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Title: Industrial Internet-of-Things & Data Analytics for Nuclear Power & Safeguards.

Abstract

Data analytics applied to nuclear power operations and nuclear safeguards is in a nascent state, yet some significant initial efforts are being undertaken by industry and academia. This report highlights our findings as to the current state-of-the-art of such efforts, in particular considering the Industrial Internet-of-Things aspect of this work, as well as an investigation into the utility of machine learning tools being developed for other industries. Blockchain applications were also studied. A consideration was undertaken into how to apply data analytics and machine learning to nuclear power and safeguards within the realm of Probabilistic Risk Assessments (PRAs), predictive maintenance & edge analytics, and proprietary data sharing.

Authors:
;  [1];  [1]
  1. UCB
Publication Date:
Research Org.:
Sandia National Lab. (SNL-CA), Livermore, CA (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA), Office of Defense Nuclear Nonproliferation (NA-20)
OSTI Identifier:
1481947
Report Number(s):
SAND2018-12807
669746
DOE Contract Number:  
AC04-94AL85000
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English

Citation Formats

Farley, David Rushton, Negus, Mitch G., and Slaybaugh, Rachel N. Industrial Internet-of-Things & Data Analytics for Nuclear Power & Safeguards.. United States: N. p., 2018. Web. doi:10.2172/1481947.
Farley, David Rushton, Negus, Mitch G., & Slaybaugh, Rachel N. Industrial Internet-of-Things & Data Analytics for Nuclear Power & Safeguards.. United States. doi:10.2172/1481947.
Farley, David Rushton, Negus, Mitch G., and Slaybaugh, Rachel N. Thu . "Industrial Internet-of-Things & Data Analytics for Nuclear Power & Safeguards.". United States. doi:10.2172/1481947. https://www.osti.gov/servlets/purl/1481947.
@article{osti_1481947,
title = {Industrial Internet-of-Things & Data Analytics for Nuclear Power & Safeguards.},
author = {Farley, David Rushton and Negus, Mitch G. and Slaybaugh, Rachel N.},
abstractNote = {Data analytics applied to nuclear power operations and nuclear safeguards is in a nascent state, yet some significant initial efforts are being undertaken by industry and academia. This report highlights our findings as to the current state-of-the-art of such efforts, in particular considering the Industrial Internet-of-Things aspect of this work, as well as an investigation into the utility of machine learning tools being developed for other industries. Blockchain applications were also studied. A consideration was undertaken into how to apply data analytics and machine learning to nuclear power and safeguards within the realm of Probabilistic Risk Assessments (PRAs), predictive maintenance & edge analytics, and proprietary data sharing.},
doi = {10.2172/1481947},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {11}
}