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Title: Repository Integration Program: RIP performance assessment and strategy evaluation model theory manual and user`s guide

Technical Report ·
DOI:https://doi.org/10.2172/210967· OSTI ID:210967

This report describes the theory and capabilities of RIP (Repository Integration Program). RIP is a powerful and flexible computational tool for carrying out probabilistic integrated total system performance assessments for geologic repositories. The primary purpose of RIP is to provide a management tool for guiding system design and site characterization. In addition, the performance assessment model (and the process of eliciting model input) can act as a mechanism for integrating the large amount of available information into a meaningful whole (in a sense, allowing one to keep the ``big picture`` and the ultimate aims of the project clearly in focus). Such an integration is useful both for project managers and project scientists. RIP is based on a `` top down`` approach to performance assessment that concentrates on the integration of the entire system, and utilizes relatively high-level descriptive models and parameters. The key point in the application of such a ``top down`` approach is that the simplified models and associated high-level parameters must incorporate an accurate representation of their uncertainty. RIP is designed in a very flexible manner such that details can be readily added to various components of the model without modifying the computer code. Uncertainty is also handled in a very flexible manner, and both parameter and model (process) uncertainty can be explicitly considered. Uncertainty is propagated through the integrated PA model using an enhanced Monte Carlo method. RIP must rely heavily on subjective assessment (expert opinion) for much of its input. The process of eliciting the high-level input parameters required for RIP is critical to its successful application. As a result, in order for any project to successfully apply a tool such as RIP, an enormous amount of communication and cooperation must exist between the data collectors, the process modelers, and the performance. assessment modelers.

Research Organization:
Golder Associates, Inc., Redmond, WA (United States)
Sponsoring Organization:
USDOE, Washington, DC (United States)
DOE Contract Number:
AC01-91RW00134
OSTI ID:
210967
Report Number(s):
DOE/RW/00134-T25; ON: DE96007839; TRN: 96:009483
Resource Relation:
Other Information: PBD: Nov 1995
Country of Publication:
United States
Language:
English