SHORT-TERM STORAGE CONSIDERATIONS FOR SPENT PLUTONIUM THORIUM FUEL BUNDLES

Transcription

1 FULL FULL ARTICLE ARTICLE To support the development of advanced pressurized heavy water reactor (PHWR) fuel cycles, it is necessary to study short-term storage solutions for spent reactor fuel. In this paper, some representational criticality safety and shielding assessments are presented for a particular PHWR plutonium thorium based fuel bundle concept in a hypothetical aboveground dry storage module. The criticality assessment found that the important parameters for the storage design are neutron absorber content and fuel composition, particularly in light of the high sensitivity of code results to plutonium. The shielding assessment showed that the shielding as presented in the paper would need to be redesigned to provide greater gamma attenuation. These findings can be used to aid in designing fuel storage facilities. SHORT-TERM STORAGE CONSIDERATIONS FOR SPENT PLUTONIUM THORIUM FUEL BUNDLES Laura Blomeley*, Clifford Dugal, Eugene Masala, and Thuy Tran Canadian Nuclear Laboratories, Chalk River, ON K0J 1J0, Canada Article Info Keywords: criticality safety; radiation shielding; sensitivity and uncertainty; pressurized heavy water reactor fuel; thorium; spent fuel storage Article History: Received 20 August 2015, Accepted 5 October 2015, Available online 26 November DOI: *Corresponding author: laura.blomeley@cnl.ca Nomenclature k eff effective neutron multiplication factor PHWR pressurized heavy water reactor Pu Th fuel mixed oxide fuel containing reactor-grade plutonium and thorium USL upper subcritical limit wt% weight percentage n fission neutron yield σ standard deviation χ fission spectrum 1. Introduction Thorium-based fuels have emerged as 1 option for advanced fuel cycles using recycled fuels; here we consider some of the short-term waste storage implications of using such fuels with pressurized heavy water reactors (PHWR). Long-term storage implications of decay heat and longterm fission products have previously been discussed in the literature [1 3]. However, the issues surrounding criticality safety for waste streams involving 233 U and shielding for shorter lived isotopes in the waste streams have not been considered in depth for PHWR bundles. As thorium-based PHWRs and associated spent fuel storage systems have not yet been built, nor are plans fully developed to do so, we used the specifications for a conceptual fuel bundle with plutonium thorium (Pu Th) fuel for the studies presented in this work. The fuel concept and exit fuel composition are based on previous work [3]. With no specific plans for implementation of PHWR thorium-based fuel cycles, it is unknown what type of systems will be used to store spent fuel. For this work, we have assumed that dry aboveground storage will be used, as is currently used for natural uranium PHWRs. Specifically, we have elected to analyze large concrete modules because they are commonly used, and the large fuel capacity brings with it additional scenarios that need to be considered. The modelled concrete module has a capacity of fuel bundles in a configuration roughly similar to existing aboveground dry storage modules used for storing conventional spent natural uranium PHWR bundles; no special changes to the configuration were made to accommodate the different characteristics of Pu Th fuel. 105

2 106 An analysis based on the combined use of the bundle concept and storage modules discussed previously was performed to assess the implications of the fuel composition on the criticality safety of short-term storage of spent thorium-based fuels. Sensitivity and uncertainty due to the nuclear data were assessed for the significant criticality safety calculations to determine the quality of current nuclear data evaluations. Finally, dose rates inside and outside the storage module were estimated to evaluate the adequacy of shielding. Together, these studies have evaluated the applicability of present short-term storage methods for advanced thorium-based fuels and identified some important considerations for designing storage modules that are specific to PHWR thorium-based fuel. 2. Codes and Methods 2.1. Criticality safety, sensitivity, and uncertainty analyses For the criticality safety calculations, KENO V.a from the SCALE 6.1 [4] code suite was used with a continuous-energy ENDF/B-VII.0-based nuclear data library. Canadian regulatory requirements on criticality safety applications require a margin of subcriticality to be assured, usually with an upper subcritical limit (USL) applied to calculation results that incorporates results of code validation and other terms, including a 50 mk administrative margin. Though this work does not present a safety case, per se, a USL on the effective neutron multiplication factor (k eff ) of was selected for the application for consistency with current spent fuel safety analysis. Scenarios are considered subcritical with sufficient