Uncertainty and sampling issues in tank characterization

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Description

A defensible characterization strategy must recognize that uncertainties are inherent in any measurement or estimate of interest and must employ statistical methods for quantifying and managing those uncertainties. Estimates of risk and therefore key decisions must incorporate knowledge about uncertainty. This report focuses statistical methods that should be employed to ensure confident decision making and appropriate management of uncertainty. Sampling is a major source of uncertainty that deserves special consideration in the tank characterization strategy. The question of whether sampling will ever provide the reliable information needed to resolve safety issues is explored. The issue of sample representativeness must be ... continued below

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54 p.

Creation Information

Liebetrau, A.M.; Pulsipher, B.A. & Kashporenko, D.M. June 1, 1997.

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  • Pacific Northwest Laboratory
    Publisher Info: Pacific Northwest Lab., Richland, WA (United States)
    Place of Publication: Richland, Washington

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Description

A defensible characterization strategy must recognize that uncertainties are inherent in any measurement or estimate of interest and must employ statistical methods for quantifying and managing those uncertainties. Estimates of risk and therefore key decisions must incorporate knowledge about uncertainty. This report focuses statistical methods that should be employed to ensure confident decision making and appropriate management of uncertainty. Sampling is a major source of uncertainty that deserves special consideration in the tank characterization strategy. The question of whether sampling will ever provide the reliable information needed to resolve safety issues is explored. The issue of sample representativeness must be resolved before sample information is reliable. Representativeness is a relative term but can be defined in terms of bias and precision. Currently, precision can be quantified and managed through an effective sampling and statistical analysis program. Quantifying bias is more difficult and is not being addressed under the current sampling strategies. Bias could be bounded by (1) employing new sampling methods that can obtain samples from other areas in the tanks, (2) putting in new risers on some worst case tanks and comparing the results from existing risers with new risers, or (3) sampling tanks through risers under which no disturbance or activity has previously occurred. With some bound on bias and estimates of precision, various sampling strategies could be determined and shown to be either cost-effective or infeasible.

Physical Description

54 p.

Notes

INIS; OSTI as DE97053945

Source

  • Other Information: PBD: Jun 1997

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  • Other: DE97053945
  • Report No.: PNNL--11529
  • Grant Number: AC06-76RL01830
  • DOI: 10.2172/548889 | External Link
  • Office of Scientific & Technical Information Report Number: 548889
  • Archival Resource Key: ark:/67531/metadc692079

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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.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

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  • June 1, 1997

Added to The UNT Digital Library

  • Aug. 14, 2015, 8:43 a.m.

Description Last Updated

  • June 14, 2016, 1:11 p.m.

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Liebetrau, A.M.; Pulsipher, B.A. & Kashporenko, D.M. Uncertainty and sampling issues in tank characterization, report, June 1, 1997; Richland, Washington. (digital.library.unt.edu/ark:/67531/metadc692079/: accessed April 25, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.