Detecting errors and anomalies in computerized materials control and accountability databases

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The Automated MC and A Database Assessment project is aimed at improving anomaly and error detection in materials control and accountability (MC and A) databases and increasing confidence in the data that they contain. Anomalous data resulting in poor categorization of nuclear material inventories greatly reduces the value of the database information to users. Therefore it is essential that MC and A data be assessed periodically for anomalies or errors. Anomaly detection can identify errors in databases and thus provide assurance of the integrity of data. An expert system has been developed at Los Alamos National Laboratory that examines these ... continued below

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6 p.

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Whiteson, R.; Hench, K.; Yarbro, T. & Baumgart, C. December 31, 1998.

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Description

The Automated MC and A Database Assessment project is aimed at improving anomaly and error detection in materials control and accountability (MC and A) databases and increasing confidence in the data that they contain. Anomalous data resulting in poor categorization of nuclear material inventories greatly reduces the value of the database information to users. Therefore it is essential that MC and A data be assessed periodically for anomalies or errors. Anomaly detection can identify errors in databases and thus provide assurance of the integrity of data. An expert system has been developed at Los Alamos National Laboratory that examines these large databases for anomalous or erroneous data. For several years, MC and A subject matter experts at Los Alamos have been using this automated system to examine the large amounts of accountability data that the Los Alamos Plutonium Facility generates. These data are collected and managed by the Material Accountability and Safeguards System, a near-real-time computerized nuclear material accountability and safeguards system. This year they have expanded the user base, customizing the anomaly detector for the varying requirements of different groups of users. This paper describes the progress in customizing the expert systems to the needs of the users of the data and reports on their results.

Physical Description

6 p.

Notes

INIS; OSTI as DE99001824

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  • 39. Institute of Nuclear Materials Management (INMM) annual meeting, Naples, FL (United States), 26-30 Jul 1998

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  • Other: DE99001824
  • Report No.: LA-UR--98-3031
  • Report No.: CONF-980733--
  • Grant Number: W-7405-ENG-36;AC04-76DP00613
  • Office of Scientific & Technical Information Report Number: 314141
  • Archival Resource Key: ark:/67531/metadc675623

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

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  • December 31, 1998

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  • July 25, 2015, 2:20 a.m.

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  • July 28, 2016, 7:31 p.m.

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Whiteson, R.; Hench, K.; Yarbro, T. & Baumgart, C. Detecting errors and anomalies in computerized materials control and accountability databases, article, December 31, 1998; New Mexico. (digital.library.unt.edu/ark:/67531/metadc675623/: accessed October 21, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.