margin if their calculated k eff (plus 2σ of calculation uncertainty) is below that USL. The values used in this work are not based on real scenarios and the goal of the exercise is simply to identify important parameters for consideration. For the nuclear data assessment of the criticality calculations, TSUNAMI, from the SCALE 6.0 code suite was used. TSUNAMI refers to a set of modules that facilitate the application of sensitivity and uncertainty analysis. For the scope of the present analysis, only the TSUNAMI-3D module was used with the included 44-group covariance data library. TSUNAMI-3D is a SCALE control sequence that executes the 3D Monte Carlo code KENO V.a followed by the SAMS module. KENO V.a is used to obtain 3D forward and adjoint fluxes from an eigenvalue (k eff ) calculation. SAMS is used to compute sensitivity coefficients by combining multigroup crosssection data with forward and adjoint fluxes from KENO V.a to be used in the adjoint-based perturbation calculations [5]. SAMS also has the capability to calculate uncertainties in k eff code results that are due to cross-section uncertainties. The SAMS code performed calculations to provide sensitivity data in the form of individual variations of each nuclide reaction and their propagation through the code calculations by means of a linear perturbation method to assess the impact of these perturbations to the code results, such as k eff. Based on the sensitivity data and known cross-section uncertainties from the covariance data libraries, a total code result uncertainty was calculated for k eff results along with the individual contributions to this uncertainty from specific nuclide reactions. The uncertainty in the calculated value of k eff, resulting from uncertainties in the basic nuclear data used in the calculation, is estimated using energy-dependent relative covariance matrices Shielding assessment The simulation to calculate dose rates in and around a dry storage module with spent Pu Th fuel bundles was carried out using MCNP [6]. Only photons were considered for this work, as it is expected that photons will present the largest component to the dose. The photon library used was based on ENDF/B-VI.8. Reflective boundary conditions were used to take advantage of the quarter-symmetry of the storage module. Weight windows were used for variance reduction to adjust for the attenuation of photons through the concrete walls and to increase the sampling of otherwise rare higher energy photons. 3. Geometry and Materials It is expected that the characteristics of a Pu Th fuel bundle would be similar to what is presented here, but the details are not yet defined. Although both the criticality safety analysis and the shielding assessment were performed for the same general fuel arrangement in the same dry storage module, different approaches and simplifications were used in the respective analyses. The general descriptions of the geometric and material models are presented in the following sections,where it is noted when the 2 analyses differed in the assumptions and modelling approaches used Pu Th fuel bundle The Pu Th fuel bundle was modelled as having 1 central neutron-absorbing element surrounded by 42 fuel elements. The 42 fuel elements are arranged in 3 rings, referred to as inner, intermediate, and outer rings. For the shielding calculations, the bundle was modelled as presented in Edwards et al. [3], and it is shown in Figure 1. There were small differences between the fuel geometry specifications used in the criticality and shielding analyses. The neutron absorber material of the central element (when modelled) was defined to be 98.0 wt% Hf and 2.0 wt% Zr at a density of 12.7 g/cm 3. For all analyses, this fresh absorber composition was used, despite the fact that the absorber would deplete as it is irradiated. In the shielding analysis, the absorber was modelled as a Hf Zr annulus around a Zircaloy-4 cylinder.

3 FIGURE 1. Cross-section of a fuel bundle Fresh fuel composition Input composition for the fresh Pu Th fuel is based on a Pu Th fuel type that has been discussed previously [3]. This fuel is a mixture of ThO 2 and PuO 2 at a density of 9.7 g/cm 3. The weight fractions of ThO 2 and PuO 2 in the mixture are wt% and 3.75 wt%, respectively. The plutonium had nuclide mass fraction values of 2.6 wt% 238 Pu, 54.2 wt% 239 Pu, 23.8 wt% 240 Pu, 12.6 wt% 241 Pu, and 6.8 wt% 242 Pu. The Pu Th fresh fuel composition is presented in Table Exit burnup fuel composition The spent fuel material was taken from a burnup calculation [3], and it varied between fuel rings. The spent fuel composition corresponded to fresh fuel burned to 20.4 MWd per kilogram of initial actinoids at a constant average thermal flux in the assembly of n/cm 2 /s for 650 days (average of 31.4 kw per kilogram of initial actinoids), then left to decay for 5 years. TABLE 1. Composition of fresh plutonium thorium fuel. Nuclide Weight percentage 238 Pu Pu Pu Pu Pu O Th For