilon$ model and convective heat exchange model is used in this paper to study the airflow and the temperature distribution of modular data center under different arrangements. Specifically, the calculation formula of convective heat transfer coefficient for plate flow is adopted to simplify analysis; and fans on the back of racks are simplified to be walls with a certain pressure jump. Simulations reveal that, in the case where air conditioners are arranged face-to-face, the temperature distribution on the back of racks is not uniform, and local high temperature points emerge near the side wall of air conditioners. By analyzing the distribution of air flow and temperature, geometric model is optimized by using a diagonal rack arrangement and drilling holes on the side wall. In the same energy consumption situation, the overall maximum temperature of the optimized model is reduced by 2.3$^\circ$C compared with that of the original one, and the maximum temperature on the server surface is reduced by 1$^\circ$C. Based on the optimized model, the effect of the hot aisle distance on the temperature distribution is studied. By simulating four different cases with various distances of hot aisle of 100cm, 120cm, 130cm and 150cm, it is found that the temperature is generally lower and distributed more evenly in the case with 120cm hot aisle distance. This demonstrates that the distance of hot aisle has an effect on temperature.

}, issn = {2075-1354}, doi = {https://doi.org/10.4208/aamm.OA-2018-0139}, url = {http://global-sci.org/intro/article_detail/aamm/12923.html} }
TY - JOUR T1 - Numerical Investigation into the Air Flow Distributions of the Air Conditioning System in the Modular Data Center AU - Dong , Hao AU - Qin , Ziqiang AU - Liu , Shicheng AU - Li , Yao AU - Shen , Yingying AU - Wang , Haibo AU - Zong , Yitong AU - Wu , Xiaojun AU - Si , Haiqing JO - Advances in Applied Mathematics and Mechanics VL - 1 SP - 91 EP - 107 PY - 2019 DA - 2019/01 SN - 11 DO - http://doi.org/10.4208/aamm.OA-2018-0139 UR - https://global-sci.org/intro/article_detail/aamm/12923.html KW - Modular data center, air conditioning, temperature distribution, hot/cold aisle, CFD. AB -

Data center plays an increasingly important role in everyday life. As data center is becoming more and more powerful, energy consumption is also increasing dramatically. The air conditioning system occupies at least 50 percent of the total energy consumption. Therefore, delicate analysis on the air conditioning system could help to reduce energy consumption in data center. An advanced Finite Volume Method with RNG $k-\varepsilon$ model and convective heat exchange model is used in this paper to study the airflow and the temperature distribution of modular data center under different arrangements. Specifically, the calculation formula of convective heat transfer coefficient for plate flow is adopted to simplify analysis; and fans on the back of racks are simplified to be walls with a certain pressure jump. Simulations reveal that, in the case where air conditioners are arranged face-to-face, the temperature distribution on the back of racks is not uniform, and local high temperature points emerge near the side wall of air conditioners. By analyzing the distribution of air flow and temperature, geometric model is optimized by using a diagonal rack arrangement and drilling holes on the side wall. In the same energy consumption situation, the overall maximum temperature of the optimized model is reduced by 2.3$^\circ$C compared with that of the original one, and the maximum temperature on the server surface is reduced by 1$^\circ$C. Based on the optimized model, the effect of the hot aisle distance on the temperature distribution is studied. By simulating four different cases with various distances of hot aisle of 100cm, 120cm, 130cm and 150cm, it is found that the temperature is generally lower and distributed more evenly in the case with 120cm hot aisle distance. This demonstrates that the distance of hot aisle has an effect on temperature.

Hao Dong, Ziqiang Qin, Shicheng Liu, Yao Li, Yingying Shen, Haibo Wang, Yitong Zong, Xiaojun Wu & Haiqing Si. (2020). Numerical Investigation into the Air Flow Distributions of the Air Conditioning System in the Modular Data Center. Advances in Applied Mathematics and Mechanics. 11 (1). 91-107. doi:10.4208/aamm.OA-2018-0139
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