scholarly journals Nuclear Structure and Radioactive Decay Resources at the US National Nuclear Data Center

2007 ◽  
Author(s):  
A. A. Sonzogni ◽  
T. W. Burrows ◽  
B. Pritychenko ◽  
J. K. Tuli ◽  
D. F. Winchell
Keyword(s):  
Nuclear Structure ◽  
Data Center ◽  
Radioactive Decay ◽  
Nuclear Data ◽  
The Us

scholarly journals Texas A&M US Nuclear DATA Program

2021 ◽  
Vol 252 ◽  
pp. 08001
Author(s):  
Ninel Nica
Keyword(s):  
Nuclear Structure ◽  
Nuclear Physics ◽  
World Literature ◽  
National Laboratory ◽  
Nuclear Data ◽  
Data File ◽  
The United States ◽  
Brookhaven National Laboratory ◽  
The Us ◽  
Data Program

Nuclear data evaluation is an independent century-long expert activity accompanying the development of the nuclear physics science. Its goal is to produce periodic surveys of the world literature in order to recommend and maintain the set of the best nuclear data parameters of common use in all basic and applied sciences. After WWII the effort extended and while it became more international it continued to be supported mainly by the US for the benefit of the whole world. The Evaluated Nuclear Structure Data File (ENSDF) is the most comprehensive nuclear structure database worldwide maintained by the United States National Nuclear Data Center(NNDC)at Brookhaven National Laboratory(BNL)and echoed by the IAEA Vienna Nuclear Data Services. Part of the US Nuclear Data Program since 2005 the Cyclotron Institute is one of the important contributors to ENSDF. Since 2018 we became an international evaluation center working in a consortium of peers hosted traditionally by prestigious national institutes as well as universities. In this paper the main stages of the evaluation work are presented in order to facilitate a basic understanding of the process as a guide for our potential users. Our goals are to maintain a good productivity vs. quality performance assuring the currency of the data and participating in the effort of modernizing the structure of ENSDF databases in order to make them compatible with the data-centric paradigms of the future.

scholarly journals An Artificial Neural Network Approach to Forecast the Environmental Impact of Data Centers

Information ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 113 ◽  
Author(s):  
Joao Ferreira ◽  
Gustavo Callou ◽  
Albert Josua ◽  
Dietmar Tutsch ◽  
Paulo Maciel
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Energy Consumption ◽  
Co2 Emissions ◽  
Data Center ◽  
Data Centers ◽  
New Technologies ◽  
Operational Costs ◽  
The Us ◽  
Artificial Neural

Due to the high demands of new technologies such as social networks, e-commerce and cloud computing, more energy is being consumed in order to store all the data produced and provide the high availability required. Over the years, this increase in energy consumption has brought about a rise in both the environmental impacts and operational costs. Some companies have adopted the concept of a green data center, which is related to electricity consumption and CO2 emissions, according to the utility power source adopted. In Brazil, almost 70% of electrical power is derived from clean electricity generation, whereas in China 65% of generated electricity comes from coal. In addition, the value per kWh in the US is much lower than in other countries surveyed. In the present work, we conducted an integrated evaluation of costs and CO2 emissions of the electrical infrastructure in data centers, considering the different energy sources adopted by each country. We used a multi-layered artificial neural network, which could forecast consumption over the following months, based on the energy consumption history of the data center. All these features were supported by a tool, the applicability of which was demonstrated through a case study that computed the CO2 emissions and operational costs of a data center using the energy mix adopted in Brazil, China, Germany and the US. China presented the highest CO2 emissions, with 41,445 tons per year in 2014, followed by the US and Germany, with 37,177 and 35,883, respectively. Brazil, with 8459 tons, proved to be the cleanest. Additionally, this study also estimated the operational costs assuming that the same data center consumes energy as if it were in China, Germany and Brazil. China presented the highest kWh/year. Therefore, the best choice according to operational costs, considering the price of energy per kWh, is the US and the worst is China. Considering both operational costs and CO2 emissions, Brazil would be the best option.

Nuclear data relevant to the production and application of diagnostic radionuclide

2001 ◽  
Vol 89 (4-5) ◽  
Author(s):  
Syed M. Qaim
Keyword(s):  
Radioactive Decay ◽  
Nuclear Data ◽  
Decay Data

The types of nuclear data and their quality required in the production and application of diagnostic radionuclides are outlined. The radioactive decay data determine the suitability of a radioisotope for

scholarly journals Completeness of neutron-, photo-induced and spontaneous fission yields data

2020 ◽  
Vol 239 ◽  
pp. 09003
Author(s):  
B. Pritychenko ◽  
O. Schwerer ◽  
J. Totans ◽  
V. Zerkin ◽  
O. Gritzay
Keyword(s):  
Nuclear Reaction ◽  
Cross Sections ◽  
Data Center ◽  
Nuclear Data ◽  
Published Data ◽  
Data Sets ◽  
Scientific Publications ◽  
Nuclear Science ◽  
And Storage ◽  
Fission Yields

Nuclear data collection, evaluation and dissemination activities have been performed worldwide for many years. They are absolutely essential for the overall progress of science and technology to create the complete collections of experimental data sets and associated publications, and store these data in publicly accessible databases. Due to many historical and technological reasons not all published data have been identified and compiled. These "missing data" manifest themselves via scientific publications, data evaluations and nuclear databases comparisons. The detailed analysis of the Nuclear Science References (NSR) and the Experimental Nuclear Reaction (EXFOR) databases shows thousands of previously missed nuclear reaction experiments and creates a roadmap for the creation of complete data records for fission cross sections, yields and covariances. The National Nuclear Data Center (NNDC) program for identification, compilation and storage of missing fission yields data sets is described, and recommendations for improving the databases completeness are given.

scholarly journals NNDC (National Nuclear Data Center) on-line services documentation

1987 ◽  
Author(s):  
C.L. Dunford ◽  
T.W. Burrows ◽  
J.K. Tuli
Keyword(s):  
Data Center ◽  
Nuclear Data ◽  
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