calculations of k eff, only the fissile nuclides of the burnup calculation were used as input compositions of spent fuel. Other nonfissile nuclides (such as oxygen and fission products), which would generally act as neutron absorbers, were omitted in the compositions. The fuel density for the spent fuel was specified as being the same density as that for fresh fuel, 9.7 g/cm 3, despite the omission of nonfissile nuclides. As burnup credit in criticality calculations is at various levels of acceptance in the regulatory sphere, not including the fission products gives a conservative estimate of the safety margin. The compositions for the spent Pu Th fuel are presented in Table 2. For the shielding calculations, a more detailed chemical element based representation of the fuel was used, with 38 chemical elements specified for each ring of fuel elements Dry storage module The dry storage module was modelled as a hollow box with an approximate exterior footprint of 22 m 11 m and a height of 8 m. Walls were modelled as 1 m thick regulardensity concrete. The interior of the storage module was filled with an array of 4 10 vertical steel storage cylinders. Within each storage cylinder, there was an array of 10 stainless steel fuel baskets, vertically stacked, and each fuel basket contained 60 vertical Pu Th fuel bundles arranged in 4 rings of 6, 12, 18, and 24 bundles. Slightly different geometric specifications for the storage cylinders and fuel baskets were used in the criticality safety and shielding analyses. A horizontal cross-section of the fuel basket model with 60 Pu Th fuel bundles is shown in Figure 2. Vertical and horizontal views of the dry storage module are shown in Figure 3. TABLE 2. Compositions of spent plutonium thorium fuel for criticality safety analyses. Nuclide Inner ring wt% (density = 9.7 g/cm 3 ) Intermediate ring wt% (density = 9.7 g/cm 3 ) Outer ring wt% (density = 9.7 g/cm 3 ) 232 Th Pa U U U U U Np Pu Pu Pu Pu Pu Am Am Cm Note: wt%, weight percentage. 107

4 108 FIGURE 2. Cross-section of the fuel basket model with 60 plutonium thorium fuel bundles. FIGURE 3. Storagecylindersina10 4arrayinadrystorage module. 4. Criticality Safety, Sensitivity, and Uncertainty Analyses 4.1. Criticality safety analysis The scope of the present work is to support the concept of a short-term storage facility for spent Pu Th fuel from a criticality safety perspective. It is accomplished here by modelling specific normal and abnormal conditions that may arise in the representative storage model by natural causes, human error, or flawed design to draw generic conclusions that can be used for designing short-term storage facilities. These conditions are modelled in separate cases that have different configurations of the fuel bundle material and the moderation condition, highlighting deviations such as flooding, spacing, and material composition. The cases and their results are presented in Table 3. Cases 1 and 2 simulated the dry condition with spent Pu Th fuel with and without Hf Zr central absorber elements, respectively. The (k eff + 2σ) results obtained are (case 1) and (case 2). These correspond to typical normal storage conditions and show that there is a large margin of safety for such conditions. Cases 3 and 4 were modelled with Hf Zr central absorber elements and light water flooding in the storage cylinders. The space between the storage cylinders was filled with water (case 3) or air (case 4). The results of the 2 cases are the same (k eff +2σ = 0.732). As the storage cylinders are approximately 1 m apart, water flooding between the cylinders would be enough to ensure full neutron reflection and isolation. In other words, each storage cylinder may be treated as an isolated (single) unit when flooded. Case 5 was modelled the same as case 4 but without Hf Zr central absorber elements. This case yielded a (k eff +2σ) of 0.769, almost 40 mk higher than the case 4 result (k eff + 2σ = 0.732). This shows that the absence of the absorber element under flooding condition could increase the k eff more significantly than under normal dry conditions. However, in both the cases of flooding, the subcriticality margin is still large. Cases 6 and 7, with 4 storage cylinders placed side by side (as shown in Figure 4), simulated concurrent flooding and violation of storage cylinder spacing. Similar to cases 3 and 4, the space between the storage cylinders was filled with water (case 6) or air (case 7). The results obtained are k eff + 2σ = (for case 6) and k eff +2σ = (for case 7). This indicates that the neutron interaction was more effective when the space between cylinders was filled with air instead of water. However, the difference between the results of case 6 and case 7 is not much higher than the calculation standard deviations, and again, these results demonstrate that each storage cylinder can be considered an isolated unit, and that the arrangement of the storage cylinders would not affect the safety.

