2004 Denver Annual Meeting (November 7–10, 2004)

Paper No. 13
Presentation Time: 4:45 PM


VAN LUIK, Abraham E. and LEVICH, Robert A., US Department of Energy, 1551 Hillshire Drive, Las Vegas, NV 89134, abe_vanluik@ymp.gov

Total System Performance Assessment (TSPA) is the use of numerical models representing natural processes to evaluate the future performance of natural and engineered components of the repository system. Future performance, in this context, means performance after the operational period and the emplacement of final seals. The basis for developing a TSPA is data collected during surface-based, underground, and laboratory tests and studies; measurements and interpretations by scientific experts; selected information from documented studies; and information related to the engineered barriers and the repository design. The numerical models are developed based on the laws and principles of chemistry and physics, where possible, augmented by empirical studies where necessary, and represent processes relevant to the system using data from field investigations and laboratory studies.

The TSPA is a key component of the License Application being submitted by the US Department of Energy (DOE) to the US Nuclear Regulatory Commission (NRC). The NRC must be able to find, on the basis of DOE’s demonstration, that there is reasonable expectation that nuclear waste can be disposed of safely for many thousands of years without posing an unacceptable risk to public health and safety. TSPA results include an evaluation of uncertainties inherent in assessing long-term repository performance.

Uncertainties are introduced by spatial and temporal variability in current and future site conditions, and the complexity of the coupled physical and chemical processes operating in a repository over time. Results from computational models are not a precise prediction of the actual performance of a repository. However, although significant uncertainties exist, there will be confidence in the safety of the system if there is a comfortable margin between pessimistically predicted results and the regulatory definitions of safety, plus additional evidence, e.g., natural or other analogues supporting the credibility of the analyses.