Hostname: page-component-cd9895bd7-q99xh Total loading time: 0 Render date: 2024-12-29T14:01:44.307Z Has data issue: false hasContentIssue false
  • English
  • Français

Performance Assessments of Geologic Repositories for High-Level Nuclear Waste: Are They Necessary or Sufficient?

Published online by Cambridge University Press:  17 March 2011

Rodney C. Ewing
Rodney C. Ewing*
Affiliation:
Department of Geological Sciences and Department of Nuclear Engineering & Radiological Sciences, University of Michigan, Ann Arbor, MI 48109-1063, USA.
Get access

Abstract

Performance assessments of geologic repositories for high-level nuclear waste will be used to determine regulatory compliance. The determination, that with a “reasonable expectation” regulatory limits are met, is based on the presumption that all of the relevant physical, chemical and biological processes have been modeled with enough accuracy to insure that a confident judgment of safety may be made. For the geologic disposal of high-level nuclear waste, this generally means that models must be capable of calculating radiation exposures to a specified population at distances of tens of kilometers for periods of tens to hundreds of thousands of years. A total system performance assessment will consist of a series of cascading models that are meant in toto to capture repository performance. There are numerous sources of uncertainty in these models: scenario uncertainty, conceptual model uncertainty and data uncertainty. These uncertainties will propagate through the analysis, and the uncertainty in the total system analysis must necessarily increase with time. For the highly-coupled, non-linear systems that are characteristic of many of the physical and chemical processes, one may anticipate emergent properties that cannot, in fact, be predicted. For all of these reasons, a performance assessment is not in and of itself a sufficient basis for determining the safety of a repository, but it remains a necessary part of the effort to develop a substantive understanding of a repository site.

Type
Research Article
Information
MRS Online Proceedings Library (OPL) , Volume 824: Symposium CC – Scientific Basis for Nuclear Waste Management XXVIII , 2004 , CC3.2
Copyright
Copyright © Materials Research Society 2004

