Speaker
Description
Energetic particles in nuclear fusion devices are essential for the heating of the plasma. The power deposition strongly depends on parameters of the plasma and equilibrium. However, uncertainties cannot be neglected. In that context, this work addresses how uncertainties in different parameters characterizing the plasma can impact the power deposition and the particle sources. We focus our analysis on the application of uncertainty quantification and sensitivity analysis to the neutral beam injection (NBI) by performing parametric modeling of the thermal equilibrium [1], [2] and the ionization process [3] – [5] of the plasma. For modeling the uncertainty distributions we considered that the uncertain input parameters are independent, each with a non-informative uniform distribution, which reflects our lack of knowledge of the shape of such a distribution, while the bounds selected are based on data and expert knowledge. These are propagated through the TAPAS code (Toroidal Accelerated PArticle Simulator) [6], obtaining various qualities of interest, such as the birth profile of the NBI and the fraction of energy that is transferred to the background plasma ions and electrons [7]. By considering a non-intrusive, black-box approach, we represent these random model responses by utilizing a Polynomial Chaos Expansion (PCE) as a surrogate model [8]. Finally, a global sensitivity analysis is conducted [9] through the computation of the Sobol' indices from the estimated coefficients of the PCE [10]. This aims to quantify the contribution of each uncertain parameter to the output variance, allowing for factor prioritization, as well as to quantify the total effects of the interactions between different parameter combinations [11].
References
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[2] E. Stefanikova et al., “Fitting of the Thomson scattering density and temperature profiles on the COMPASS tokamak,” Review of Scientific Instruments, vol. 87, no. 11, 11E536, 2016, issn: 0034-6748. doi: 10.1063/1.4961554.
[3] R. Janev et al., “Atomic and plasma-material interaction data for fusion,” IAEA, Vienna, 1993.
[4] R. Koch, “Plasma heating by neutral beam injection,” Fusion science and technology, vol. 45, no. 2T, pp. 183–192, 2004.
[5] C. Hill et al., “Atomic collisional data for neutral beam modeling in fusion plasmas,”Nuclear Fusion, vol. 63, no. 12, p. 125 001, 2023.
[6] H. Betar et al., “Transport and losses of energetic particles in tokamaks in the presence of alfvén activity using the new full orbit tapas code coupled to far3d,” Nuclear Fusion. 2024. doi: 10.1088/1741-4326/ad7c66.
[7] C. Hopf et al., “Neutral beam injection for fusion reactors: Technological constraints versus functional requirements,” Nuclear Fusion, vol. 61, 2021, issn: 17414326. doi: 10.1088/1741-4326/ac227a.
[8] D. Xiu et al., “The wiener–askey polynomial chaos for stochastic differential equations,” SIAM Journal on Scientific Computing, vol. 24, no. 2, pp. 619–644, 2002. doi: 10.1137/S1064827501387826.
[9] I. M. Sobol, “Sensitivity estimates for nonlinear mathematical models,” 1993.
[10] B. Sudret, “Global sensitivity analysis using polynomial chaos expansion,” Reliability Engineering & System Safety, vol. 93, pp. 964–979, Jul. 2008. doi: 10.1016/j.ress.2007.04.002.
[11] A. Saltelli, “Sensitivity analysis for importance assessment,” Risk analysis : an official publication of the Society for Risk Analysis, vol. 22, pp. 579–90, 2002. doi: 10.1111/0272-4332.00040
| Presentation type | Oral |
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