1. CONCEPTUAL MODEL RESULTS AND ANALYSES RESULTS AND ANALYSES
Multiscale Thermohydrologic Model Supporting the Total System Performance Assessment for the Proposed Repository at Yucca Mountain T.A. Buscheck1, Y. Sun1, Y. Hao1, Y. Duan, S. Ezzedine2, and S.C. James3 1Lawrence Livermore National Laboratory 2 Weiss Associates 3 Sandia National Laboratories
CONCEPTUAL MODEL
RESULTS AND ANALYSES
RESULTS AND ANALYSES
MSTHM INPUTS
INTRODUCTION
Table 1. Percolation-flux cases addressed in parameter uncertainty study, consistent with the UZ flow model [5]
Low-Probability Seismic Case w/ Collapsed Drifts
The MSTHM [2,3] utilizes
Hydrostratigraphy, hydrologic properties, and percolation-flux distribution from the UZ flow model [4] with
560 unique hydrostratigraphic columns [4] across the heated repository footprint
560 unique percolation-flux histories [5] for 4 climate states (Table 1) for 4 infiltration-flux cases [6]
Unique waste-package heat-generation histories for PWR CSNF WPs, BWR CSNF WPs, and DHLW WPs [7]
Thermal properties for the repository host-rock units [8]
Percolation Flux Case
Repository-Wide-Averaged Percolation Flux
(mm/yr)
Present-Day
Monsoonal
Glacial-Transition
Post-10,000-Year
P10
4.1
7.8
12.2
15.9
P30
10.2
16.1
26.3
23.6
P50
14.6
19.5
36.2
35.2
P90
34.1
92.4
69.7
52.4
Mountain Scale
Figure 3. Heated repository footprint with distribution of host-rock units: Tptpul, Tptpmn, Tptpll, and Tptpln
Thermal-hydrologic (TH) conditions are predicted in the emplacement drifts and adjoining host rock for
m-long intervals along 108 emplacement drifts
8 different waste packages, each with unique heat-generation histories
A single repository-wide MSTHM realization consists of 3264 x 8 = 26,112 TH histories
For 7 parameter uncertainty cases (Table 2) 182,784 TH histories are generated and provided to TSPA
A parameter uncertainty study addressed key natural system parameters
Percolation flux [5], based on 10th, 30th, 50th, and 90th percentile infiltration maps [6]
Host-rock thermal conductivity for the 10th, 50th, and 90th percentile wet and dry values from reference [8]
Weighting factors are applied to percolation-flux cases, based on other analyses [5,6]
Weighting factors for host-rock thermal conductivity obtained from reference [2], based on data from reference [8]
Analyses [2] found that 7 of the 12 cases (see Table) can be used as surrogates for the remaining 5 cases; weighting factors are revised accordingly (Table 2)
MSTHM OUTPUT
Table 2. Percolation-flux cases in parameter uncertainty study with “surrogate” cases shown in red.
Engineered
Barrier System
Percolation Flux Uncertainty
Host-Rock Thermal Conductivity Uncertainty
P10
0.6191
P30
0.1568
P50
0.1645
P90
0.0596
High
(H)
0.34
P10H
0.2105a
0.2105b
0.0533a
0.0000b
0.0559a
P90H
0.0203a
0.0203b
Mean
(M)
0.37
0.2291a
0.2768b
0.0580a
0.0753b
0.0609a
0.0609b
0.0220a
0.1312b
Low
(L)
0.29
P10L
0.1795a
0.2250b
P30L
0.0455a
P50L
0.0477a
P90L
0.0173a
NOTES: P10, P30, P50, and P90 stand for 10th, 30th, 50th, and 90th percentile percolation flux. L, M, and M stand for 10th, 50th, and 90th percentile host-rock thermal conductivity. The respective “M” cases are simply called P10, P30, P50, and P90.
aDenotes weight of that case, which is the product of the percolation-flux weight and the host-rock thermal conductivity weight.
bSum of that case’s own weight, plus the weights of the cases for which that case is a surrogate.