5 TABLE 3. Cases calculated for criticality safety analysis. Case Fuel configuration Condition k eff +2σ 1 Spent fuel bundles with Hf Zr central absorber elements. Dry condition: air filled all the spaces inside fuel baskets and storage cylinders and between storage cylinders. 2 Spent fuel bundles without Hf Zr central absorber elements. Dry condition: air filled all the spaces inside fuel baskets and storage cylinders and between storage cylinders. 3 Spent fuel bundles with Hf Zr central absorber elements. Flooding condition: light water filled all the spaces inside fuel baskets and storage cylinders and between storage cylinders. 4 Spent fuel bundles with Hf Zr central absorber elements. 5 Spent fuel bundles without Hf Zr central absorber elements. 6 Spent fuel bundles with Hf Zr central absorber elements, but 4 storage cylinders were placed side by side (Figure 4). 7 Spent fuel bundles with Hf Zr central absorber elements, but 4 storage cylinders were placed side by side (Figure 4). 8 Spent fuel bundles without Hf Zr central absorber elements, but 4 storage cylinders were placed side by side (Figure 4). 9 Ten fresh fuel bundles without Hf Zr central absorber elements (Figure 5). The rest of the bundles were spent fuel bundles with Hf Zr central absorber elements. 10 Ten fresh fuel bundles (Figure 5). The rest of the bundles were spent fuel bundles. All fuel bundles had no Hf Zr central absorber elements. 11 Twenty fresh fuel bundles without Hf Zr central absorber elements (Figure 5). The rest of the bundles were spent fuel bundles with Hf Zr central poison elements. 12 Twenty fresh fuel bundles (Figure 5). The rest of the bundles were spent fuel bundles. All fuel bundles had no Hf Zr central absorber elements. 13 Sixty fresh fuel bundles (1 fuel basket) without Hf Zr central absorber elements (Figure 6). The rest of the bundles were spent fuel bundles with Hf Zr central poison elements. 14 Sixty fresh fuel bundles (1 fuel basket) (Figure 6). The rest of the bundles were spent fuel bundles. All fuel bundles had no Hf Zr central absorber elements. 15 One-hundred twenty fresh fuel bundles (2 fuel baskets) without Hf Zr central poison elements (Figure 6). The rest of the bundles were spent fuel bundles with Hf Zr central absorber elements. 16 One-hundred twenty fresh fuel bundles (2 fuel baskets) (Figure 6). The rest of the bundles were spent fuel bundles. All fuel bundles had no Hf Zr central absorber elements. 17 Fresh fuel bundles with Hf Zr central absorber elements in all the fuel baskets. 18 Fresh fuel bundles without Hf Zr central absorber elements in all the fuel baskets. Flooding condition: light water filled all the spaces inside fuel baskets and storage cylinders and between storage cylinders

6 FIGURE 4. Horizontal cross-section of dry storage module with 4 storage cylinders placed side by side (cases 6, 7, and 8). Case 8 was modelled the same as case 7 but the fuel bundles had no Hf Zr central absorber elements. This case yielded a (k eff +2σ) of 0.767, approximately 30 mk higher than the case 7 result (k eff +2σ = 0.734). The difference in the k eff of these cases is almost the same as that of cases 5 and 4. Cases 9 16 (Figures 5 and 6) were all modelled with the same flooding configuration (as cases 4 and 5) but different fuel bundle configurations (i.e., spent fuel or fresh fuel and with or without Hf Zr central absorber elements in different numbers of fuel bundles or fuel baskets). These cases test how much fresh fuel would have to be accidentally emplaced for potential criticality safety concerns to emerge. Because fresh fuel is more reactive, this gives an indication of how sensitive the results are to the fuel composition. The results show that the system would be subcritical if fresh fuel without Hf Zr central absorber elements was in 10 bundles (cases 9 and 10), 20 bundles (cases 11 and 12), or even 60 bundles (1 fuel basket, cases 13 and 14). However, the USL of was exceeded in cases 15 and 16 with 120 bundles (2 fuel baskets) of fresh fuel without Hf Zr central absorber elements. The presence or absence of Hf Zr central absorber elements in the remaining spent fuel bundles of these cases had no effect on the results. Cases 17 and 18 were also modelled with the same flooding configuration but all the fuel baskets contained fresh fuel with and without Hf Zr central absorber elements. The results show that the storage with fresh fuel bundles would be safe if the bundles have Hf Zr central absorber elements (case 17: k eff +2σ = 0.919) but would not be safe if the bundles have no Hf Zr central absorber elements (case 18: k eff + 2σ = 0.957). Comparing case 18 with cases 15 and 16, the likelihood of cases 15 and 16 would be higher than that of case 18. As a result, the configuration of cases 15 and 16, i.e., concurrent flooding and 2 fuel baskets containing fresh fuel, is considered the onerous criticality scenario for the storage. FIGURE 5. Horizontal cross-section of the 2 fuel baskets, 1 with 10 fresh plutonium thorium fuel bundles and the other with 20 bundles (cases 9, 10, 11, and 12). 110

