A Stochastic Model of Radionuclide Migration from Natural and Engineered Repositories

  • Anne S. Kiremidjian
  • Paul Kruger
Part of the Advances in Nuclear Science & Technology book series (ANST)


A stochastic model is being developed to analyze available migration data from existing radionuclide repositories, as a tool for assessing the adequacy of geologic formations as long term repositories of high level nuclear wastes. Since factual data on long term disposal of commercial nuclear wastes do not exist, the data needed for licensing and regulatory decisions on nuclear waste management must come from controlled laboratory and field experiments and from indirect sources. Much information is already available from the former. For example, considerable efforts are underway in the DOE-sponsored program to develop methods for forecasting radionuclide migration. Two major programs are the general models being developed at Sandia Laboratories (1) and at Battelle Pacific Northwest Laboratories (2). The Sandia program is a mathematical model to estimate the long term stability of engineered repositories, while the PNL model is focused on repository performance assessment (acronymed WIPAP). The Sandia program uses analytical approaches to estimate the geologic stability based on probabilistic models and numerical simulation, and are being applied to idealized waste repositories. The PNL program is divided into two parts, 1) release scenarios and 2) consequence analysis, the release scenarios are analyzed by a number of techniques, such as lumped-parameters simulation simulation, Monte Carlo simulation, and fault/event tree analyses. Stottlemeyre et al.(3) described a simplified one-dimensional model to simulate the system response to potential disruptive phenomena over time. The model is being developed to expand its capability. Although it now operates in a deterministic manner, based on user selected scenarios, it is planned to develop the model for stochastic operation. The consequence analysis involves deterministic modeling of the processes transporting the release radionuclides through dose commitment.


Nuclear Waste Migration Data Migration Characteristic Fault Tree Analysis Underground Nuclear Explosion 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 1980

Authors and Affiliations

  • Anne S. Kiremidjian
    • 1
  • Paul Kruger
    • 1
  1. 1.Civil Engineering Dept.Stanford UniversityStanfordUSA

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