数据中心硬件内部空气悬浮污染物分布的CFD模拟

S. Saini, Kaustubh Adsul, Pardeep Shahi, Amirreza Niazmand, Pratik V. Bansode, D. Agonafer
{"title":"数据中心硬件内部空气悬浮污染物分布的CFD模拟","authors":"S. Saini, Kaustubh Adsul, Pardeep Shahi, Amirreza Niazmand, Pratik V. Bansode, D. Agonafer","doi":"10.1115/ipack2020-2590","DOIUrl":null,"url":null,"abstract":"\n Modern-day data center administrators are finding it increasingly difficult to lower the costs incurred in mechanical cooling of their IT equipment. This is especially true for high-performance computing facilities like Artificial Intelligence, Bitcoin Mining, and Deep Learning, etc. Airside Economization or free air cooling has been out there as a technology for a long time now to reduce the mechanical cooling costs. In free air cooling, under favorable ambient conditions of temperature and humidity, outside air can be used for cooling the IT equipment. In doing so, the IT equipment is exposed to sub-micron particulate/gaseous contaminants that might enter the data center facility with the cooling airflow.\n The present investigation uses a computational approach to model the airflow paths of particulate contaminants entering inside the IT equipment using a commercially available CFD code. A Discrete Phase Particle modeling approach is chosen to calculate trajectories of the dispersed contaminants. Standard RANS approach is used to model the airflow in the airflow and the particles are superimposed on the flow field by the CFD solver using Lagrangian particle tracking. The server geometry was modeled in 2-D with a combination of rectangular and cylindrical obstructions. This was done to comprehend the effect of change in the obstruction type and aspect ratio on particle distribution. Identifying such discrete areas of contaminant proliferation based on concentration fields due to changing geometries will help with the mitigation of particulate contamination related failures in data centers.","PeriodicalId":199024,"journal":{"name":"ASME 2020 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"CFD Modeling of the Distribution of Airborne Particulate Contaminants Inside Data Center Hardware\",\"authors\":\"S. Saini, Kaustubh Adsul, Pardeep Shahi, Amirreza Niazmand, Pratik V. Bansode, D. Agonafer\",\"doi\":\"10.1115/ipack2020-2590\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Modern-day data center administrators are finding it increasingly difficult to lower the costs incurred in mechanical cooling of their IT equipment. This is especially true for high-performance computing facilities like Artificial Intelligence, Bitcoin Mining, and Deep Learning, etc. Airside Economization or free air cooling has been out there as a technology for a long time now to reduce the mechanical cooling costs. In free air cooling, under favorable ambient conditions of temperature and humidity, outside air can be used for cooling the IT equipment. In doing so, the IT equipment is exposed to sub-micron particulate/gaseous contaminants that might enter the data center facility with the cooling airflow.\\n The present investigation uses a computational approach to model the airflow paths of particulate contaminants entering inside the IT equipment using a commercially available CFD code. A Discrete Phase Particle modeling approach is chosen to calculate trajectories of the dispersed contaminants. Standard RANS approach is used to model the airflow in the airflow and the particles are superimposed on the flow field by the CFD solver using Lagrangian particle tracking. The server geometry was modeled in 2-D with a combination of rectangular and cylindrical obstructions. This was done to comprehend the effect of change in the obstruction type and aspect ratio on particle distribution. Identifying such discrete areas of contaminant proliferation based on concentration fields due to changing geometries will help with the mitigation of particulate contamination related failures in data centers.\",\"PeriodicalId\":199024,\"journal\":{\"name\":\"ASME 2020 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ASME 2020 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1115/ipack2020-2590\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ASME 2020 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/ipack2020-2590","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

现代数据中心管理员发现,降低it设备的机械冷却成本越来越困难。对于人工智能、比特币挖矿和深度学习等高性能计算设施来说尤其如此。空侧节约或自然空气冷却作为一项技术已经存在很长时间了,现在可以降低机械冷却成本。在自然风冷时,在温度和湿度较好的环境条件下,可以利用外部空气对IT设备进行冷却。在这样做的过程中,IT设备暴露在亚微米颗粒/气体污染物中,这些污染物可能随着冷却气流进入数据中心设施。本研究使用计算方法模拟颗粒污染物进入IT设备内部的气流路径,并使用市售CFD代码。采用离散相粒子建模方法来计算分散污染物的运动轨迹。采用标准的RANS方法对气流中的气流进行建模,采用拉格朗日粒子跟踪的CFD求解器将颗粒叠加到流场上。服务器的几何形状以矩形和圆柱形障碍物组合的二维形式建模。这样做是为了了解障碍物类型和展弦比的变化对颗粒分布的影响。根据由于几何形状变化而产生的浓度场确定这种污染物扩散的离散区域,将有助于减轻数据中心中与颗粒污染有关的故障。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CFD Modeling of the Distribution of Airborne Particulate Contaminants Inside Data Center Hardware
Modern-day data center administrators are finding it increasingly difficult to lower the costs incurred in mechanical cooling of their IT equipment. This is especially true for high-performance computing facilities like Artificial Intelligence, Bitcoin Mining, and Deep Learning, etc. Airside Economization or free air cooling has been out there as a technology for a long time now to reduce the mechanical cooling costs. In free air cooling, under favorable ambient conditions of temperature and humidity, outside air can be used for cooling the IT equipment. In doing so, the IT equipment is exposed to sub-micron particulate/gaseous contaminants that might enter the data center facility with the cooling airflow. The present investigation uses a computational approach to model the airflow paths of particulate contaminants entering inside the IT equipment using a commercially available CFD code. A Discrete Phase Particle modeling approach is chosen to calculate trajectories of the dispersed contaminants. Standard RANS approach is used to model the airflow in the airflow and the particles are superimposed on the flow field by the CFD solver using Lagrangian particle tracking. The server geometry was modeled in 2-D with a combination of rectangular and cylindrical obstructions. This was done to comprehend the effect of change in the obstruction type and aspect ratio on particle distribution. Identifying such discrete areas of contaminant proliferation based on concentration fields due to changing geometries will help with the mitigation of particulate contamination related failures in data centers.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信