7 contributors to the total code result uncertainty provided by the SAMS output, are shown in Figures The sensitivity values represent the expected relative change in k eff due to relative changes in the cross-sections. These sensitivities are intrinsic to the material containing that nuclide and its spatial distribution within the analyzed system. Figures 7 and 8 show the sensitivity profiles for the top 5 nuclide reaction contributors to the overall calculated k eff value, for fresh and spent fuel, respectively. It can be observed from Figures 7 and 8 that the top contributors to nuclear data sensitivity are similar for the 2 fuel FIGURE 6. Vertical cross-section of the abnormal storage cylinder showing the position of the abnormal fuel basket(s) (cases 13, 14, 15, and 16) Sensitivity and uncertainty analysis A sensitivity and uncertainty analysis on the KENO V.a code results was performed using the TSUNAMI code suite. Known uncertainties in the cross-section data were applied in TSUNAMI for various configurations, and useful information such as sensitivity and uncertainty in the calculated k eff values were determined along with contributions from individual nuclide reactions Cases selected for sensitivity and uncertainty analysis In the TSUNAMI analyses, KENO V.a input files selected from the criticality safety analysis were used to perform the additional sensitivity and uncertainty analyses. These sensitivity and uncertainty analyses are based on the uncertainties in the nuclear data libraries. In the criticality safety analysis, multiple cases were considered to cover a range of varying parameters that affect the results of the calculations such as fuel type (fresh vs. spent Pu Th fuel), absorber in the central element of the bundle, geometry, and moderation configurations (see Table 3). Of these cases, 6 representative cases (cases 3, 4, 5, 8, 15, and 17) were selected for the TSUNAMI analysis. In the TSUNAMI analysis, the KENO V.a input files initially prepared for these selected cases were used, with additional specifications included for running the SAMS code to perform the sensitivity and uncertainty calculations Sensitivity analysis A sensitivity analysis for k eff is presented in this section. Key k eff sensitivity plots, based on the top nuclide reaction FIGURE 7. Sensitivity profiles for the top 5 contributors for fresh fuel nuclide reactions. FIGURE 8. Sensitivity profiles for the top 5 contributors for spent fuel nuclide reactions. 111

8 types (fresh vs. spent), with 239 Pu (n) (fission neutron yield) and 239 Pu (fission) having the largest positive contributions to sensitivity in k eff in both cases. The difference in terms of sensitivities between the 2 fuel types is highlighted by the presence of 241 Pu (fission) in Figure 8 for the spent fuel. The largest negative contributors to sensitivity in k eff (i.e., neutron absorbers) are 232 Th (n,γ), 239 Pu (n,γ), and 240 Pu (n,γ). These results show that the fuel material components are most important in terms of nuclear data sensitivities. Though the fuel bundle design is different, it may be useful to note that the sensitivities are similar to those noted for Pu Th SCWR fuel in Blomeley et al. [7]. Figures 9 11 show the sensitivity plots of individual nuclide reactions for fresh and spent fuel. It can be observed from these plots that the magnitude of the sensitivities differs for the different fuel types. In particular, sensitivities for fresh fuel are about twice as large as those for spent fuel for 239 Pu (fission) and 239 Pu (n,γ), but only marginally larger for 239 Pu (total) because the positive sensitivities from fissions are counterbalanced by the negative sensitivities from absorptions. This difference in sensitivities will be reflected in the individual uncertainty contributions to the overall uncertainty of the calculated k eff value, as discussed in the uncertainty analysis section. Figures 12 and 13 show the sensitivity profiles for 1 H (n,γ), corresponding to neutron absorption in water, in different flooding configurations, for fresh and spent fuel. Figure 12 corresponds to case 3 in which light water filled all the spaces inside the fuel baskets and storage cylinders and between the storage cylinders, whereas Figure 13 corresponds to cases 4 and 17 in which the space between the storage cylinders was filled with air while everything else was filled with water. Under the same partial flooding configuration, the sensitivity for the neutron absorption in water is slightly higher in absolute value for the spent fuel than for fresh fuel (Figure 13). Under different flooding configurations (full flooding vs. partial flooding), the sensitivity for the neutron absorption in water is higher in absolute value for the case of full flooding (Figure 12) than for partial flooding (Figure 13), as was expected, although the difference is relatively small. FIGURE 10. Sensitivity profile of k eff to 239 Pu (n,γ) for fresh and spent fuel. 112 FIGURE 9. Sensitivity profile of k eff to 239 Pu fission for fresh and spent fuel. FIGURE 11. Sensitivity profile of k eff to 239 Pu total for fresh and spent fuel.