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Glimcher, P.W. Decisions, Uncertainty, and the Brain – The Science of Neuroeconomics (MIT Press, 2003) 375.Google Scholar
2. Ottino, J.M. Nature, 427, 399 (2004).Google Scholar
3. Cipra, B. Science, 287, 960 (2000).Google Scholar
4. Ewing, R.C., Tierney, M.S., Konikow, L.F., and Rechard, R.P., Risk Analysis, 19, 933 (1999).Google Scholar
5. Hoffmann-Riem, H. and Wynne, B. Nature, 416, 123 (2002).Google Scholar
6. Ewing, R.C., Palenik, C.S. and Konikow, L.F., Risk Analysis, (in press).Google Scholar
7. Rechard, R.P. Risk Analysis, 19, 763 (1999).Google Scholar
8. Rasmussen, N.C. Reactor Safety Study: An Assessment of Accident Risk in U.S. Commercial Nuclear Power Plants, NUREG-75/014, WASH-1400 (U.S. Nuclear Regulatory Commission, Washington D.C., 1975).Google Scholar
9. Hebel, L.C., Christensen, E.L., Donath, F.A., Falconer, W.E., Lidofsky, L.J., Moniz, E.J., Moss, T.H., Pigford, R.L., Pigford, T.H., Rochlin, G.I., Silsbee, R.H., Wrenn, M.E. Reviews in Modern Physics, 50, S1 (1978).Google Scholar
10.National Research Council, Disposition of High-Level Waste and Spent Nuclear Fuel (National Academy Press, 2001) 198.Google Scholar
11. Garrick, B.J. and Kaplan, S. Radioactive and Mixed Waste – Risk as a Basis for Waste Classification (NCRP Symposium, Proceedings No. 2 (National Council on Radiation Protection and Measurements, Bethesda, Maryland) 59–73.Google Scholar
12. Bredehoeft, J.D., England, A.W., Stewart, D.B., Trask, N.J., Winograd, I.J. Geologic Disposal of High-Level Radioactive Wastes – Earth-Science Perspectives (Geological Survey Circular 779, 1978) 15.Google Scholar
13. Palenik, C.S., Jensen, K, Ewing, R.C. MRS Proceedings, this volume.Google Scholar
14. Oreskes, N., Shrader-Frechette, K., Belitz, K. Science, 263, 641 (1994).Google Scholar
15. Oreskes, N. and Belitz, K. Philosophical Issues in Model Assessment in Model Validation: Perspectives in Hydrological Science (John Wiley and Sons, Ltd., 2001) 23–41.Google Scholar
16. Konikow, L.F. Ground Water, 24, 173 (1986).Google Scholar
17. Konikow, L.F. Ground Water, 30, 622 (1992).Google Scholar
18. Konikow, L.F. and Bredehoeft, J.D., Advances in Water Resources, 15, 75 (1992).Google Scholar
19. de Marsily, G., Combes, P. and Goblet, P. Advances in Water Resources, 15, 367 (1992).Google Scholar
20. Bredehoeft, J.D. and Konikow, L.F. Advances in Water Resources, 15, 371 (1992).Google Scholar
21. Konikow, L.F. and Ewing, R.C., 37, 481 (1999).Google Scholar
22. Konikow, L.F. The Value of postaudits in Groundwater Model Applications in Groundwater Models for Resources Analysis and Management (Lewis Publishers, 1995) 59–78.Google Scholar
23. Bredehoeft, J.D., Ground Water, 41, 571 (2003).Google Scholar
24. Bethke, C.M., Geochimica et Cosmochimica Acta, 56, 4315 (1992).Google Scholar
25. Wang, T., Bryan, C. Xu, H., and Gao, H. Geology, 31, 387 (2003).Google Scholar
26. Duro, L., Bruno, J., , J., Jordana, S., Grive, M., Pon, J., Castilier, E., Beaucaire, C., Faure, M.H., Peña, J., Gimeno, M.J., del Nero, M., Ayora, C., Salas, J., Ledoux, E. and Made, B. “Blind Prediction Modeling (BPM) exercises in Oklo,” Oklo working group Proceedings of the third and final EC-CEA workshop on Oklo – Phase II, held in Cadarache, France, ed. Louvat, D., Michaud, V., and Maravic, H. von (Nuclear Science and Technology Report EUR 19137 EN, 2000), 285.Google Scholar
27. Madé, B., Ledoux, E., Ayora, C., and Salas, J., “Coupled chemical transport modeling of uranium around the reaction zone at Bangombé (Oklo, Gabon),” Oklo working group Proceedings of the third and final EC-CEA workshop on Oklo – Phase II, held in Cadarache, France, ed. Louvat, D., Michaud, V., and Maravic, H. von (Nuclear Science and Technology Report EUR 19137 EN, 2000), 307.Google Scholar
28. Jensen, K.A., Palenik, C.S. and Ewing, R.C. Radiochimica Acta, 90, 761 (2002).Google Scholar
29. Browning, L., Murphy, W.M., Manepally, C. and Fedors, R. Computers & Geosciences, 29, 247 (2003).Google Scholar
30. Hughson, D.L., Browning, L., Murphy, W.M. and Green, R.T. Mater. Res. Soc. Proc., 608, 557 (2000).Google Scholar
31. Herrick, C. and Sarewitz, D. Science, Technology & Human Values, 25, 309 (2000).Google Scholar
32. Tal, A. Environmental Science & Technology, 31, 470 (1997).Google Scholar
33. Andersson, J. and Grundteknik, G. Data and Data Uncertainties, SKB Technical Rept. TR-99-09, (1999) 138.Google Scholar
34. Apostolakis, G.A. Risk Analysis, 24, 515 (2004).Google Scholar
35. Mohanty, S. and Codell, R.B. Risk Analysis, 24, 537 (2004).Google Scholar