## 6 Conclusions  
The tritium breeding ratio (TBR) is the fundamental integral nuclear response of the fusion DEMO reactor that provides the most critical judgment of the project technical feasibility for the sustainable tritium fuel cycle and industrial fusion energy. The TBR allows to support or reject engineering solutions employed in the DEMO blankets technology and it contributes to the acceptance of the technical solutions. To enable the reliable operation of the tritium fuel cycle, the minimum TBR\({}_{\text{target}}\) = 1.05 must be demonstrated by the DEMO tokamak with all included blankets and auxiliary systems. At the current phase of the DEMO development, the tokamak architecture is not finalized and the thereby introduced certain uncertainty of the TBR must be accounted for in the blanket design. To this end, the blanket must be potentially capable to compensate all such uncertainties to ensure the achievement of the TBR\({}_{\text{target}}\). The consolidated blanket design of the HCPB DEMO can meet this requirement and the WCLL DEMO could reach it marginally. The nuclear data serve as the fundamental basic information that allows performing particle transport calculations in the DEMO geometry and as the result they enable the development of the DEMO design. The choice of the nuclear data library can significantly affect the results of the MCNP calculations leading to the incorrect justifications of the output. As all the nuclear data involved in the calculations inherently include some uncertainties due to their physical nature, their use for the TBR calculations also introduces some additional uncertainty to this integral response. If included in the final uncertainty of the TBR in the DEMO project, it can significantly affect the blanket development strategy. In this work, we applied the TMC approach for the nuclear data uncertainty propagation of the TBR integral response in the DEMO fusion facility. For the calculations, the TENDL-2017 data were varied by making use of the so-called random files included in this library. The TMC method provides the reliable information for the assessment and the judgment of the TBR uncertainty that nuclear data bring in the DEMO project. To provide credible TMC results, the investigations were performed to determine the reliable parameters that must be applied in the calculations, in both the MCNP and TMC computations. The MCNP statistical uncertainty of the results is below 0.1% that is much less compared to the uncertainties calculated with TMC method and therefore it does not affect the final results. The TMC simulations were also optimized to ensure the convergence of the results: 300 random files for each nuclide involved in the MCNP calculations were proved to be enough, as 10,000 TMC cycles provide results which can reliably fit with the Gaussian distributions. Figure 11: The TBR distribution for the TENDL-2017 data with random files for each nuclide and 300 random files for n+\({}^{56}\)Fe from JEFF-3.2. The TMC method optimized for the DEMO applications appeared to a powerful tool for the assessment of the TBR integral response uncertainty for the nuclear data. These separate studies were carried out to estimate the TBR uncertainty for the n+\({}^{6}\)Li, n+\({}^{9}\)Be and n+\({}^{56}\)Fe nuclear data. The separate effects of \({}^{9}\)Be and \({}^{56}\)Fe data for the TBR uncertainty do not exceed 3%. The use of the original \({}^{6}\)Li covariance data available in the modern nuclear data libraries results in the very low (\(\sim\)0.05%) uncertainty of the TBR and the application of the modified covariance data accounting for the majority of the experimental data leads to \(\sim\)2% of the TBR uncertainty. The total effect of the nuclear data uncertainties for the uncertainty of the TBR was assessed to be \(\sim\)3 and \(\sim\)4% for the HCPB and WCLL DEMOs, respectively. The uncertainty of the \({}^{6}\)Li data appeared to not be dominant in the whole assessment.