9 Figure 14 shows the sensitivity profile of Hf (n,γ) representing the neutron absorptions in the Hf of the central element. Although Hf plays an important role as a neutron absorber, the sensitivity associated with it is very small as compared with the top nuclide reactions analyzed so far. This is due to the relatively small amount of Hf, present in the fuel bundle, in the central element of the bundle. Hf therefore does not play a significant role in the sensitivity and uncertainty analysis of the fuels considered in this study. By looking at how the sensitivity is distributed along the entire neutron energy spectrum, it can be observed from all FIGURE 12. Sensitivity of k eff to 1 H(n,γ) for fresh fuel, full flooding (case 3). sensitivity plots presented previously that most of the sensitivity for a nuclide reaction is located around the energy of the thermal neutrons, in a region below 1 ev, for both absorption and fission reactions. The fissile nuclides also have a more limited component around the resonance energies, in a region from a few ev to hundreds of ev. The low energy resonance for neutron absorption in 240 Pu at around 1 ev is also visible in Figures 7 and Uncertainty analysis The uncertainties in the computed k eff and reactivity coefficients due to the uncertainties in the cross-section data were calculated with the SAMS module of TSUNAMI. The sensitivities presented in the sensitivity analysis section are dependent on the material containing that nuclide and its amount and spatial distribution within the analyzed system. When these sensitivities are coupled with the uncertainties in the cross-sections, the individual contributions of each nuclide reaction to the uncertainty of the calculated k eff is determined. FIGURE 14. Sensitivity of k eff to Hf (n,γ) for fresh and spent fuel. FIGURE 13. Sensitivity of k eff to 1 H(n,γ) for fresh and spent fuel, partial flooding. TABLE 4. Overall uncertainties in k eff due to cross-section covariance data. Case k eff deviation (%) Standard Standard deviation (mk) Case Case Case Case Case Case

10 Table 4 presents the overall k eff uncertainty results from the TSUNAMI analysis applied for each of the selected cases. The values presented in this table represent the total uncertainties in calculated k eff propagated through the code from the uncertainties in the cross-sections of all nuclide reactions, across the entire energy spectrum, for a case. The uncertainties are presented as standard deviations in relative units (δk eff /k eff ) and in absolute units (mk). It can be observed that the uncertainties for the cases with fresh fuel (cases 15 and 17) are noticeably higher than uncertainties for the cases with spent fuel (cases 3, 4, 5, and 8). This is due mostly to the fact that sensitivities associated with the fresh fuel nuclide reactions were larger than for the spent fuel, as it was discussed in the sensitivity analysis section, and it can be seen in Figure 11. The isotopic compositions for the fresh and spent Pu Th fuel, for the cases used in this analysis, are presented in Tables 1 and 2. The sensitivity of the code result to a nuclide reaction cross-section, and therefore the contribution of that nuclide reaction to k eff uncertainty, depends on the amount of that nuclide in the analyzed system, among other factors. Thus, the isotopic compositions for the fresh and spent fuel presented in these tables give an indication of the amount of each nuclide in the fuel mix. Therefore, the interpretation of individual nuclide contributions to sensitivities and uncertainties can be better understood by reference to these isotopic compositions. TABLE 5. Uncertainties in k eff due to cross-section covariance data by individual contributors in case 4, spent fuel with Hf poison. Nuclide reaction Nuclide reaction δk eff /k eff (%) δk eff (mk) Fraction of total uncertainty (%) 239 Pu (n) 232 Th (n,γ) 239 Pu (fission) 240 Pu (n,γ) 239 Pu (fission) 241 Pu (fission) 239 Pu (n,γ) 233 U (fission) 1 H (n,γ) 242 Pu (n,γ) 1 H (elastic) 241 Pu (n) 241 Am (n,γ) 233 U(n) 241 Pu (fission) 239 Pu (n) Th (n,γ) Pu (fission) Pu (n,γ) Pu (n,γ) Pu (fission) Pu (n,γ) U (fission) H (n,γ) Pu (n,γ) H (elastic) Pu (n) Am (n,γ) U(n) Pu (n,γ) TABLE 6. Uncertainties in k eff due to cross-section covariance data by individual contributors in case 5, spent fuel without Hf poison. Nuclide reaction Nuclide reaction δk eff /k eff (%) δk eff (mk) Fraction of total uncertainty (%) 239 Pu (n) 232 Th (n,γ) 239 Pu (fission) 240 Pu (n,γ) 239 Pu (fission) 241 Pu (fission) 239 Pu (n,γ) 242 Pu (n,γ) 233 U (fission) 1 H (n,γ) 241 Pu (n) 1 H (elastic) 241 Am (n,γ) 233 U(n) 241 Pu (fission) 239 Pu (n) Th (n,γ) Pu (fission) Pu (n,γ) Pu (n,γ) Pu (fission) Pu (n,γ) Pu (n,γ) U (fission) H (n,γ) Pu (n) H (elastic) Am (n,γ) U(n) Pu (n,γ)

