A review of thermal management and innovative cooling strategies for data center

Nadjahi, Chayan; Louahlia-Gualous, H.; Lemasson, Stéphane

doi:10.1016/j.suscom.2018.05.002

Cited by 122 publications

(92 citation statements)

References 30 publications

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“…If the temperature difference ΔT between the chilled water inlet and outlet temperatures is assumed to be constant 5.5 °C, the functions for the chilled water temperature changes can be expressed as Equation (5). Therefore, the circulation n + 1th chilled water supply temperature is nth chilled water supply temperature +5.5 °C.…”

Section: Temperature Increase Over Time After a Cooling System Outagementioning

confidence: 99%

“…Data centers strengthen their stability by having redundant power supply paths, including emergency generators, UPSs, etc. IT servers require uninterruptible supplies of not only power, but also cooling [4][5][6]. For this purpose, central cooling systems are designed to allow for chilled water supply during cooling system outages by including cooling buffer tanks for stable cooling of IT equipment.…”

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Thermal Performance Evaluation of a Data Center Cooling System under Fault Conditions

Cho

Park²,

Jeong³

2019

Energies

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If a data center experiences a system outage or fault conditions, it becomes difficult to provide a stable and continuous information technology (IT) service. Therefore, it is critical to design and implement a backup system so that stability can be maintained even in emergency (unforeseen) situations. In this study, an actual 20 MW data center project was analyzed to evaluate the thermal performance of an IT server room during a cooling system outage under six fault conditions. In addition, a method of organizing and systematically managing operational stability and energy efficiency verification was identified for data center construction in accordance with the commissioning process. Up to a chilled water supply temperature of 17 • C and a computer room air handling unit air supply temperature of 24 • C, the temperature of the air flowing into the IT server room fell into the allowable range specified by the American Society of Heating, Refrigerating, and Air-Conditioning Engineers standard (18-27 • C). It was possible to perform allowable operations for approximately 320 s after cooling system outage. Starting at a chilled water supply temperature of 18 • C and an air supply temperature of 25 • C, a rapid temperature increase occurred, which is a serious cause of IT equipment failure. Due to the use of cold aisle containment and designs with relatively high chilled water and air supply temperatures, there is a high possibility that a rapid temperature increase inside an IT server room will occur during a cooling system outage. Thus, the backup system must be activated within 300 s. It is essential to understand the operational characteristics of data centers and design optimal cooling systems to ensure the reliability of high-density data centers. In particular, it is necessary to consider these physical results and to perform an integrated review of the time required for emergency cooling equipment to operate as well as the backup system availability time.As shown in Figure 1, considerable technological infrastructure is required in data centers to meet even the minimum requirements for Tier 1 system availability (96.671% uptime per year), which is the basic level. In specialized colocation data centers for business purposes, enormous system construction costs are required for uninterrupted system operation to ensure Tier 3-4 high availability (95.995-99.982% uptime) [3]. On the other hand, interest in environmental problems such as global warming and the demand for low-energy and high-efficiency buildings is increasing, so the use of excessive facilities in the pursuit of reliability alone must be avoided. Considering these facts, ensuring stable and efficient performance is an important aspect of data center design and implementation. Conventional construction methods are focused on tangible results such as the construction period and financial costs (not quality) necessary to set up the data center infrastructure according to the design plans, which can make it difficult to verify whether non-IT equipment ...

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Section: Temperature Increase Over Time After a Cooling System Outagementioning

confidence: 99%

mentioning

confidence: 99%

Thermal Performance Evaluation of a Data Center Cooling System under Fault Conditions

Cho

Park²,

Jeong³

2019

Energies

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“…DCs maintain their stability by having redundant power supply paths, including emergency generators, UPSs, etc. IT servers require uninterruptible supplies of not only power but also cooling [3,4]. For this purpose, in liquid cooling, central cooling systems are designed and manage to allow for chilled water supply during cooling system outages by including cooling buffer tanks for stable cooling of IT equipment.…”

Section: Introductionmentioning

confidence: 99%

A Machine Learning Solution for Data Center Thermal Characteristics Analysis

Chinnici¹,

Grishina²,

Kor³

et al. 2020

Preprint

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Energy efficiency of Data Center (DC) operations heavily relies on IT and cooling systems performance. A reliable and efficient cooling system is necessary to produce a persistent flow of cold air to cool servers that are subjected to constantly increasing computational load due to the advent of IoT- enabled smart systems. Consequently, increased demand for computing power will bring about increased waste heat dissipation in data centers. In order to bring about a DC energy efficiency, it is imperative to explore the thermal characteristics analysis of an IT room (due to waste heat). This work encompasses the employment of an unsupervised machine learning modelling technique for uncovering weaknesses of the DC cooling system based on real DC monitoring thermal data. The findings of the analysis result in the identification of areas for energy efficiency improvement that will feed into DC recommendations. The methodology employed for this research includes statistical analysis of IT room thermal characteristics, and the identification of individual servers that frequently occur in the hotspot zones. A critical analysis has been conducted on available big dataset of ambient air temperature in the hot aisle of ENEA Portici CRESCO6 computing cluster. Clustering techniques have been used for hotspots localization as well as categorization of nodes based on surrounding air temperature ranges. The principles and approaches covered in this work are replicable for energy efficiency evaluation of any DC and thus, foster transferability. This work showcases applicability of best practices and guidelines in the context of a real commercial DC that transcends the set of existing metrics for DC energy efficiency assessment.

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“…Optimizing data centre power consumption is high on the priority list of data centre managers. However, it continues to reveal challenges given the increasing percentage of ongoing costs that this consumption represents [4]. For instance, the ventilation and cooling system absorbs almost 40% of the overall energy consumption in a data centre [5], since the majority of the energy consumed by the data centre equipment is converted into heat [6].…”

Section: Introductionmentioning

confidence: 99%

Improving Airflow and Thermal Distribution in a Real Data Centre Room Through Computational Fluid Dynamics Modeling

Macedo

Gaspar²,

Silva³

et al. 2019

2019 8th International Conference on Industrial Technology and Management (ICITM)

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A Data Centre is a physical space that groups together computer equipment such as servers, storage arrays, among other equipment. It can be used for storage, processing and data protection. The majority of data centres operate 24 hours a day, and must provide the user with guarantees in terms of security and performance. Energy consumption is therefore permanent and the level of assistance and maintenance high. Data Centres have an ecological impact that is almost invisible to many users. In this paper a computational fluid dynamics (CFD) model of the airflow and thermal distribution of a real data centre room with 208 racks is proposed. Two case studies are presented and simulated with a high thermal load subjected to the minimum and maximum air flow velocity, respectively. The objective is to assess if the computer room air conditioning unit (CRAC) can cool the racks of the data centre in order to efficiently refrigerate all the hot spots.

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A review of thermal management and innovative cooling strategies for data center

Cited by 122 publications

References 30 publications

Thermal Performance Evaluation of a Data Center Cooling System under Fault Conditions

Thermal Performance Evaluation of a Data Center Cooling System under Fault Conditions

A Machine Learning Solution for Data Center Thermal Characteristics Analysis

Improving Airflow and Thermal Distribution in a Real Data Centre Room Through Computational Fluid Dynamics Modeling

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