Uncertainty and sensitivity analysis in performance assessment for the Waste Isolation Pilot Plant Original Research Article

The Waste Isolation Pilot Plant (WIPP) is under development by the U.S. Department of Energy (DOE) for the geologic (deep underground) disposal of transuranic (TRU) waste. This development has been supported by a sequence of performance assessments (PAs) carried out by Sandia National Laboratories (SNL) to assess what is known about the WIPP and to provide guidance for future DOE research and development activities. Uncertainty and sensitivity analysis procedures based on Latin hypercube sampling and regression techniques play a major role in these PAs by providing an assessment of the uncertainty in important analysis outcomes and identifying the sources of this uncertainty. Performance assessments for the WIPP are conceptually and computationally interesting due to regulatory requirements to assess and display the effects of both stochastic (i.e., aleatory) and subjective (i.e., epistemic) uncertainty, where stochastic uncertainty arises from the possible disruptions that could occur over the 10000 yr regulatory period associated with the WIPP and subjective uncertainty arises from an inability to unambiguously characterize the many models and associated parameters required in a PA for the WIPP. The interplay between uncertainty analysis, sensitivity analysis, stochastic uncertainty and subjective uncertainty is discussed and illustrated in the context of a recent PA carried out by SNL to support an application by the DOE to the U.S. Environmental Protection Agency for the certification of the WIPP for the disposal of TRU waste.