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Title: Seamless Digital Environment – Plan for Data Analytics Use Case Study

Abstract

The U.S Department of Energy Light Water Reactor Sustainability (LWRS) Program initiated research in to what is needed in order to provide a roadmap or model for Nuclear Power Plants to reference when building an architecture that can support the growing data supply and demand flowing through their networks. The Digital Architecture project published report Digital Architecture Planning Model (Oxstrand et. al, 2016) discusses things to consider when building an architecture to support the increasing needs and demands of data throughout the plant. Once the plant is able to support the data demands it still needs to be able to provide the data in an easy, quick and reliable method. A common method is to create a “one stop shop” application that a user can go to get all the data they need. The creation of this leads to the need of creating a Seamless Digital Environment (SDE) to integrate all the “siloed” data. An SDE is the desired perception that should be presented to users by gathering the data from any data source (e.g., legacy applications and work management systems) without effort by the user. The goal for FY16 was to complete a feasibility study for data mining andmore » analytics for employing information from computer-based procedures enabled technologies for use in developing improved business analytics. The research team collaborated with multiple organizations to identify use cases or scenarios, which could be beneficial to investigate in a feasibility study. Many interesting potential use cases were identified throughout the FY16 activity. Unfortunately, due to factors out of the research team’s control, none of the studies were initiated this year. However, the insights gained and the relationships built with both PVNGS and NextAxiom will be valuable when moving forward with future research. During the 2016 annual Nuclear Information Technology Strategic Leadership (NITSL) group meeting it was identified would be very beneficial to the industry to support a research effort focused on data analytics. It was suggested that the effort would develop and evaluate use cases for data mining and analytics for employing information from plant sensors and database for use in developing improved business analytics.« less

Authors:
 [1];  [1]
  1. Idaho National Lab. (INL), Idaho Falls, ID (United States)
Publication Date:
Research Org.:
Idaho National Lab. (INL), Idaho Falls, ID (United States)
Sponsoring Org.:
USDOE Office of Nuclear Energy (NE)
OSTI Identifier:
1344174
Report Number(s):
INL/EXT-16-39985
DOE Contract Number:
AC07-05ID14517
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS; 97 MATHEMATICS AND COMPUTING; seamless digital environment

Citation Formats

Oxstrand, Johanna, and Bly, Aaron. Seamless Digital Environment – Plan for Data Analytics Use Case Study. United States: N. p., 2016. Web. doi:10.2172/1344174.
Oxstrand, Johanna, & Bly, Aaron. Seamless Digital Environment – Plan for Data Analytics Use Case Study. United States. doi:10.2172/1344174.
Oxstrand, Johanna, and Bly, Aaron. Thu . "Seamless Digital Environment – Plan for Data Analytics Use Case Study". United States. doi:10.2172/1344174. https://www.osti.gov/servlets/purl/1344174.
@article{osti_1344174,
title = {Seamless Digital Environment – Plan for Data Analytics Use Case Study},
author = {Oxstrand, Johanna and Bly, Aaron},
abstractNote = {The U.S Department of Energy Light Water Reactor Sustainability (LWRS) Program initiated research in to what is needed in order to provide a roadmap or model for Nuclear Power Plants to reference when building an architecture that can support the growing data supply and demand flowing through their networks. The Digital Architecture project published report Digital Architecture Planning Model (Oxstrand et. al, 2016) discusses things to consider when building an architecture to support the increasing needs and demands of data throughout the plant. Once the plant is able to support the data demands it still needs to be able to provide the data in an easy, quick and reliable method. A common method is to create a “one stop shop” application that a user can go to get all the data they need. The creation of this leads to the need of creating a Seamless Digital Environment (SDE) to integrate all the “siloed” data. An SDE is the desired perception that should be presented to users by gathering the data from any data source (e.g., legacy applications and work management systems) without effort by the user. The goal for FY16 was to complete a feasibility study for data mining and analytics for employing information from computer-based procedures enabled technologies for use in developing improved business analytics. The research team collaborated with multiple organizations to identify use cases or scenarios, which could be beneficial to investigate in a feasibility study. Many interesting potential use cases were identified throughout the FY16 activity. Unfortunately, due to factors out of the research team’s control, none of the studies were initiated this year. However, the insights gained and the relationships built with both PVNGS and NextAxiom will be valuable when moving forward with future research. During the 2016 annual Nuclear Information Technology Strategic Leadership (NITSL) group meeting it was identified would be very beneficial to the industry to support a research effort focused on data analytics. It was suggested that the effort would develop and evaluate use cases for data mining and analytics for employing information from plant sensors and database for use in developing improved business analytics.},
doi = {10.2172/1344174},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Sep 01 00:00:00 EDT 2016},
month = {Thu Sep 01 00:00:00 EDT 2016}
}

Technical Report:

