Cfd Modeling of the Distribution of Airborne Particulate Contaminants Inside Data Center Hardware

2021 ◽  
Author(s):  
Kaustubh Adsul ◽  
Satyam Saini ◽  
Pardeep Shahi ◽  
Amirreza Niazmand ◽  
Pratik Bansode ◽  
...  
Keyword(s):  
Data Center ◽  
Cfd Modeling ◽  
Airborne Particulate ◽  
Particulate Contaminants

Cfd Investigation of the Distribution and Dispersion of Airborne Particulate Contaminants Inside Data Center Hardware

2021 ◽  
Author(s):  
Satyam Saini ◽  
Kaustubh Adsul ◽  
Pardeep Shahi ◽  
Pratik Bansode ◽  
Amirreza Niazmand ◽  
...  
Keyword(s):  
Data Center ◽  
Airborne Particulate ◽  
Particulate Contaminants

CFD Modeling of the Distribution of Airborne Particulate Contaminants Inside Data Center Hardware

2020 ◽  
Author(s):  
Satyam Saini ◽  
Kaustubh K. Adsul ◽  
Pardeep Shahi ◽  
Amirreza Niazmand ◽  
Pratik Bansode ◽  
...  
Keyword(s):  
Data Center ◽  
High Performance ◽  
Phase Particle ◽  
Cfd Modeling ◽  
Air Cooling ◽  
Ambient Conditions ◽  
Particle Modeling ◽  
Free Air ◽  
Discrete Phase ◽  
Particulate Contaminants

Abstract 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.

Rack Level Modeling of Air Flow Through Perforated Tile in a Data Center

2012 ◽  
Author(s):  
Vaibhav K. Arghode ◽  
Pramod Kumar ◽  
Yogendra Joshi ◽  
Thomas S. Weiss ◽  
Gary Meyer
Keyword(s):  
Data Center ◽  
Body Force ◽  
Air Flow ◽  
The Body ◽  
Physical Models ◽  
Cfd Modeling ◽  
Computational Time ◽  
Force Model ◽  
Flow Through ◽  
Tile Surface

Effective air flow distribution through perforated tiles is required to efficiently cool servers in a raised floor data center. We present detailed computational fluid dynamics (CFD) modeling of air flow through a perforated tile and its entrance to the adjacent server rack. The realistic geometrical details of the perforated tile, as well as of the rack are included in the model. Generally models for air flow through perforated tiles specify a step pressure loss across the tile surface, or porous jump model based on the tile porosity. An improvement to this includes a momentum source specification above the tile to simulate the acceleration of the air flow through the pores, or body force model. In both of these models geometrical details of tile such as pore locations and shapes are not included. More details increase the grid size as well as the computational time. However, the grid refinement can be controlled to achieve balance between the accuracy and computational time. We compared the results from CFD using geometrical resolution with the porous jump and body force model solution as well as with the measured flow field using Particle Image Velocimetry (PIV) experiments. We observe that including tile geometrical details gives better results as compared to elimination of tile geometrical details and specifying physical models across and above the tile surface. A modification to the body force model is also suggested and improved results were achieved.

scholarly journals Airborne Particulate Contaminants During Refrigeration of Meat in Controled Medium

2011 ◽  
Vol 68 (2) ◽  
Author(s):  
C. JIANU ◽  
Ileana COCAN ◽  
A. RIVIT ◽  
Monica NEGREA ◽  
Corina MISCĂ ◽  
...  
Keyword(s):  
Potassium Dichromate ◽  
Meat Products ◽  
Processing System ◽  
Ethanol Solution ◽  
Modified Atmosphere ◽  
Airborne Particulate ◽  
Air Contamination ◽  
Volatile Metabolites ◽  
Major Interest ◽  
Particulate Contaminants

