## 5 Results of the TMC Uncertainties Assessments
### Analyses of the Effect of the Nuclear Data for \({}^{56}\)Fe  
Since iron makes up approximately 90% of the steel mass composition, the significant differences between the mean and reference TBR values obtained with TENDL-2017 data result from different evaluations for iron isotopes included in these libraries. The most  
Figure 9: TBR statistical distributions for the HCPB and WCLL DEMOs.  
abundant isotope of iron is \({}^{56}\)Fe (\(\sim\)90% in the natural mixture), and therefore, the effect of the evaluated data for this isotope dominates the final effect of Eurofer steel.  
The TMC calculations only performed with variation of the n+\({}^{56}\)Fe data, i.e., involving only random files from TENDL-2017 for \({}^{56}\)Fe provide the uncertainty estimation of the TBR to only these data. The results of these calculations and their fit with the Gaussian distribution are presented in Figure 10a. Ten thousand TMC cycles were executed with the HCPB DEMO geometry model. The mean TBR value calculated with the Gaussian fit is 1.165, which is close to the TBR = 1.164 obtained previously with TENDL-2017 data. This result differs significantly from the TBR = 1.181 obtained as recommended for the fusion-related tasks, as the JEFF-3.2 data indicate the importance of the nuclear data used in the calculations. The use of the covariance data included in the n+\({}^{56}\)Fe evaluation from the TENDL-2017 library results in the bright TBR distribution with the \(\sigma\) = 0.056 (4.8%) being fitted with the Gaussian distribution.  
The effect of the nuclear data choice was further investigated by the replacement of the n+56 Fe data in TENDL-2017 with one from the JEFF-3.2 library. The 300 random files were generated with BEKED from original JEFF-3.2 file. The results of the 10,000 TMC cycles are presented in Figure 10b. The mean TBR value was calculated to be 1.173. Therefore, the replacement of the n+\({}^{56}\)Fe nuclear data with JEFF-3.2 leads to the significant increase in the TBR (+0.008) compared to the results with only TENDL-2017 data (TBR = 1.164). The standard deviation in this case is \(\sigma\) = 0.035 (3%). These data support the conclusion that the nuclear data used for the MCNP calculations affect the results for TBR uncertainty to a high extent.  
Based on the TENDL-2017 data (with 300 random files for each nuclide) and data for n+\({}^{56}\)Fe from JEFF-3.2 (with 300 random files), the 10,000 TMC repetitions were performed to obtain the modified TBR statistical distribution for both the HCPB and WCLL DEMOs. The random files for n+\({}^{6}\)Li and n+\({}^{9}\)Be data were produced with BEKED codes as described previously. The results of the simulations are shown in Figure 11. The mean TBR values were calculated to be 1.173 and 1.146 for the HCPB and the WCLL DEMOs, respectively. The standard deviation of the results \(\sigma\) = 0.035 (3%) for the HCPB and \(\sigma\) = 0.096 (-4%) for the WCLL DEMOs. The spread of the TBR is bigger compared to the results obtained for the TENDL-2017 library because of the replacement of the \({}^{56}\)Fe data with the JEFF-3.2 data.  
Figure 10: The TBR statistical distribution for the variated n+\({}^{56}\)Fe data from TENDL-2017 library (**a**) and TBR distribution for the TENDL-2017 data and 300 random files for n+\({}^{56}\)Fe from JEFF-3.2 (**b**).