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STUDY OF THE FACTORS THAT AFFECT ACCLIMATION TIME FOR IT EQUIPMENT

Neil Johnson V ,Abel Misrak, Mullai Varadharasan, R Lakshminarashimhan, Dereje Agonafer

Department of Mechanical and Aerospace Engineering, University of Texas at Arlington, Arlington, TX 76019

ABSTRACTNewly commissioned IT equipment usually tend to have condensation on them due to the change in temperature and humidity conditions encountered during shipping. Acclimation of IT equipment is an important step in order to prevent an unnecessary condensation from forming and causing premature failure in the equipment. Acclimation is particularly important in cold weather shipping where the component or server reaches the destination well below the destination data center’s dew point, resulting in moisture and condensate. This study tries to address the issue by studying the various factors that affect acclimation and prioritizing them. In this poster, previous work done on acclimation modeling was used as a basis to study and understand how different factors influence and affect acclimation time of servers and components. The temperature of different components of a server were tracked during a simulated shipping conditions using a Thermotron environmental chamber. From the obtained results, it was observed that the various components of the server acclimate at different rates. The results from this work coupled with humidity conditions would be used to identify and prioritize the different factors that affect acclimation time of server components.

BACKGROUNDAcclimation allows equipment that may have been packaged and shipped in a variety of environmental conditions to adjust to the new data center environment before being powered on. This issue is particularly critical in cold weather shipping where a computing system can reach the destination well below the destination data center’s dew point, resulting in moisture (or even frosting) forming on the cold surfaces. Powering on or even connecting a system to power in this condition can create shorts and damage.

Acclimation requirements can vary significantly and be too conservative or too vague, leading to misunderstanding of the phenomena, its impact on the system, and the time needed for a system to remain unpowered during installation. Waiting too long is costly for the user due to lost computation time, while waiting too little could lead to damaged equipment and loss of computing system.

METHOD

Condensation seen inside the environmental chamber on and around the

servers

RESULTS

DISCUSSION

Server with thermocouples attached to

different components shown in yellow arrow

and DHT22 sensor shown in red oval.

• The Fan and memory has a time constant of 0.41 hrs, followed by the Heat sink with a time constant of 0.52 hrs and finally the hard disk with a time constant of 0.82 hrs

• The significant difference in the thermal time constants of the different components emphasizes the complexity of the environment within the server. This phenomenon will be further investigated in the next part of the project

• A Thermotron environmental chamber was used to simulate the environmental conditions encountered during shipping

• Thermocouple (Type T) was attached to the different components in the server which were read by the Agilent DAQ, to give us the acclimation time of different components

• The environmental chamber was programmed to simulate the temperature profile shown below

𝑇−𝑇𝑓

𝑇𝑖−𝑇𝑓=𝑒−𝑡ℎ𝑟𝑠/𝑡𝑐

The main objective of the work presented in this poster is to identify and prioritizethe factors that affect acclimation time such as mass, packaging, surface area-to-volume ratio etc. that influence the total acclimation time of: 1) Servers – U/2Ucompute, disk enclosures etc. 2)Components – modules, memory, disk drives, fans,cold plates, heatsinks, cables, etc.

The final goal of this project is to develop a transient model that can be applied forservers and components to allow a user to determine how long one needs to waitbefore a system can be powered-on or before a particular component can beinstalled in a running server.

FUTURE WORK

OBJECTIVE

ComponentsTime

constant(hrs)

Standard

Error

Reduced

Chi-SqrAdj. R Sqr

Fan 0.41 0.00204 3.03207 0.9687

Heat Sink 0.52 0.0021 3.19533 0.97747

Memory 0.41 0.00213 3.37264 0.96692

Hard disk 0.82 0.00204 2.35263 0.988

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0 2 4 6 8 10 12 14 16 18 20

Tem

per

atu

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°C)

Time(hrs)

Temperature Profile Used for the Experiment

Thermotron

SE-600-10-10

The results from the tracking of the temperature of the different components are shown below. From the shown results, it is evident that the different components acclimate at different rates.

EXPERIMENTAL SET UP• All component temperatures follow a lumped thermal capacitance model as shown

below where 𝑡ℎ𝑟𝑠 is the time in hours, 𝑡𝑐 is the time constant and T is the temperature at different points in time in degree Celsius

• A commercially available data analysis software, OriginPro, was used to curve-fit the above obtained data to the lumped capacitance model

• From the curve-fitting the time constants for the various components was obtained and is tabulated below

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0 0.5 1 1.5 2 2.5 3 3.5 4 4.5

Tem

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Time(Hrs)

Acclimation of Various Components

Heat Sink Memory Fan Hard Disk Control

• In this poster, humidity tracking during acclimation and the effect of factors like mass, surface area to volume , packaging to the acclimation time wasn’t covered, which will be the next set of experiments for the coming weeks

• Transient model will be prepared in order to allow a user to determine how long one needs to wait before safely powering on the server without damaging the components and wasting computational time

• Best practices for acclimation of IT equipment and components will be identified and documented