11 TABLE 7. Uncertainties in k eff due to cross-section covariance data by individual contributors in case 17, fresh fuel. Nuclide reaction Nuclide reaction δk eff /k eff (%) δk eff (mk) Fraction of total uncertainty (%) 239 Pu (n) 239 Pu (fission) 239 Pu (fission) 239 Pu (n,γ) 232 Th (n,γ) 240 Pu (n,γ) 241 Pu (fission) 1 H (n,γ) 241 Pu (n) 242 Pu (n,γ) 1 H (elastic) 241 Pu (n,γ) 239 Pu (χ) 56 Fe (n,γ) 241 Pu (fission) 239 Pu (n) Pu (fission) Pu (n,γ) Pu (n,γ) Th (n,γ) Pu (n,γ) Pu (fission) H (n,γ) Pu (n) Pu (n,γ) H (elastic) Pu (n,γ) Pu (χ) Fe (n,γ) Pu (n,γ) Tables 5 7 present the individual nuclide reaction contributions to the uncertainty of the calculated k eff for various cases including spent and fresh Pu Th fuel. The first 2 columns of these tables present the nuclide reaction pairs that are correlated to determine the covariance term used in the calculation of the uncertainty. Tables 5 and 6 present the uncertainty results for spent fuel, with and without Hf absorber. The differences between the 2 tables are minor, due to the limited impact of the Hf absorber on the code results and sensitivities/uncertainties, as discussed in the sensitivity analysis section and shown in Figure 14. The Hf (n,γ) uncertainty component, although it exists, is very small and did not make the top contributors list presented in Table 6 because of the very small amount of Hf absorber present only in the central element of the fuel bundle. Table 7 presents the uncertainty results for fresh fuel. Comparison of uncertainty data in Tables 5 and 7 for spent versus fresh fuel shows that 239 Pu sensitivity and contribution to uncertainty in k eff results is the highest by far among all contributors (over 80% by combined reactions), whereas 232 Th (n,γ) accounts for 14% for the spent fuel and only 4% for the fresh fuel. The intrinsic large 239 Pu sensitivity is evident as it is only a small component of the Pu Th fuel (1.8 wt% for fresh fuel and 0.9 wt% for spent fuel; cf. compositions in Tables 1 and 2). The high uncertainty arising from 239 Pu has been previously noted in Pu Th fuel [7] and is indicative of known uncertainties in the cross-section data. That contrasts with 232 Th, which has a relatively small contribution to uncertainty, and yet it is the largest fraction of the fuel s composition (84.6 wt% for fresh fuel and 96.6 wt% for spent fuel). 239 Pu, with both fission and absorption reactions, is therefore the largest contributor to the overall uncertainty in the calculated k eff value, with a cumulated value of 63% for spent fuel (Table 5) and 90% for fresh fuel (Table 7). The next main contributors are 240 Pu by absorption with 11% for spent fuel and 2% for fresh fuel and 241 Pu by fission with 4% and 1.7%, respectively. For spent fuel (Table 5), 241 Am and 233 Umakeittothelistof top contributors ( 241 Am as neutron absorber and 233 U with fission), although with small contributions, due to their very small amounts in the spent fuel mix. 5. Shielding Analysis The shielding assessment considered the dose rate for a full storage module of identical fuel bundles. As a FIGURE 15. Cross-section of the storage module showing 2 storage cylinders. 115

12 116 simplification, the ground under and surrounding the dry storage module was specified as being completely flat, composed of the same regular density concrete as was used for the construction of the storage module. A side cross-section of this setup is seen in Figure 15. Surrounding the storage module was air with a composition and density that roughly corresponded to sea-level air at 20 C with 40% relative humidity Radiation source Only the photon sources from the exit burnup fuel were considered for this work. Furthermore, only 3 different photon spectra, one for each of the bundle element rings, were considered. The spectra were obtained as part of the burnup calculation previously described [3], and the photon spectra per element are plotted in Figure 16. Those photon sources were applied uniformly to the fuel meat of each of the elements, based on the ring to which the element belongs Dose rate calculation Dose rates were calculated by tallying photon flux averaged over a volume and converting it to the ambient dose equivalent rate at a depth of 10 mm, H*(10), using flux to dose rate conversion coefficients from ICRP 74 [8]. The dose rates calculated by MCNP5 at various locations in and around the storage module are listed in Table 8. In the extreme case of someone standing directly beside such a storage module for 2500 h in a year, his or her effective dose for the year would be around 100 msv, exceeding the regulatory limit (which is an average of 20 msv per year for a Photon Rate per Unit Energy (/s/mev) 1E+14 1E+13 1E+12 1E+11 1E+10 1E+9 1E+8 1E+7 1E+6 1E+5 1E+4 1E+3 1E+2 Outer Element Intermediate Element Inner Element Photon Energy (MeV) FIGURE 16. Photon spectra per element for the 3 rings of elements. TABLE 8. Calculated dose rates for a dry storage module filled with spent PuTh fuel. Location Canadian nuclear energy worker). At 100 m away, his or her yearly effective dose would be around 1 msv for the same amount of time. Because these dose rates are at least twice as high as those seen for similar natural uranium spent fuel storage, it would likely be desired to use more effective shielding than that that analyzed here: 1 m of regular density concrete. 