The transfer of contamination through the airborne route is one of the most significant areas of high-care food production. The food industry specially the manufacturing of the chilled meat products strive for lower levels of the air contamination, therefore lot of experimental and numerical studies considers the concentration of airborne particulate contaminants, such as different species of food spoilage microorganism. In a food processing system concerned with efficient and duration preservation of primary agricultural produce post-harvesting/post-slaughtering, low carbonylic compounds as potential volatile metabolites generated by the micro flora present in the modified atmosphere CO2/O2; N2/O2, etc. of refrigeration areas for wholesale or pre-packaged fresh meat are of major interest together with other risk factors of consumer food safety. Some low aliphatic ketones with high volatility can be seized by smelling even at freezing temperatures in an advanced stage of accumulation. In this paper we suggest a guick method for the measurement of their concentration expressed as MEK starting with values of 1 μg/m3 atmosphere (refrigeration environment) through periodical and/or continuous sampling through aspiration from the proximity of meat surface both pre-packed and stored in standard cells in modified atmosphere (25% CO2; 75% O2) (25% N2; 75% O2) in an ethanol solution of salicylaldehyde 10% (CAS 90-02-8) when it makes up a colorimetrable yellow-orange compound. Assessment can be done continuously in parallel with comparing the colour with a potassium dichromate scale (qualitatively) and also by reporting it to a sampling curve previously prepared (quantitatively). The specificity of the method is affected only by the presence in the refrigeration atmosphere of other toxic volatile metabolites of ketonic nature (acetone, acetoin, 2,3-butane dione).

Air Flow Pattern and Path Flow Simulation of Airborne Particulate Contaminants in a High-Density Data Center Utilizing Airside Economization

2018 ◽  
Author(s):  
Gautham Thirunavakkarasu ◽  
Satyam Saini ◽  
Jimil Shah ◽  
Dereje Agonafer
Keyword(s):  
Data Center ◽  
Carbon Particle ◽  
High Density ◽  
Submicron Particles ◽  
Air Cooling ◽  
Density Data ◽  
Particulate Contamination ◽  
Free Air ◽  
First Choice ◽  
Particulate Contaminants

The percentage of the energy used by data centers for cooling their equipment has been on the rise. With that, there has been a necessity for exploring new and more efficient methods like airside economization, both from an engineering as well as business point of view, to contain this energy demand. Air cooling especially, free air cooling has always been the first choice for IT companies to cool their equipment. But, it has its downside as well. As per ASHRAE standard (2009b), the air which is entering the data center should be continuously filtered with MERV 11 or preferably MERV 13 filters and the air which is inside the data center should be clean as per ISO class 8. The objective of this study is to design a model data center and simulate the flow path with the help of 6sigma room analysis software. A high-density data center was modelled for both hot aisle and cold aisle containment configurations. The particles taken into consideration for modelling were spherical in shape and of diameters 0.05, 0.1 and 1 micron. The physical properties of the submicron particles have been assumed to be same as that of air. For heavier particles of 1 micron in size, the properties of dense carbon particle are chosen for simulating particulate contamination in a data center. The Computer Room Air Conditioning unit is modelled as the source for the particulate contaminants which represents contaminants entering along with free air through an air-side economizer. The data obtained from this analysis can be helpful in predicting which type of particles will be deposited at what location based on its distance from the source and weight of the particles. This can further help in reinforcing the regions with a potential to fail under particulate contamination.

Creating a Calibrated CFD Model of a Midsize Data Center

2015 ◽  
Author(s):  
Zachary M. Pardey ◽  
James W. VanGilder ◽  
Christopher M. Healey ◽  
David W. Plamondon
Keyword(s):  
Data Center ◽  
Real Data ◽  
Measured Data ◽  
Cfd Modeling ◽  
Design Stage ◽  
Cfd Model ◽  
Modeling Techniques ◽  
Room Model ◽  
Tile Flow ◽  
Level Of Agreement

Calibrating a CFD model against measured data is the first step to successfully utilizing this technology for change-management and the optimization of an existing data center. To date, there has been very little published on this calibration process; more focus has been placed on the use of CFD at the design stage and the development of modeling techniques and solvers. Further, few studies which feature comprehensive comparisons of CFD-predicted and measured data have been published for real data centers, and many that have, demonstrated only modest agreement at best. This study provides another such comparison — for a 7,400 ft2 (687 m2), 138-rack, raised-floor facility. The goals of the study are to benchmark the level of agreement that can be practically obtained and also to investigate the level of modeling detail required. Additionally, specific practical advice covering both CFD modeling and experimental measurements is provided. A plenum-only CFD model is compared to measured tile airflow rates and a room-model, which uses measured tile flow rates as boundary conditions, is compared to temperatures measured at each rack inlet. The level of agreement is among the best published to date and demonstrates that a CFD model can be adequately calibrated against measured data and is of value for ongoing data center operation.

