A formalism to generate probability distributions for performance-assessment modeling
A formalism is presented for generating probability distributions of parameters used in performance-assessment modeling. The formalism is used when data are either sparse or nonexistent. The appropriate distribution is a function of the known or estimated constraints and is chosen to maximize a quantity known as Shannon`s informational entropy. The formalism is applied to a parameter used in performance-assessment modeling. The functional form of the model that defines the parameter, data from the actual field site, and natural analog data are analyzed to estimate the constraints. A beta probability distribution of the example parameter is generated after finding four constraints. As an example of how the formalism is applied to the site characterization studies of Yucca Mountain, the distribution is generated for an input parameter in a performance-assessment model currently used to estimate compliance with disposal of high-level radioactive waste in geologic repositories, 10 CFR 60.113(a)(2), commonly known as the ground water travel time criterion. 8 refs., 2 figs.
- Research Organization:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- DOE Contract Number:
- AC04-76DP00789
- OSTI ID:
- 137980
- Report Number(s):
- SAND-90-2221C; CONF-910435-28; ON: DE91005968; TRN: 91:004781
- Resource Relation:
- Conference: 2. annual American Nuclear Society (ANS) international high level radioactive waste management conference, Las Vegas, NV (United States), 28 Apr - 3 May 1991; Other Information: PBD: [1990]
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
54 ENVIRONMENTAL SCIENCES
HIGH-LEVEL RADIOACTIVE WASTES
RADIONUCLIDE MIGRATION
RADIOACTIVE WASTE DISPOSAL
YUCCA MOUNTAIN
SITE CHARACTERIZATION
MONTE CARLO METHOD
PERFORMANCE
MATHEMATICAL MODELS
ENTROPY
COMPUTERIZED SIMULATION
PROBABILITY
US DOE
SATURATION
STRATIGRAPHY
POROSITY
ROCKS
SAMPLING
INSPECTION
TUFF
SOILS
US NRC
REGULATIONS
SANDIA LABORATORIES
Yucca Mountain Project