Figure 11. Cross-sectional view of drift, showing original “intact” drift diameter and the rubble zone, which has an 11-m diameter
(This figure is excerpted from “Yucca Mountain Science and Engineering Report”)
Figure 1. Schematic of the Yucca Mountain repository
Drift/Waste-Package Scale
Figure 12. Waste-package temperature for DHLW-Long (a) and PWR CSNF (b) waste package for low and high rubble Kth cases and for the nominal (intact) case
Figure 13. Waste-package relative humidity for DHLW-Long (a) and PWR CSNF (b) waste packages for low and high rubble Kth cases and for the nominal (intact) case
Modeling thermal-hydrologic (TH) behavior at Yucca Mountain involves
Multiple scales
Mountain scale: heated repository area, structure of mountain, including unsaturated and saturated zones
Drift/waste-package scale: tens of centimeters around waste packages, drip shields, and granular invert
Coupled TH processes: multi-phase flow in porous and open systems, including evaporation, vapor transport, condensation, condensate drainage, thermal conduction, forced and natural convection, and thermal radiation
Waste inventory with a wide range of heat-generation histories
Heterogeneous distributions of natural system properties and percolation flux
The Multiscale Thermohydrologic Model (MSTHM) was developed to support the Total System
Performance Assessment (TSPA), in particular to assess
Degradation of in-drift components (e.g., waste packages) of the Engineered Barrier System
Radionuclide dissolution and release from the waste form (in waste packages) and transport in the invert
TH variables are predicted in the drifts and adjoining host rock in the repository, including
Temperature
Relative humidity
Liquid-phase saturation
Liquid-phase flux
Lateral extent of boiling zone
Low-probability seismic case with drift collapse is represented with a 11-m-diameter rubble zone
To address uncertainty in rubble thermal conductivity, low and high rubble thermal-conductivity Kth cases are included
The low Kth of the rubble (compared to Kth of the host rock) causes an increase in drip-shield and WP temperatures (Figures 12a and 13a), and greater WP-to-WP variability (Figure 14), compared to the nominal case
The temperature increase causes a reduction in WP relative humidity (Figures 12b and 13b) and in invert liquid-phase saturation
Results of the low and high rubble Kth cases are compared with corresponding nominal results to develop “delta” tables of WP temperature and relative humidity and invert liquid-phase saturation
The “deltas” are applied to TH results for the 7 nominal cases to generate TH results for the corresponding drift-collapse cases
Nominal Case with Intact Drifts
Figure 14. Complementary cumulative distribution function (CCDF) for the low and high rubble Kth cases for the 7 parameter uncertainty cases
NOTE: CCDFs for the corresponding nominal cases are plotted in Figure 6.
CONCLUSIONS:
Two key natural-system parametric uncertainties (host-rock thermal conductivity and percolation flux) are propagated through the MSTHM results supporting TSPA
The influence of the edge-cooling effect and WP-to-WP heat-generation variability are addressed in the MSTHM results
The combined influences of host-rock thermal-conductivity and percolation-flux uncertainty/variability, edge-cooling effect, and WP-to-WP heat-generation variability result in
Peak WP temperatures ranging from 100 to 220oC
Duration of boiling conditions at the drift wall ranging from 0 to 1300 yr
Low-probability seismic drift collapse results in a zone of low thermal-conductivity rubbelized host rock that increases
In-drift temperatures and the duration of boiling
The magnitude of the duration of in-drift relative-humidity reduction
Figure 4. Heated repository footprint represented by the MSTHM, including “contingency” area shown in purple.
Figure 5. Drift-wall temperature (a) and liquid-phase saturation (b) for three approaches to lumping thermal and hydrologic properties and for a full representation of the thermal-hydrologic property distributions
NUMERICAL MODEL
NOTE: A study of alternative approaches to lumping thermal and hydrological properties concluded that discrete representation of thermal properties in the four repository host-rock units and generalizing hydrological properties to 2 host-rock units: lithophysal and nonlithophysal, yielded similar TH predictions as a full representation of thermal and hydrologic property distributions (Fig. 5). It was also found that the 10th and 30th percentile hydrologic properties yielded similar TH predictions (Fig. 12).
