The method of belief scales as a means for dealing with uncertainty in tough regulatory decisions.

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Modeling and simulation is playing an increasing role in supporting tough regulatory decisions, which are typically characterized by variabilities and uncertainties in the scenarios, input conditions, failure criteria, model parameters, and even model form. Variability exists when there is a statistically significant database that is fully relevant to the application. Uncertainty, on the other hand, is characterized by some degree of ignorance. A simple algebraic problem was used to illustrate how various risk methodologies address variability and uncertainty in a regulatory context. These traditional risk methodologies include probabilistic methods (including frequensic and Bayesian perspectives) and second-order methods where variabilities and ... continued below

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86 p.

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Pilch, Martin M. October 1, 2005.

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Description

Modeling and simulation is playing an increasing role in supporting tough regulatory decisions, which are typically characterized by variabilities and uncertainties in the scenarios, input conditions, failure criteria, model parameters, and even model form. Variability exists when there is a statistically significant database that is fully relevant to the application. Uncertainty, on the other hand, is characterized by some degree of ignorance. A simple algebraic problem was used to illustrate how various risk methodologies address variability and uncertainty in a regulatory context. These traditional risk methodologies include probabilistic methods (including frequensic and Bayesian perspectives) and second-order methods where variabilities and uncertainties are treated separately. Representing uncertainties with (subjective) probability distributions and using probabilistic methods to propagate subjective distributions can lead to results that are not logically consistent with available knowledge and that may not be conservative. The Method of Belief Scales (MBS) is developed as a means to logically aggregate uncertain input information and to propagate that information through the model to a set of results that are scrutable, easily interpretable by the nonexpert, and logically consistent with the available input information. The MBS, particularly in conjunction with sensitivity analyses, has the potential to be more computationally efficient than other risk methodologies. The regulatory language must be tailored to the specific risk methodology if ambiguity and conflict are to be avoided.

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86 p.

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  • Report No.: SAND2005-4777
  • Grant Number: AC04-94AL85000
  • DOI: 10.2172/875624 | External Link
  • Office of Scientific & Technical Information Report Number: 875624
  • Archival Resource Key: ark:/67531/metadc881140

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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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  • October 1, 2005

Added to The UNT Digital Library

  • Sept. 21, 2016, 2:29 a.m.

Description Last Updated

  • Nov. 29, 2016, 8:03 p.m.

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Pilch, Martin M. The method of belief scales as a means for dealing with uncertainty in tough regulatory decisions., report, October 1, 2005; United States. (digital.library.unt.edu/ark:/67531/metadc881140/: accessed September 21, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.