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  • The U.S Department of Energy Light Water Reactor Sustainability (LWRS) Program initiated research in to what is needed in order to provide a roadmap or model for Nuclear Power Plants to reference when building an architecture that can support the growing data supply and demand flowing through their networks. The Digital Architecture project published report Digital Architecture Planning Model (Oxstrand et. al, 2016) discusses things to consider when building an architecture to support the increasing needs and demands of data throughout the plant. Once the plant is able to support the data demands it still needs to be able tomore » provide the data in an easy, quick and reliable method. A common method is to create a “one stop shop” application that a user can go to get all the data they need. The creation of this leads to the need of creating a Seamless Digital Environment (SDE) to integrate all the “siloed” data. An SDE is the desired perception that should be presented to users by gathering the data from any data source (e.g., legacy applications and work management systems) without effort by the user. The goal for FY16 was to complete a feasibility study for data mining and analytics for employing information from computer-based procedures enabled technologies for use in developing improved business analytics. The research team collaborated with multiple organizations to identify use cases or scenarios, which could be beneficial to investigate in a feasibility study. Many interesting potential use cases were identified throughout the FY16 activity. Unfortunately, due to factors out of the research team’s control, none of the studies were initiated this year. However, the insights gained and the relationships built with both PVNGS and NextAxiom will be valuable when moving forward with future research. During the 2016 annual Nuclear Information Technology Strategic Leadership (NITSL) group meeting it was identified would be very beneficial to the industry to support a research effort focused on data analytics. It was suggested that the effort would develop and evaluate use cases for data mining and analytics for employing information from plant sensors and database for use in developing improved business analytics.« less
  • Multiple research efforts in the U.S Department of Energy Light Water Reactor Sustainability (LWRS) Program studies the need and design of an underlying architecture to support the increased amount and use of data in the nuclear power plant. More specifically the three LWRS research efforts; Digital Architecture for an Automated Plant, Automated Work Packages, Computer-Based Procedures for Field Workers, and the Online Monitoring efforts all have identified the need for a digital architecture and more importantly the need for a Seamless Digital Environment (SDE). A SDE provides a mean to access multiple applications, gather the data points needed, conduct themore » analysis requested, and present the result to the user with minimal or no effort by the user. During the 2016 annual Nuclear Information Technology Strategic Leadership (NITSL) group meeting the nuclear utilities identified the need for research focused on data analytics. The effort was to develop and evaluate use cases for data mining and analytics for employing information from plant sensors and database for use in developing improved business analytics. The goal of the study is to research potential approaches to building an analytics solution for equipment reliability, on a small scale, focusing on either a single piece of equipment or a single system. The analytics solution will likely consist of a data integration layer, predictive and machine learning layer and the user interface layer that will display the output of the analysis in a straight forward, easy to consume manner. This report describes the use case study initiated by NITSL and conducted in a collaboration between Idaho National Laboratory, Arizona Public Service – Palo Verde Nuclear Generating Station, and NextAxiom Inc.« less
  • As technology continues to evolve and become more integrated into a worker’s daily routine in the Nuclear Power industry the need for easy access to data becomes a priority. Not only does the need for data increase but the amount of data collected increases. In most cases the data is collected and stored in various software applications, many of which are legacy systems, which do not offer any other option to access the data except through the application’s user interface. Furthermore the data gets grouped in “silos” according to work function and not necessarily by subject. Hence, in order tomore » access all the information needed for a particular task or analysis one may have to access multiple applications to gather all the data needed. The industry and the research community have identified the need for a digital architecture and more importantly the need for a Seamless Digital Environment. An SDE provides a means to access multiple applications, gather the data points needed, conduct the analysis requested, and present the result to the user with minimal or no effort by the user. In addition, the nuclear utilities have identified the need for research focused on data analytics. The effort should develop and evaluate use cases for data mining and analytics for employing information from plant sensors and database for use in developing improved business analytics. Idaho National Laboratory is leading such effort, which is conducted in close collaboration with vendors, nuclear utilities, Institute of Nuclear Power Operations, and Electric Power Research Institute. The goal of the study is to research potential approaches to building an analytics solution for equipment reliability, on a small scale, focusing on either a single piece of equipment or a single system. The analytics solution will likely consist of a data integration layer, predictive and machine learning layer and the user interface layer that will display the output of the analysis in a straight forward, easy to consume manner. This paper will describe the study and the initial results.« less
  • This report describes a new methodology for developing statistically reliable, end-use load information for commercial markets. DOE-2 energy models and statistical data leveraging were used to combine information from billing data, a commercial survey, available whole-premise load data and a small amount of transferred and self generated end use metering. Site-specific DOE-2 models were developed to describe the actual operation of a sample of offices, based on each site`s characteristics data and conventional whole-premise load data. These DOE-2 models generated end-use profiles which were projected to the office market segment using the billing and survey data. End-use metered data, whichmore » was available for a subsample, was used to develop more accurate DOE-2 models which, in turn, were used to true up the results of the full sample. Statistical methods were used to select the sample sites, adjust the survey data for multiple account bias and misclassification, evaluate the statistical precision of the end use results, assess the value of the end use metering, and guide future data development. The report describes the findings and methodology, and discusses the lessons that were learned. The methodology demonstrated in this project promises to provide less expensive end-use data with better measures of statistical precision in less time than conventional approaches. Compared to prototype-building models, the new methodology offers better representation of actual operating conditions, reduced risk of bias, and measured statistical precision at the end use level. Compared to conventional end use metering, and given a preexisting commercial survey and load research data, this approach can generate results in months instead of years, at 50% or less cost, with less customer intrusiveness. Moreover, the methodology can address ``what if`` analysis, provide weather adjustment, and support transferability between areas and over time.« less
  • The use of computer aided classification of LANDSAT data in developing water quality plans for New Jersey watersheds is used to exemplify how a state natural resource management program benefits from satellite imagery. The transition of a research and development system into an operational remote sensing system to help decision makers is demonstrated. Nontechnial issues that can assist (or hinder) an agency in adopting a new technology are examined. The progress of LANDSAT use by state government from the earliest stage of curiosity through to incorporation in actual state planning methods is charted. Potential applications of LANDSAT data to realmore » information needs and solutions to management problems are examined. The problems and mistakes that occurred in using LANDSAT data in the past are discussed as well as the ways by which these problems were overcome.« less