Optimization and comprehensive evaluation of liquid cooling tank for single-phase immersion cooling data center

材料科学 冷却液 迷惑 多孔性 体积流量 核工程 数据中心 机械 压力降 沉浸式(数学) 机械工程 工程类 复合材料 计算机科学 数学 纯数学 物理 操作系统
作者
Shengchun Liu,Zhiming Xu,Zhi Ming Wang,Xueqiang Li,Haiwang Sun,Xinyu Zhang,Haoran Zhang
出处
期刊:Applied Thermal Engineering [Elsevier BV]
卷期号:245: 122864-122864 被引量:48
标识
DOI:10.1016/j.applthermaleng.2024.122864
摘要

Single-phase immersion cooling has emerged as a highly promising solution for addressing energy challenges and the substantial heat dissipation demands in data centers (DCs). The liquid cooling tank is a curial component in such system where numerous servers are immersed and the coolant are evenly flowed to each server. However, its performance and the comprehensive evaluation for the tank have not received much attention. In this study, by using the validated numerical model, the different tank structures, with or without consideration of baffle and porous panel, were firstly discussed. Then, four key parameters of tank, including inlet flowrate (Parameter A), the ratio of separation chamber height to server height (Parameter B), the ratio of pressure chamber height to server height (Parameter C), and the porosity of the porous panel (Parameter D) were explored in detail. Finally, the tank performance is evaluated and optimized by the orthogonal analysis and the entropy weight method (EWM). Results showed that, flow uniformity within the tank can be enhanced by incorporating a porous panel, and it was advisable to minimize the gaps between servers, despite the potential increase in pressure loss. Parameter A significantly impacted both the maximum temperature and pressure loss. Parameters B and C demonstrated effects on coolant weight and pressure loss, while Parameter D influenced pressure loss. By using orthogonal analysis and the EWM, maximum temperature carried the highest weight (0.362), followed by temperature difference (0.245), coolant weight (0.216), and pressure loss (0.177). The recommended values for Parameters A-D were 4 m3/h, 1.35 %, 4.05 %, and 11.33 %, respectively, which could be also considered as universality, since the comprehensive evaluation index only changed by 8 % when the server number increased from 10 to 40.
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