Analysis of the Molten Salt Fast Reactor using reduced-order models. (October 2021)

• Record Type: Journal Article
• Authors: Alsayyari, Fahad; Tiberga, Marco; Perkó, Zoltán; Kloosterman, Jan Leen; Lathouwers, Danny
• Is Part Of: Progress in nuclear energy. Volume 140(2021)
• Publication Date: 2021-10
• Subjects: Proper orthogonal decomposition -- Data-driven -- Adaptive -- Molten Salt Fast Reactor -- Uncertainty and sensitivity analysis -- Transient analysis; Nuclear energy -- Periodicals; Nuclear engineering -- Periodicals; 333.7924
• DOI: 10.1016/j.pnucene.2021.103909
• Languages: English
• ISSNs: 0149-1970

Abstract

Abstract: In this paper, we present a reduced-order modeling approach to study the Molten Salt Fast Reactor (MSFR). Our approach is nonintrusive and based on the proper orthogonal decomposition method. We include adaptivity in selecting the sampling points both in time and parameter space. Steady-state and transient analysis were both performed using the developed models. In the steady-state analysis, we capture the effect of 30 model parameters on the spatial distributions of fission power and temperature, and on the multiplication factor. The dimensionality of the fission power was reduced from the 104288 nominal dimensions in the physical space to 10 dimensions in the reduced space, whereas the temperature was reduced from 220972 dimensions to 3. The reduced model was then used for uncertainty and sensitivity study of the maximum temperature in the reactor and the multiplication factor. In the transient analysis, the reduced model captured the effect of perturbations in the flow rate of salt in the intermediate circuit on the fission power density and temperature. The reduced models were successfully tested on a set of points that were not part of the snapshots used during the construction stage. Highlights: Reduced-order modeling for a three-dimensional model of the Molten Salt Fast Reactor (MSFR). A data-driven adaptive approach for both steady-state and transient analysis. Uncertainty and sensitivity analysis considered 30 model parameters. A dynamic reduced-order model for transient analysis.