Automated Damage Onset Analysis Techniques Applied to KDP Damage and the Zeus Small Area Damage Test Facility

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Automated damage testing of KDP using LLNL's Zeus automated damage test system has allowed the statistics of KDP bulk damage to be investigated. Samples are now characterized by the cumulative damage probability curve, or S-curve, that is generated from hundreds of individual test sites per sample. A HeNe laser/PMT scatter diagnostic is used to determine the onset of damage at each test site. The nature of KDP bulk damage is such that each scatter signal may possess many different indicators of a damage event. Because of this, the determination of the initial onset for each scatter trace is not a ... continued below

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7,800 Kilobytes pages

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Sharp, R. & Runkel, M. December 16, 1999.

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Automated damage testing of KDP using LLNL's Zeus automated damage test system has allowed the statistics of KDP bulk damage to be investigated. Samples are now characterized by the cumulative damage probability curve, or S-curve, that is generated from hundreds of individual test sites per sample. A HeNe laser/PMT scatter diagnostic is used to determine the onset of damage at each test site. The nature of KDP bulk damage is such that each scatter signal may possess many different indicators of a damage event. Because of this, the determination of the initial onset for each scatter trace is not a straightforward affair and has required considerable manual analysis. The amount of testing required by crystal development for the National Ignition Facility (NIF) has made it impractical to continue analysis by hand. Because of this, we have developed and implemented algorithms for analyzing the scatter traces by computer. We discuss the signal cleaning algorithms and damage determination criteria that have lead to the successful implementation of a LabView based analysis code. For the typical R/1 damage data set, the program can find the correct damage onset in more than 80% of the cases, with the remaining 20% being left to operator determination. The potential time savings for data analysis is on the order of {approx} 100X over manual analysis and is expected to result in the savings of at least 400 man-hours over the next 3 years of NIF quality assurance testing.

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7,800 Kilobytes pages

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  • 31st Boulder Damage Symposium: Annual Symposium on Optical Materials for High Power Lasers, Boulder, CO (US), 10/04/1999--10/07/1999

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  • Report No.: UCRL-JC-134765
  • Grant Number: W-7405-Eng-48
  • Office of Scientific & Technical Information Report Number: 791053
  • Archival Resource Key: ark:/67531/metadc717488

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  • December 16, 1999

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  • Sept. 29, 2015, 5:31 a.m.

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  • May 6, 2016, 2:15 p.m.

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Sharp, R. & Runkel, M. Automated Damage Onset Analysis Techniques Applied to KDP Damage and the Zeus Small Area Damage Test Facility, article, December 16, 1999; California. (digital.library.unt.edu/ark:/67531/metadc717488/: accessed August 18, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.