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Modeling Uncertainty: Realism vs Conservatism in Radiological Performance Assessment

Modeling Uncertainty: Realism vs Conservatism in Radiological Performance Assessment. John Tauxe, PhD, PE Paul K. Black, PhD Bruce M. Crowe, PhD Donald W. Lee, PhD, PE. Neptune and Company, Inc. http://www.neptuneandco.com/~jtauxe/ngwa03. Presentation Outline.

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Modeling Uncertainty: Realism vs Conservatism in Radiological Performance Assessment

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  1. Modeling Uncertainty: Realism vs Conservatism in Radiological Performance Assessment John Tauxe, PhD, PE Paul K. Black, PhD Bruce M. Crowe, PhD Donald W. Lee, PhD, PE Neptune and Company, Inc. http://www.neptuneandco.com/~jtauxe/ngwa03

  2. Presentation Outline • What is Performance Assessment? • Probabilistic PA modeling • A Low-Level Radioactive Waste example • Advantages of probabilistic modeling • Modeling and uncertainty

  3. Quote of the Day “Reports that say that something hasn't happened are always interesting to me, because as we know, there are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns – the ones we don't know we don't know.” Secretary of Defense Donald H. Rumsfeld DoD News Briefing – 12 Feb 2002 Source: http://www.defenselink.mil/news/Feb2002/t02122002_t212sdv2.html

  4. 435.1 PA DAS Performance Assessment • For the DOE and its LLW sites, PAs are intended to establish “reasonable expectation” that performance objectives are not exceeded (e.g. DOE M 435.1), in order to authorize waste disposal. • PAs are traditionally deterministic and conservative, yet any such analysis has inherent uncertainties in assumptions, parameter values, and in the models themselves.

  5. Determinisitic vs Probabilistic

  6. ? ? PAs and Uncertainty ? Sources of uncertainty in PA modeling include • conceptual model assumptions and exposure scenarios, • analytical and numerical models and their assumptions, and • model input parameters in space and time (variability and knowledge uncertainty). ? ? ? ? ? ? ?

  7. Deterministic Modeling Deterministic models • produce deterministic (single-valued) output with no uncertainty, • are easy to compare to deterministic performance objectives, • typically strive for conservatism*, and • may be a good choice for simple demonstration of compliance. * What is conservative may not always be obvious, and conservatism can obscure model complexities.

  8. Probabilistic Modeling Probabilistic models • strive to be realistic (not conservative), • represent uncertainty using probability density functions for model parameters, • propagate uncertainty through Monte Carlo simulation, and • calculate model outputs as probability density functions.

  9. An Example from the Nevada Test Site Area 5 Radioactive Waste Management Site • Photo courtesy NNSA/NSO

  10. The Area 5 RWMS The conceptual model of transport at the Area 5 Radioactive Waste Management Site at the Nevada Test Site includes: • upward flux of water driven by high evapotranspiration potentials, • diffusion in liquid and gaseous phases, • biotic transport of contamination and materials in the near surface, and • resuspension by wind. Processes are nonlinear and tightly coupled, so what makes for a conservative estimate?

  11. ground surface no-flux boundary 1. advection of water • down to distant water table • up to “no-flux boundary” cap 2. diffusion in water below “no-flux boundary” (NFB) advection in water diffusion in water diffusion in air waste 3. diffusion in air phase throughout unsaturated zone flow divide alluvium to groundwater Advective/Diffusive Transport Modeled processes: What is conservative?

  12. 1. Plant roots uptake contaminants during growth. cap 2. Contaminants are redistributed within the plants. 3. Contaminants are returned to soil upon senescence. waste Plant-Induced Transport Modeled processes: Again: What is conservative?

  13. 1. Animals excavate subsurface bulk materials and bring them to the surface. excavation cap 2. Burrows collapse, returning materials to the subsurface. collapse waste Animal-Induced Transport Modeled processes: Yet again: What is conservative?

  14. GoldSim at the NTS

  15. An example: These bulk density data need to be turned in to an input distribution. Stochastic Parameters • Inventory • Dimensions • Material properties • Biotic properties and rates of activities • Human behavior • Chemical properties

  16. Monte Carlo Simulation • Select time stepping • Select number of realizations • Select seed • Optional use of LHS

  17. 1 . 0 0 x 1 0 0 2 1 . 0 0 x 1 0 0 1 performance objective 1 . 0 0 x 1 0 0 0 1 . 0 0 x 1 0 - 0 1 1 . 0 0 x 1 0 - 0 2 1 . 0 0 x 1 0 - 0 3 1 . 0 0 x 1 0 - 0 4 0 100 200 300 400 500 600 700 800 900 1000 time (yr) Deterministic Results Comparison is easy, but is it honest?

  18. performance objective 0 100 200 300 400 500 600 700 800 900 1000 time (yr) Probabilistic Results Comparison is challenging, but more honest.

  19. 1 . 0 0 x 1 0 0 2 upper bound 1 . 0 0 x 1 0 0 1 performance objective 95% mean 1 . 0 0 x 1 0 0 0 median 75% 1 . 0 0 x 1 0 - 0 1 25% 1 . 0 0 x 1 0 - 0 2 5% lower bound 1 . 0 0 x 1 0 - 0 3 1 . 0 0 x 1 0 - 0 4 0 100 200 300 400 500 600 700 800 900 1000 time (yr) Statistical Summaries

  20. Advantages of Probabilistic Analysis • More realistic (honest) answers • More information for decision makers (not doing their job for them) • Provides information for statistical comparisons with monitoring data and for value of information analysis (when to stop monitoring) • Identification of sensitive parameters

  21. Sensitivity Analysis 1 Sensitivity analysis provides a ranking of sensitive parameters, enhancing appreciation for their significance. For example, dose may be driven by: 1. Cap thickness 2. Volume of materials excavated by ants 3. Inventory of 238U 4. Plant/soil concentration ratio for 99Tc

  22. Sensitivity Analysis 2 Using the MART* statistical technique, the range over which a parameter is sensitive can be evaluated. Sensitivity Index That’s cool! *Multiple Additive Regression Trees Cap Thickness (m)

  23. Value of Information Analysis • Evaluate VOI from monitoring activities. • Determine value of continued monitoring (this cannot be done with a deterministic model). • Decide when monitoring no longer provides useful information (time to stop).

  24. Take Home Points • Environmental modeling is most useful if done stochastically. • Confirmation of performance assessment (through monitoring) requires statistical analysis. • Probabilistic modeling provides a technical basis for deciding when to stop monitoring. http://www.neptuneandco.com/~jtauxe/ngwa03

  25. Yucca Flat, Nevada: The world’s best radioactive waste disposal site. The holes have already been “dug”!

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