scholarly journals Continuous Learning Graphical Knowledge Unit for Cluster Identification in High Density Data Sets

Symmetry ◽  
2016 ◽  
Vol 8 (12) ◽  
pp. 152
Author(s):  
K.K.L.B. Adikaram ◽  
Mohamed Hussein ◽  
Mathias Effenberger ◽  
Thomas Becker
Keyword(s):  
High Density ◽  
Data Sets ◽  
Continuous Learning ◽  
Density Data ◽  
Cluster Identification ◽  
Knowledge Unit ◽  
Graphical Knowledge

25-Gb/s Clocked Pluggable Optics for High-Density Data Center Interconnections

2018 ◽  
Vol 65 (10) ◽  
pp. 1395-1399 ◽  
Author(s):  
Gyu-Seob Jeong ◽  
Jeongho Hwang ◽  
Hong-Seok Choi ◽  
Hyungrok Do ◽  
Daehyun Koh ◽  
...  
Keyword(s):  
Data Center ◽  
High Density ◽  
Density Data

Thermomechanical High-Density Data Storage in a Metallic Material Via the Shape-Memory Effect

2005 ◽  
Vol 17 (9) ◽  
pp. 1123-1127 ◽  
Author(s):  
G. A. Shaw ◽  
J. S. Trethewey ◽  
A. D. Johnson ◽  
W. J. Drugan ◽  
W. C. Crone
Keyword(s):  
Shape Memory ◽  
Shape Memory Effect ◽  
Memory Effect ◽  
Data Storage ◽  
High Density ◽  
Metallic Material ◽  
Density Data

Study, Tests, and Evaluation for Wideband High-Density Data Acquisition (WHIDDA).

1977 ◽  
Author(s):  
Charles F. Spitzer ◽  
Theodore A. Jensen ◽  
John M. Utschig
Keyword(s):  
Data Acquisition ◽  
High Density ◽  
Density Data

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.

scholarly journals Improvement in airflow and temperature distribution with an in-rack UFAD system at a high-density data center

2020 ◽  
Vol 168 ◽  
pp. 106495
Author(s):  
Xiaolei Yuan ◽  
Xinjie Xu ◽  
Jinxiang Liu ◽  
Yiqun Pan ◽  
Risto Kosonen ◽  
...  
Keyword(s):  
Temperature Distribution ◽  
Data Center ◽  
High Density ◽  
Density Data
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