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Development of groundwater flow and transport models for repository performance assessments

Development of groundwater flow and transport models for repository performance assessments. Bruce A. Robinson Los Alamos National Laboratory. Topics of Discussion. Flow and transport modeling methods (Yucca Mountain example) Single and multiphase fluid flow Radionuclide transport

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Development of groundwater flow and transport models for repository performance assessments

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  1. Development of groundwater flow and transport models for repository performance assessments Bruce A. Robinson Los Alamos National Laboratory

  2. Topics of Discussion • Flow and transport modeling methods (Yucca Mountain example) • Single and multiphase fluid flow • Radionuclide transport • Computational issues for transport • Uncertainty quantification (Nevada Test Site Underground Test Area example – courtesy of Andrew Wolfsberg) • Model development and structural uncertainty • Geochemistry as a constraint on model development • Parameter and conceptual uncertainty

  3. FEHM – Finite Element Heat and Mass Uses on Yucca Mountain Project • Unsaturated Zone: simulation of radionuclide migration from the repository to the water table • Saturated Zone • Flow model calibrated with head data and flux information • Transport model to simulate radionuclide migration from the water table beneath the repository to the compliance boundary

  4. FEHM – Finite Element Heat and Mass Uses on other Similar Projects • Nevada Test Site Underground Test Area Project • Unsaturated and saturated zone flow models • Radionuclide transport prediction and uncertainty quantification • Los Alamos National Laboratory groundwater program • Proposed Romanian LIL Waste Site • Flow model development and calibration • Radionuclide transport

  5. Yucca Mountain Saturated Zone Model • Flow model construction • Hydrogeologic framework model (HFM) • Grid generation • Parameter ranges (prior values, updated using calibration) • Calibration (FEHM plus PEST software) • Confidence building using other data sets • Transport model simulations

  6. Head contours and model fit

  7. Particle pathways • Computed using particle tracking algorithm • Pathways are a function of uncertain hydrologic parameters

  8. Confidence building: Comparison of model paths and paths inferred by geochemistry data

  9. Saturated zone radionuclide transport

  10. Neptunium Monte Carlo transport results • Calculations shown are for illustrative purposes only – see Yucca Mountain License Application for final results • Flow and transport parameters sampled randomly from uncertainty distributions • Breakthrough curves generated using FEHM particle tracking model – represent mass flux crossing compliance boundary • These breakthrough curves are input to the Yucca Mountain Total System Performance Assessment model

  11. Nevada Test Site Underground Test Area • Environmental management program to investigate the transport of radionuclides in groundwater as a result of underground nuclear testing at the NTS • In situ radionuclide concentration contours must be predicted, not simply mass flux crossing a compliance boundary • Example is used here to illustrate uncertainty quantification issues • Model development • Geochemistry as a constraint on model development • Parameter and conceptual uncertainty

  12. The Nevada Test Site (NTS) Rainier Mesa Pahute Mesa Yucca Flat Pahute Mesa Corrective Action Unit (CAU) Model Domain Frenchman Flat NTS

  13. Black Mountain Caldera Pahute Mesa Timber Mountain Oasis Valley The Pahute Mesa Model Domain • 50 x 50 km • Substantial elevation changes • Rough topography

  14. Pahute Mesa Black Mountain Thirsty Canyon Timber Mountain 40 Mile Canyon Oasis Valley Sparse Data is a Universal Issue Two models of the buried Silent Canyon Caldera below Pahute Mesa. Different conceptual models of the geometry of the caldera structure, faults, and stratigraphy. We have 7 different HFMs

  15. Stratigraphic Framework Model Uncertainty Two Alternative conceptualizations of the structural framework model below Pahute Mesa We have 7 different HFMs

  16. Uncertainty Quantification – A Practical Question Which is more important to consider? • Conceptual model uncertainty • Parametric uncertainty cumulative alternative conceptual models p