6. Conclusions Ambient dose equivalent, H*(10), rate (µsv/h) Length direction Width direction Height direction Inside wall Outside wall m from outside wall m from outside wall m from outside wall km from centre of module Calculations for spent advanced Pu Th based fuel stored in a dry storage module demonstrated that the fuel was subcritical under either dry or flooding conditions. The subcriticality was shown not be affected by the presence or absence of Hf Zr central absorber elements for spent fuel. However, for fresh fuel, the presence of Hf Zr central absorber elements was shown to have significant effect on criticality. The most onerous criticality scenario identified is the case in which the fuel bundles in 2 fuel baskets (i.e., 120 fuel bundles) were fresh fuel without Hf Zr central absorber elements. The calculation results also show that the storage cylinders were mostly neutron isolated under flooding condition. This indicates that the spacing between the storage cylinders has no criticality safety effect. Consequently, the material compositions used for modelling the air and the concrete boundaries would have no significant effect on the results either. Other parameters that may have significant effect on the (k eff +2σ) are the material and the geometry of the fuel bundles. Therefore, further studies and analyses will need to be performed when detailed design of fuel and storage options is complete. The TSUNAMI analysis complements the preliminary criticality assessment, identifying the main nuclide contributors to the sensitivity and uncertainty in the k eff values calculated with KENO V.a. A list of top contributors was identified, both by sensitivities and by uncertainties. The main contributor to uncertainty, by a large margin, was identified to be 239 Pu, by both fission and neutron absorption reactions,

13 with a cumulated value of 63% for spent fuel and 90% for fresh fuel. The next main contributor was 232 Th by neutron absorption, with 16% for spent fuel and 4% for fresh fuel, followed by 240 Pu by absorption with 11% for spent fuel and 2% for fresh fuel, and 241 Pu by fission with 4% and 1.7%, respectively. 241 Am (as neutron absorber) and 233 U (with fission) have relatively small contributions for the spent fuel, whereas Hf, as an absorber, showed insignificant sensitivity and contribution to uncertainty due to its very limited amount in the fuel mix. It was also shown that sensitivities, and therefore associated uncertainty contributions, were larger for fresh fuel than for spent fuel. Dose rates around the hypothetical storage module were calculated and shown to be somewhat high for 1 m thick regular-density concrete. For storing such a quantity of spent fuel, more effective shielding is likely desired. ACKNOWLEDGEMENTS This work would not have been possible without the efforts of Geoffrey Edwards, who provided the fuel specifications and photon spectra upon which all the calculations are based. REFERENCES [1] J. Frybot, 2014, Comparison of the Radiological Hazard of Thorium and Uranium Spent Fuels from VVER-1000 Reactor, Radiation Physics and Chemistry, 104, pp doi: /j.radphyschem [2] C.E. Velasquez, R.V. Sousa, A. Fortini, C. Pereira, A.L. Costa, C.A.M. da Silva, M.A.F. Veloso, A.H. de Oliveira, and F.R. de Carvalho, 2014, Spent Fuel Criticality and Compositions Evaluation for Long-term Disposal in a Generic Cask, Nuclear Engineering and Design, 275, pp doi: /j.nucengdes [3] G. Edwards, B. Hyland, C. Kitson, and T. Chschyolkova, 2013, Postclosure Performance Assessment of a Deep Geological Repository for Advanced Heavy Water Reactor Fuels, AECL Nuclear Review, 2(2), pp doi: /ANR [4] S.M. Bowman, 2011, SCALE 6: Comprehensive Nuclear Safety Analysis Code System, Nuclear Technology, 174(2), pp doi: / NT [5] A. Gandini, 1967, A Generalized Perturbation Method for Bilinear Functionals of the Real and Adjoint Neutron Fluxes, Journal of Nuclear Energy, 21, pp [6] MCNP Team, 2005, MCNP RSICC Release Notes, Los Alamos National Laboratory, Los Alamos, NM, USA. [7] L. Blomeley, J. Pencer, B. Hyland, and F.P. Adams, 2014, Nuclear Data Sensitivity and Uncertainty for the Canadian Supercritical Water-cooled Reactor, Annals of Nuclear Energy, 63, pp doi: /j. anucene [8] ICRP, 1996, Conversion Coefficients for Use in Radiological Protection against External Radiation, Annals of the ICRP, 26(3 4), pp PMID: