Fission Yield Uncertainty Analysis of Pebble-Bed High-Temperature Gas-Cooled Reactor Based on Detailed Burnup Chain

CUI Menglei¹,²,*, WANG Lianjie¹, WANG Yizhen³, GUO Jiong²

¹ Nuclear Reactor System Design Technology Key Laboratory, China Nuclear Power Research and Design Institute, Chengdu 610213, China
² Institute of Nuclear and New Energy Technology, Tsinghua University, Advanced Nuclear Energy Technology Co-Innovation Center, Key Laboratory of Advanced Reactor Engineering and Safety, Ministry of Education, Beijing 100084, China
³ Harbin Engineering University, College of Nuclear Science and Technology, Harbin 150001, China

*Corresponding author: CUI Menglei (1995–), female, engineer, Ph.D. in Nuclear Science and Engineering, specializing in reactor physics, 416458845@qq.com.

[Abstract]

[Objective] The pebble-bed high-temperature gas-cooled reactor (HTGR) is a continuously refueled reactor with spherical fuel elements. In the equilibrium core, each fuel pebble undergoes approximately 15 passes through the core, being loaded from the top and discharged from the bottom under gravity, resulting in a complex burnup history. During the burnup process in the equilibrium core, fission yields and their uncertainties primarily affect the composition, concentration levels, and spatial distribution of nuclides in the core's nuclide inventory. In the equilibrium state, these nuclide-related factors remain constant. After reactor shutdown, fission yield uncertainty propagates to decay heat uncertainty through nuclide concentration uncertainty. Since decay heat uncertainty in pebble-bed HTGRs determines the maximum fuel pebble temperature under accident conditions and is crucial for inherent safety, it is essential to investigate the contribution of fission yield uncertainty to nuclide concentration uncertainty during equilibrium core burnup.

[Methods] Currently, the VSOP-UAM core physics design and uncertainty analysis code for pebble-bed HTGRs can quantify the contribution of fission yield uncertainty to uncertainties in keff and nuclide concentrations in the equilibrium core. However, VSOP-UAM simplifies the burnup calculation process, omits many burnup chains, and can only output information for approximately one hundred nuclides, making it incapable of detailed quantitative analysis of fission yield uncertainties. Therefore, developing a refined burnup uncertainty analysis capability based on detailed burnup chains and a complete nuclide library is necessary. The NUIT core source term calculation code can perform constant-power burnup and decay heat calculations for pebble-bed HTGRs while providing complete burnup and nuclide library information. NUIT-EMBAD, an existing module for 235U fission yield uncertainty analysis, serves as the foundation for this work.

[Results] Based on the NUIT-EMBAD burnup uncertainty analysis code, this study developed fission yield uncertainty analysis capabilities for 233U, 239Pu, and 241Pu using detailed burnup chains, quantitatively analyzing the contribution of each fission yield uncertainty to overall burnup uncertainty. Comparative analysis reveals that the contributions of 239Pu and 235U fission yield uncertainties to the burnup process are comparable. NUIT-EMBAD's calculated uncertainty contributions for actinide nuclide concentrations are generally smaller than those from VSOP-UAM, while the results for fission product concentrations show minimal differences between the two codes.

[Conclusion] These findings demonstrate the accuracy of the NUIT-EMBAD uncertainty analysis code. Furthermore, NUIT-EMBAD can output complete nuclide concentration uncertainty information, enabling refined decay heat uncertainty analysis for pebble-bed HTGRs based on these results.

[Keywords] pebble-bed HTGR; fine burnup uncertainty analysis; fission yield uncertainty; nuclide concentration uncertainty; NUIT-EMBAD

[DOI] 10.16516/j.ceec.2025-083

Funding: National Natural Science Foundation of China project "Research on uncertainty propagation method under multi-pass refueling mode" (11505102)

Compared to pressurized water reactors with fixed fuel configurations, the unique refueling mode and flowing core of pebble-bed high-temperature gas-cooled reactors make it difficult to precisely simulate the burnup irradiation history experienced by each fuel pebble from loading to discharge [1]. The equilibrium core theoretical refueling model is illustrated in Figure 1 [FIGURE:1], where the entire simulation divides the core axially into 20 layers. Fuel pebbles move downward one layer every 3 days under gravity, with each batch representing a refueling pass, and the complete refueling process for each pebble spans 1056 days. This results in complex uncertainty inputs accompanying the burnup calculations for pebble-bed HTGRs [2-3]. Moreover, burnup uncertainty analysis for pebble-bed HTGRs is critical for reactor operational design and inherent safety evaluation, representing an important component of overall uncertainty analysis for this reactor type [4-5].

Fission yield uncertainty constitutes one source of nuclear data uncertainty, with its uncertainty range provided by nuclear data libraries. It influences the uncertainty of the burnup process in pebble-bed HTGRs and significantly contributes to uncertainties in important operational parameters such as keff and equilibrium core nuclide concentrations [4]. Additionally, due to the high burnup characteristics of pebble-bed HTGRs, the fission fraction of 239Pu exceeds that of 235U during later burnup stages, as shown in Figure 2 [FIGURE:2]. Therefore, it is necessary to accurately quantify the contribution of fission yield uncertainties for fissile nuclides such as 239Pu to the core burnup process [6].

Current computational tools for burnup uncertainty analysis in pebble-bed HTGRs primarily include VSOP-UAM [7], the SCALE/SAMPLER module [2, 8], and NUIT-EMBAD [9]. The former can analyze multi-group nuclear cross-sections and fission yield uncertainties for fissile nuclides, but VSOP simplifies the reactor burnup calculation process and burnup chains, only outputting concentration and uncertainty information for approximately one hundred nuclides [6, 10], and lacks the capability to output complete burnup information for pebble-bed HTGRs. While the latter possesses detailed burnup calculation and uncertainty analysis capabilities for pebble-bed HTGRs, it lacks the refined power history functionality for simulating pebble flow movement [11]. The NUIT-EMBAD code, developed based on the NUIT source term analysis program for pebble-bed HTGRs [12], features detailed constant-power burnup calculation capabilities, including all intermediate and short-lived nuclides generated during burnup and decay processes. The program already includes fission yield uncertainty analysis functionality for 235U and can output complete nuclide concentration information and uncertainty data for the equilibrium core nuclide library [2], providing a foundation for refined decay heat calculations in pebble-bed HTGRs. Therefore, this study developed fission yield uncertainty analysis capabilities for 233U, 239Pu, and 241Pu based on the NUIT-EMBAD code, outputting detailed nuclide concentration uncertainty information for the equilibrium core of a pebble-bed HTGR and comparing the results with VSOP-UAM calculations [5] to demonstrate the accuracy of the developed uncertainty analysis functionality.

1 NUIT-EMBAD Uncertainty Analysis Process

The NUIT-EMBAD uncertainty analysis process is illustrated in Figure 3 [FIGURE:3]. This study employs a sampling statistics methodology, treating the code as a "black box" and randomly perturbing fission yields based on the uncertainty data provided by the ENDF/B-VII.1 library to quantify the uncertainty of output parameters through physical calculation and simulation of the pebble-bed HTGR [13-14]. The analysis process primarily consists of:

1) Using the Bayesian update method and fission yield and decay data from the ENDF/B-VII.1 library to calculate the covariance of independent fission yield data from thermal neutron-induced fission [15-16];

2) Assuming the probability density distribution follows a multivariate log-normal distribution based on the physical non-negativity of independent fission yields, with distribution parameters derived from the mean and covariance data of independent fission yields, and using Latin hypercube sampling to generate multiple sets of random perturbation samples for independent fission yields [17-19];

3) Matching the independent fission yield perturbation samples with the NUIT-EMBAD fission yield library (the matching process is shown in Figure 4) to generate the NUIT-EMBAD fission yield random perturbation sample library, and conducting numerical simulation calculations in NUIT-EMBAD for each perturbation sample library;

Figure 4 NUIT-EMBAD fine burnup calculation process for pebble-bed HTGR

4) Statistically analyzing the standard deviation of nuclide concentrations output by NUIT-EMBAD and using this standard deviation data as the quantitative result [4].

1.1 NUIT-EMBAD Detailed Burnup Uncertainty Calculation Process

The NUIT-EMBAD burnup calculation process is illustrated in Figure 4 [2]. This method is based on the equilibrium core of a pebble-bed HTGR and utilizes NUIT's constant-power burnup calculation capability along with complete nuclide library information to simulate the detailed burnup power history experienced by each fresh fuel batch from initial loading through multiple burnup cycles until final discharge from the core, obtaining both nuclide composition and concentration information for the complete core nuclide library.

During the NUIT-EMBAD burnup uncertainty analysis process, each fission yield perturbation sample library generates a corresponding set of nuclide concentration calculation results. By statistically analyzing the uncertainties across these complete nuclide library datasets, comprehensive uncertainty information for the entire nuclide library can be obtained and statistically processed.

Additionally, to validate the correctness of the NUIT-EMBAD burnup uncertainty analysis process, fission yield uncertainties were also obtained using the VSOP-UAM code.

Building upon this foundation, this study conducts evaluation of fission yield covariance matrices and fission yield uncertainty analysis based on the NUIT-EMBAD code.

1.2 Evaluation of Fission Yield Covariance Matrices

The first step involves the estimation process for fission yield covariance matrices. Based on the independent fission yield data for 239Pu thermal fission from the ENDF/B-VII.1 fission yield database and the ENDF/B-VII.1 decay database, the normal Bayesian update method is employed to incorporate four constraint conditions for independent fission yields: cumulative fission yield constraint, total independent fission yield constraint, mass number conservation of the fission system, and charge number conservation of the fission system, to evaluate the fission yield covariance matrix [4]. The relevant constraint conditions are listed in Table 1 [TABLE:1], and the specific steps are illustrated in Figure 5 [FIGURE:5]. After four levels of updates using the Bayesian method, the fission yield correlation coefficient matrices for each nuclide can be obtained, as shown in Figure 6 [20].

Table 1 Each fission yield covariance matrix constraint

Constraint 239Pu 241Pu I. Cumulative fission yield constraint E[Ytot]=ytot=2.0 II. Total independent fission yield conservation E[Atot]=atot=231.55 E[Atot]=atot=237.10 III. Mass number conservation of fission system E[Atot]=atot=239.05 IV. Charge number conservation of fission system E[Ztot]=ztot=92.01 E[Ztot]=ztot=94.00

Note: The table formatting in the original source appears incomplete.

Figure 5 Evaluation process of fission yield covariance matrix

Figure 6 [FIGURE:6] Fission yield correlation matrix of 233U, 239Pu and 241Pu

Based on the updated matrices, log-normal sampling is performed [20] to generate various perturbation samples.

1.3 NUIT-EMBAD Perturbation Database Matching Process

Based on the updated fission yield covariance matrices, it is necessary to conduct a consistency evaluation study between the fission yield sample library and the NUIT-EMBAD fission yield database, with the process illustrated in Figure 7 [FIGURE:7].

Figure 7 The process of establishing the fission yield perturbation database in NUIT-EMBAD

Analysis reveals that since the NUIT-EMBAD fission yield database is constructed using independent fission yield data for fissile nuclides provided by the ENDF/B-VII.1 fission yield database, the perturbation sample library generated based on ENDF/B-VII.1 can be directly mapped to the independent fission yield library used by NUIT-EMBAD, satisfying consistency requirements. In other words, the independent fission yield sample library generated from the ENDF/B-VII.1 database can be directly applied to burnup calculations in the NUIT-EMBAD code for conducting relevant burnup uncertainty analysis research.

2 Calculation Results and Validation

Since decay heat calculations for high-temperature gas-cooled reactors are critical for inherent safety evaluation, quantifying the contribution of uncertainties originating from nuclide library parameters to detailed burnup uncertainty in pebble-bed HTGR cores is essential [1]. This analysis focuses on fission yield uncertainties for thermal fission of 233U, 235U, 239Pu, and 241Pu in high-temperature gas-cooled reactors. First, a comparative analysis is conducted on the contributions of fission yield uncertainties from 239Pu and 235U fission to nuclide concentration uncertainties in NUIT-EMBAD. Second, the contributions of fission yield uncertainties for all four nuclides to burnup calculation uncertainties are compared between VSOP and NUIT-EMBAD to evaluate the magnitude of each fission yield uncertainty and validate the accuracy of NUIT-EMBAD's fission yield uncertainty analysis functionality. During the analysis, results were separately compiled for actinide nuclides and fission product nuclides, with detailed results presented in Tables 2 [TABLE:2] through 5 [TABLE:5] and Figure 8 [FIGURE:8].

Table 2 Comparison of the relative uncertainty contributions (%) of fission yield uncertainties of U to the nuclide concentration uncertainties of actinide isotopes

| Nuclide concentration relative uncertainty (%) | Nuclide concentration relative uncertainty (%)) |
| 2.93×10 | 1.12×10 |
| 5.10×10 | 239Pu |
| 5.49×10 | 2.68×10 |
| 2.04×10 | 6.37×10 |
| 1.43×10− | 1.36×10 |
| 1.52×10 | 240Pu |
| 5.47×10 | 2.84×10− |
| 9.19×10 | 9.80×10 |
| 6.49×10 | 1.85×10− |
| 6.82×10 | 1.12×10 |
| 241Pu | 5.76×10 |
| 1.23×10− | 2.74×10 |
| 1.95×10 | 237U |
| 1.33×10 | 2.17×10− |
| 9.18×10 | 4.58×10 |
| 242Pu | 1.17×10 |
| 3.94×10− | 7.41×10 |
| 5.29×10 | 1.48×10 |
| 4.03×10− | 3.72×10 |
| 6.40×10 | 2.78×10 |
| 6.20×10− | 1.48×10 |
| 2.99×10 | 1.05×10 |
| 2.82×10− | 8.69×10 |
| 3.44×10 | 4.59×10 |
| 6.12×10− | 1.48×10 |
| 2.98×10 | 1.87×10 |
| 1.48×10− | 8.69×10 |
| 5.80×10 | 4.88×10 |
| 3.95×10− | 3.18×10 |
| 6.78×10 | 3.09×10 |
| 2.28×10− | 1.75×10 |
| 8.32×10 | 1.47×10 |
| 3.09×10− | 2.10×10 |
| 4.14×10 | 1.96×10 |
| 6.80×10− | 2.32×10 |
| 1.18×10 | |

Table 3 [TABLE:3] Comparison of the relative uncertainty contributions (%) of fission yield uncertainties of Pu to the nuclide concentration uncertainties of actinide isotopes

| Nuclide concentration relative uncertainty (%) | Nuclide concentration relative uncertainty (%) |
| 241Pu | 239Pu |
| 核素浓度相对不确定度（%） | 241Pu |
| 239Pu | 9.25×10 |
| 3.61×10 | 2.14×10 |
| 5.91×10 | 239Pu |
| 3.40×10 | 5.17×10 |
| 7.89×10 | 3.65×10 |
| 1.13×10 | 9.95×10 |
| 2.88×10 | 1.51×10 |
| 240Pu | 9.20×10 |
| 5.57×10 | 2.12×10 |
| 7.01×10 | 5.59×10 |
| 7.13×10 | 1.40×10 |
| 1.05×10 | 241Pu |
| 2.85×10 | 1.29×10 |
| 6.94×10 | 1.92×10 |
| 1.09×10 | 4.08×10 |
| 2.55×10 | 8.45×10 |
| 242Pu | 5.42×10 |
| 4.02×10 | 1.46×10 |
| 7.00×10 | 4.17×10 |
| 4.61×10 | 1.01×10 |
| 7.69×10 | 1.48×10 |
| 2.67×10 | 3.61×10 |
| 5.55×10 | 1.30×10 |
| 2.50×10 | 2.90×10 |
| 4.17×10 | 1.49×10 |
| 2.67×10 | 3.59×10 |
| 5.53×10 | 8.86×10 |
| 4.41×10 | 2.28×10 |
| 7.72×10 | 3.72×10 |
| 9.56×10 | 8.86×10 |
| 3.22×10 | 1.73×10 |
| 6.59×10 | 4.37×10 |
| 1.20×10 | 1.88×10 |
| 3.24×10 | 4.79×10 |
| 6.07×10 | 2.43×10 |
| 9.63×10 | 6.16×10 |
| 1.81×10 | |

Table 4 [TABLE:4] Comparison of the relative uncertainty contributions (%) of fission yield uncertainties of U to the nuclide concentration uncertainties of fission products

| Nuclide concentration relative uncertainty (%) | Nuclide concentration relative uncertainty (%) | VSOP | NUIT | VSOP | NUIT |
| 136Xe | 8.42×10⁻⁶ | 5.31×10⁻¹¹ | 0.22 | 0.21 |
| 143Pr | 1.70×10⁻⁵ | 1.34×10⁻¹⁰ | 0.26 | 0.27 |
| 83Kr | 5.69×10⁻⁶ | 6.92×10⁻¹¹ | 0.38 | 0.64 |
| 143Nd | 3.73×10⁻⁶ | 2.62×10⁻¹⁰ | 0.29 | 0.29 |
| 95Zr | 5.04×10⁻⁶ | 1.51×10⁻¹⁰ | 0.37 | 0.40 |
| 144Nd | 7.76×10⁻⁶ | 7.06×10⁻¹² | 0.18 | 0.18 |
| 95Mo | 6.95×10⁻⁶ | 2.07×10⁻¹⁰ | 0.86 | 0.43 |
| 145Nd | 6.59×10⁻⁶ | 1.03×10⁻¹⁰ | 0.35 | 0.42 |
| 97Mo | 7.09×10⁻⁶ | 7.27×10⁻¹¹ | 0.41 | 0.43 |
| 146Nd | 1.01×10⁻⁵ | 2.66×10⁻¹⁰ | 2.71 | 3.32 |
| 147Pm | 4.29×10⁻⁶ | 1.15×10⁻¹⁰ | 0.51 | 0.55 |
| 99Tc | 6.09×10⁻⁶ | 3.17×10⁻¹² | 0.41 | 0.44 |
| 101Ru | 4.55×10⁻⁶ | 1.39×10⁻¹¹ | 0.47 | 0.48 |
| 148mPm | 5.59×10⁻⁶ | 1.08×10⁻¹⁰ | 0.52 | 0.55 |
| 148Pm | 9.09×10⁻⁶ | 1.11×10⁻¹⁰ | 0.52 | 0.55 |
| 103Ru | 6.03×10⁻⁶ | 1.64×10⁻¹⁰ | 0.10 | 1.02 |
| 147Sm | 5.99×10⁻⁶ | 1.73×10⁻¹⁰ | 0.56 | 0.59 |
| 103Rh | 5.98×10⁻⁶ | 2.69×10⁻¹¹ | 1.18 | 1.20 |
| 148Sm | 1.05×10⁻⁵ | 4.01×10⁻¹¹ | 0.56 | 0.60 |
| 105Rh | 2.16×10⁻⁵ | 5.84×10⁻¹¹ | 0.26 | 0.30 |
| 149Pm | 9.17×10⁻⁶ | 3.51×10⁻¹⁰ | 0.55 | 0.68 |
| 105Pd | 6.89×10⁻⁶ | 8.34×10⁻¹² | 0.34 | 0.39 |
| 149Sm | 2.06×10⁻⁵ | 3.65×10⁻¹⁰ | 0.54 | 0.66 |
| 108Pd | 1.26×10⁻⁵ | 1.94×10⁻¹¹ | 0.38 | 0.66 |
| 150Sm | 6.47×10⁻⁶ | 1.60×10⁻¹⁰ | 0.66 | 0.82 |
| 109Ag | 7.25×10⁻⁶ | 5.73×10⁻¹¹ | 0.74 | 0.93 |
| 151Sm | 5.56×10⁻⁶ | 3.05×10⁻¹⁰ | 2.04 | 2.52 |
| 7.11×10⁻⁶ | 9.73×10⁻¹¹ | 1.27 | 1.63 |
| 152Sm | 5.96×10⁻⁶ | 1.92×10⁻¹⁰ | 1.93 | 2.45 |
| 131Xe | 9.06×10⁻⁶ | 1.03×10⁻¹⁰ | 1.45 | 1.84 |
| 133Xe | 6.94×10⁻⁶ | 1.28×10⁻¹⁰ | 0.21 | 0.28 |
| 133Cs | 9.16×10⁻⁶ | 2.77×10⁻¹⁰ | 0.29 | 0.32 |
| 134Cs | 1.35×10⁻⁵ | 2.70×10⁻¹⁰ | 0.25 | 0.34 |
| 141Pr | 5.31×10⁻⁶ | 1.62×10⁻¹⁰ | 0.49 | 0.45 |

Table 5 Comparison of the relative uncertainty contributions (%) of fission yield uncertainties of Pu to the nuclide concentration uncertainties of fission products

| Nuclide concentration relative uncertainty (%) | 241Pu | 239Pu | Nuclide concentration relative uncertainty (%) | 239Pu | 241Pu |
| VSOP | NUIT | VSOP | 136Xe | 101Ru | 103Ru | 103Rh | 105Rh | 105Pd | 143Pr | 143Nd | 144Nd | 145Nd | 146Nd | 147Pm | 148mPm | 0.70 | 148Pm | 147Sm | 148Sm | 149Pm | 108Pd | 109Ag | 131Xe | 133Xe | 133Cs | 134Cs | 141Pr | 149Sm | 150Sm | 151Sm | 152Sm | 153Eu | 154Eu | 155Eu | 156Gd |

Figure 8 [FIGURE:8] Comparison of nuclide concentration uncertainties

As indicated in Tables 2-5 and Figure 7, the contribution of fission yield uncertainty to actinide nuclide concentration uncertainty is significantly smaller than that to fission products. First, comparing actinide nuclide concentration uncertainties reveals that NUIT-EMBAD results are generally smaller than VSOP results. This occurs because VSOP is a core design code for pebble-bed HTGRs that can handle the strong coupling of the reactor system. During the burnup calculation phase, perturbations to fission yields affect the power values of each batch, which in turn influences the neutron physics calculation phase combined with pebble flow movement, ultimately directly impacting actinide nuclide concentrations. In contrast, NUIT-EMBAD performs constant-power calculations without incorporating reactor neutron physics processes, resulting in very small statistical uncertainty results for actinide nuclide concentrations, with fission yield uncertainty contributing negligibly to actinide nuclide concentration uncertainty.

Simultaneously, comparing fission product nuclide concentration uncertainties shows that the statistical results from VSOP and NUIT-EMBAD are nearly consistent. On one hand, both codes use the ENDF/B-VII.1 fission yield library, and fission yield uncertainty directly propagates to fission product nuclide concentration uncertainty. On the other hand, these results indirectly demonstrate the reliability of the nuclide concentration uncertainty statistical results from NUIT-EMBAD's fission yield uncertainty analysis functionality, enabling subsequent work to be based on these uncertainty results.

Specifically, 239Pu's contribution to actinide nuclide concentration uncertainty ranges from 4.6E-7 to 9.6E-5. In contrast, 239Pu's contribution to fission product nuclide concentration uncertainty is substantially larger, ranging from 0.095% to 12.73%, because fission yield uncertainty directly affects the accumulated concentration of fission products. The nuclide concentration uncertainty for 109Ag reaches 12.73%, while the contribution from 235U to its uncertainty is only 0.93%. This is primarily because 109Pd produced from 239Pu thermal fission undergoes β-decay to 109Ag with a very short half-life of only 13.7 hours. Furthermore, the fission yield and its uncertainty for 109Pd production from 239Pu thermal fission are larger than those from 235U. This demonstrates that the contribution of 239Pu fission yield uncertainty to nuclide concentration uncertainty must be considered. The decay model for 109Ag is shown in Figure 9 [FIGURE:9].

Figure 9 109Ag decay models

This study primarily built upon the NUIT-EMBAD code by adding fission yield uncertainty analysis capabilities for thermal fission of 233U, 239Pu, and 241Pu, thereby completing the NUIT-EMBAD fission yield uncertainty analysis functionality and enabling refined quantitative analysis of the contribution of fission yield uncertainty to nuclide concentration uncertainty in the equilibrium core of pebble-bed HTGRs. Comparison with VSOP-UAM calculation results demonstrates the accuracy of the NIUT-EMBAD fission yield uncertainty analysis results. During shutdown or accident conditions, fission yield uncertainty propagates to decay heat uncertainty through nuclide concentration uncertainty, representing one source of decay heat uncertainty. Therefore, this code can be used to investigate refined decay heat uncertainty in pebble-bed HTGRs.

The statistical results indicate that:

1) For fission yield uncertainty in the equilibrium core of pebble-bed HTGRs, the uncertainty contribution to fission products is substantially greater than that to actinide nuclides;

2) Comparing the calculation results of the two codes reveals that for fission product nuclide concentration uncertainty, the statistical results are similar between both codes, while for actinide nuclides, VSOP-UAM results are larger than NUIT-EMBAD results because NUIT-EMBAD performs constant-power calculations without incorporating reactor neutron physics processes, leading to smaller statistical results;

3) The close agreement between VSOP-UAM and NUIT-EMBAD nuclide concentration uncertainty results validates the correctness of the burnup calculation uncertainty analysis results from the NUIT-EMBAD code;

4) The analysis results demonstrate that the contribution of 239Pu fission yield uncertainty to nuclide concentration uncertainty is comparable to that of 235U, and therefore the uncertainty of 239Pu fission yields cannot be neglected. Specifically, the contribution of 239Pu fission yield uncertainty to the nuclide concentration uncertainty of 109Ag reaches as high as 12.73%.

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