Extensive work has been carried out by the U.S. Department of Energy (DOE) in the development of a proposed geologic repository at Yucca Mountain (YM), Nevada, for the disposal of high-level radioactive waste. In support of this development and an associated license application to the U.S. Nuclear Regulatory Commission (NRC), the DOE completed an extensive performance assessment (PA) for the proposed YM repository in 2008. This presentation describes uncertainty and sensitivity analysis results for the igneous intrusive scenario class and the igneous eruptive scenario class obtained in the 2008 YM PA. The following topics are addressed for the igneous intrusive scenario class: (i) engineered barrier system conditions, (ii) release results for the engineered barrier system, unsaturated zone, and saturated zone, (iii) dose to the reasonably maximally exposed individual (RMEI) specified in the NRC regulations for the YM repository, and (iv) expected dose to the RMEI. In addition, expected dose to the RMEI for the igneous eruptive scenario class is also considered. The present article is part of a special issue of Reliability Engineering and System Safety devoted to the 2008 YM PA; additional articles in the issue describe other aspects of the 2008 YM PA.
Uncertainty and sensitivity analysis are fundamental components of the 2008 performance assessment (PA) conducted by the U.S. Department of Energy (DOE) for the proposed high-level radioactive waste (HLW) repository at Yucca Mountain (YM), Nevada [1] and [2]. The following presentation describes uncertainty and sensitivity analysis results obtained for the igneous scenario classes [3] in the 2008 YM PA. Additional presentations describe uncertainty and sensitivity analysis results obtained in the 2008 YM PA for the nominal scenario class [4] and [5], early failure scenario classes [6] and [7], seismic scenario classes [8] and [9], and all scenario classes collectively [10].
The uncertainty and sensitivity techniques in use are described in Section 2 of Ref. [5] and involve the use of Latin hypercube sampling, partial rank correlation coefficients (PRCCs) and stepwise rank regression. The presented uncertainty and sensitivity analysis results are obtained with the first of the three replicated Latin hypercube samples (LHSs) described in Sections 11 and 12 of Ref. [2]. This is the same LHS used in the generation of the expected dose results for the igneous scenario classes [3] and also in the generation of results for the other scenario classes under consideration [4], [5], [6], [7], [8] and [9]. Descriptions of the epistemically uncertain analysis inputs under consideration and references to additional sources of information on these variables are given in Appendix B of Ref. [2]. Further, additional information on the uncertainty and sensitivity techniques in use is available in several reviews [11], [12], [13] and [14].
The following topics are considered in this presentation for the igneous intrusive scenario class: engineered barrier system (EBS) conditions (Section 2), release from the EBS (Section 3), release from the unsaturated zone (UZ) (Section 4), release from the saturated zone (SZ) (Section 5), dose to the reasonably maximally exposed individual (RMEI) (Section 6), and expected dose to the RMEI (Section 7). The movement of three radionuclides (239Pu, 237Np and 99Tc) is described. These radionuclides are broadly representative of the range of radionuclide solubilities, sorption properties and interaction with colloids for all radionuclides considered in the 2008 YM PA; thus, examining results for these three radionuclides provides insights into transport processes. In addition, expected dose to the RMEI for the igneous eruptive scenario class is also considered (Section 8). The presentation then ends with a summary discussion (Section 9).
The primary focus of this presentation is on uncertainty and sensitivity analysis results obtained for the igneous intrusive and igneous eruptive scenario classes. Summary descriptions of the models that underlie these results are given in Ref. [15] and in Section 6 of Ref. [1], and more detailed descriptions are available in the reports cited in Refs. [1] and [15] and in Appendix B of Ref. [2]. Further, an extensive description of the development process that led to these models is given in Refs. [16], [17], [18], [19], [20], [21], [22], [23], [24] and [25].