  17. Flow Model Uncertainty Quantification • 21 steady-state FEHM flow models calibrated with PEST • 7 alternative hydrostratigraphic framework models (HFMs) • 3 alternative recharge models • Flow models were ranked for goodness of fit against independent geochemical mixing simulations (Wolfsberg et al., 2006)

  18. NW East Recharge Geochemical analysis using reverse particle tracking Exit locations at top of model for particles released at well ER-OV-3c 1 Million particles released at each well Exit locations compared with geochemical source locations Geochemical residuals identified NE NC

  19. Transport Model Uncertainty Quantification • Transport model considers • 35 transient, spatially distributed sources • 12 species: conservative, sorbing, and colloidal • Uncertain transport parameters in heterogeneous materials • Fracture properties: aperture, spacing, fracture porosity • Matrix diffusion coefficient • Matrix porosity • Sorption Kds of reactive species • Mobile fraction of aqueous plutonium available for colloid-facilitated transport • Colloid mobility • Convolution-integral solution for transport on steady-state flow fields (transient source release) (Robinson and Dash, 2007) • Results presented as locations where concentrations exceed the standards within 1000 years for greater than 5% of realizations

  20. Calculating in situ concentrations • Computer code PLUMECALC provides a means for computing resident or flux-averaged concentrations from particle tracking information and source term • Particle tracking (FEHM) : advection, dispersion • Source term: radionuclide mass flux vs. time • PLUMECALC: computes in situ concentrations in the presence of sorption and matrix diffusion

  21. Type I model Type II model Type III model Contaminant predictions are affected by flow model conceptual uncertainty Time at which 5% of realizations exceed standard

  22. Monte Carlo Null Space Analysis • Permits definition of insensitivity range per parameter (permeability) • Generation of multiple, equiprobable calibrated models, each re-parameterized • Method: • Assume selected calibrated model parameters are expected values • Add insensitive component of a random perturbation to each calibrated value, for any number of realizations For example:

  23. Monte Carlo Null Space Results • Results above are for identical transport parameters (only flow parameters are varied) • Conclusion: Significant uncertainty due to flow parameters exists even within a given hydrogeologic conceptual model

  24. Conclusions • Confidence in natural system model results are obtained through a synthesis of available information and robust uncertainty quantification • Computational tools exist for: • Flow and transport model calibration • Radionuclide transport prediction • Uncertainty quantification • Conceptual model uncertainty is important to consider • Predictive uncertainty within the constraints provided by the calibrated model must also be quantified

  25. Backup Slides

  26. Particle tracking method - advection • Trajectory and travel times of particles are computed within a cell by velocity interpolation (Pollack, 1988). • Dispersion is modeled with a random-walk algorithm (Tompson and Gelhar, 1993). • Matrix diffusion and sorption are modeled using a transfer function approach. Computational Cell and Particle Pathway Q2 Q1

  27. Particle tracking method – sorption and diffusion Transfer Function Approach • Transfer function corresponds to a distribution of residence times that reproduces an analytical solution • Travel time through each cell is computed based on the transport properties in that cell • Similar approach is used in the unsaturated zone Determination of Particle Travel Time

  28. Particle tracking method –diffusion submodel Parallel Fracture Model Dimensionless Groups 2b 2B Parameters: - q (specific discharge) - fm(matrix porosity) - ff(fracture porosity) - B (fracture spacing) - D (diffusion coefficient) - Rf (retardation factor) Solution: Sudicky and Frind (1982)

  29. PLUMECALC TheoryConvolution-Based Particle Tracking (CBPT) • Superposition principle is applied: Mass density function Concentration information in the integral is obtained from the composite behavior of particles passing through a computational grid cell

  30. PLUMECALC demonstration

  31. Cernavoda Danube NPP disposal area lock dam Saligny village canal Romanian concept on LIL waste disposal Digitized map of the topography and the main features of the Saligny site

  32. Romanian concept on LIL waste disposal LIL wastenearsurface repository selected site : Saligny disposal cell cementitious waste-form Saligny site

  33. Saturated zone 3-D stratigraphic model of Saligny site Unsaturated zone Flow models developed, followed by radionuclide transport calculations

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