Simplified and Detailed Analysis of Data Center Particulate Contamination At Server and Room Level Using CFD

2021 ◽  
Author(s):  
Satyam Saini ◽  
Pardeep Shahi ◽  
Pratik V Bansode ◽  
Jimil M. Shah ◽  
Dereje Agonafer
Keyword(s):  
Detailed Analysis ◽  
Data Center ◽  
Particle Concentration ◽  
Heat Sinks ◽  
Cooling Power ◽  
Air Cooling ◽  
Component Reliability ◽  
Particulate Contamination ◽  
Free Air ◽  
Particulate Contaminants

Abstract Continuous rise in cloud computing and other web-based services propelled the data center proliferation seen over the past decade. Traditional data centers use vapor-compression-based cooling units that not only reduce energy efficiency but also increase operational and initial investment costs due to involved redundancies. Free air cooling and airside economization can substantially reduce the IT Equipment (ITE) cooling power consumption, which accounts for approximately 40% of energy consumption for a typical air-cooled data center. However, this cooling approach entails an inherent risk of exposing the IT equipment to harmful ultrafine particulate contaminants, thus, potentially reducing the equipment and component reliability. The present investigation attempts to quantify the effects of particulate contamination inside the data center equipment and ITE room using CFD. An analysis of the boundary conditions to be used was done by detailed modeling of IT equipment and the data center white space. Both 2-D and 3-D simulations were done for detailed analysis of particle transport within the server enclosure. An analysis of the effect of the primary pressure loss obstructions like heat sinks and DIMMs inside the server was done to visualize the localized particle concentrations within the server. A room-level simulation was then conducted to identify the most vulnerable locations of particle concentration within the data center space. The results show that parameters such as higher velocities, heat sink cutouts, and higher aspect ratio features within the server tend to increase the particle concentration inside the servers.

Identification and Characterization of Particulate Contaminants Found at a Data Center Using Airside Economization

2019 ◽  
Vol 141 (3) ◽  
Author(s):  
Jimil M. Shah ◽  
Abel Misrak ◽  
Dereje Agonafer ◽  
Mike Kaler
Keyword(s):  
Data Center ◽  
Energy Dispersive Spectrometer ◽  
Corrosion Damage ◽  
Real World Data ◽  
Metallic Particles ◽  
Equipment Reliability ◽  
Particulate Contaminants ◽  
Electrical Components ◽  
The Impact

Contamination due to the use of airside economizer has become a major issue that cost companies revenue. This issue will continue to rise as server components become smaller, densely packed, and as companies move into more polluted environments. Contaminants with small particles less than 10 μm are not noticeable; yet, these particles are most likely to get to areas where they can cause damage. Dust from different sources and suspended in air settles on surfaces of electrical components. The dust mainly contains two components: salts and metallic particles. The salts may be neutral or corrosive and the nature of the salt depends on the deliquescent humidity. For metallic particles, surveys are performed in various data centers in order to determine the limits in terms of weight per unit area and particle size distribution. It is necessary to first identify those contaminants that directly affect the information technology (IT) equipment in the data center. In this research, a real-world data center utilizing airside economization in an ANSI/ISA classified G2 environment was chosen for the study. Servers were removed and qualitative study of cumulative corrosion damage was carried out. The particulate contaminants were collected from different locations of a server and material characterization was performed using scanning electron microscopy (SEM), energy dispersive spectrometer (EDS), and Fourier transform infrared spectroscopy (FTIR). The analysis from these results helps to explain the impact of the contaminants on IT equipment reliability.

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