REFERENCES
Figure 6. Complementary cumulative distribution function (CCDF) of peak drift-wall (a) and waste-package (b) temperature
Nitao, J.J., User's manual for the USNT module of the NUFT code, version 2 (NP-phase, NC-component, thermal), Lawrence Livermore National Laboratory, UCRL-MA , 1998.
Buscheck, T.A., N.D. Rosenberg, J. Gansemer, and Y. Sun. Thermohydrologic behavior at an underground nuclear waste repository, Water Resour. Res., 38(3), 1431−1447, 2002.
SNL (Sandia National Laboratories). Multiscale Thermohydrologic Model. ANL-EBS-MDL REV03 AD01. Las Vegas, Nevada: Sandia National Laboratories
BSC (Bechtel SAIC Corporation). Development of Numerical Grids for UZ Flow and Transport Modeling. ANL-NBS-HS REV 02. Las Vegas, Nevada: Bechtel SAIC Company
SNL (Sandia National Laboratories). UZ Flow Models and Submodels. ANL-NBS-HS REV 03. Las Vegas, Sandia National Laboratories
SNL (Sandia National Laboratories). Simulation of Net Infiltration for Present-Day and Potential Future Climates. MDL-NBS-HS REV01. Las Vegas, Nevada: Sandia National Laboratories
SNL (Sandia National Laboratories). Postclosure Analysis of the Range of Design Thermal Loadings. ANL-NBS-HS REV01. Las Vegas, Nevada: Sandia National Laboratories
BSC (Bechtel SAIC Company). Thermal Conductivity of the Potential Repository Horizon. MDL-NBS-GS REV01. Las Vegas, Nevada: Bechtel SAIC Company
Figure 7. Range of drift-wall (a) and waste-package (b) temperature for the 7 cases
Figure 8. Complementary cumulative distribution function (CCDF) of the maximum horizontal extent of the boiling zone
NOTE: The “ensemble” is the weighted average of the 7 cases, with the weights listed in Table 2.
Figure 2. MSTHM calculation steps (a) and plan view of SMT submodel (b)
The NUFT code [1] is used to generate submodel results for 4 families of submodel; the MSTHM [2,3] integrates the results from those four families of submodels
3-D Smeared-heat-source Mountain-scale Thermal (SMT) submodel
Represents mountain topography and stratigraphy, and the drift and panel layout in the repository
Extends 1 km below water table and a minimum of 1 km laterally from repository edges
1-D Smeared-heat-source Drift-scale Thermal (SDT) submodel
Ties together the SMT and LDTH submodels by using the same heat-flow representation as the SMT submodel
2-D Line-averaged-heat-source Drift-scale Thermal-Hydrologic (LDTH) submodel
Simulates TH processes in the drifts and host rock
3-D Discrete-heat-source Drift-scale Thermal (DDT) submodel
Represents geometric details of the drifts
Simulates thermal radiation in the drifts
Accounts for waste-package (WP) heat-generation variability and uncertainty, using an 8-WP unit cell, with 2 full PWR CSNF WPs, 2 half-PWR CSNF WPs, 2 full BWR CSNF WPs, and 2 full DHLW WPs
ACKNOWLEDGEMENTS
CONTACT INFORMATION
This work was performed under the auspices of the U.S. Department of Energy by the University of California, Lawrence Livermore National Laboratory under Contract No. DE-AC52-07NA Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.
Lawrence Livermore
National Laboratory
Thomas A. Buscheck
Thermal Hydrologist
Hydrologic Science Group
Atmospheric, Earth and Energy Division
P.O. Box 808, L-631
7000 East Avenue
Livermore, CA 94550
Fax:
Lawrence Livermore National Security, LLC
Operated for the US Department of Energy
Figure 11. Complementary cumulative distribution function (CCDF) of time when boiling ceases on drift wall (a) and waste package (b)
Figure 12. Drift-wall temperature (a) and liquid-phase saturation (b) for the 10th and 30th percentile hydrologic property sets
Figure 9. Range of drift-wall (a) and invert (b) liquid-phase saturation for the 7 cases
Figure 10. Range of drift-wall (a) and waste-package (b) relative humidity for the 7 cases
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