A Review of Molten Salt Reactor Kinetics Models

Abstract

Interest in circulating fuel reactors (CFRs), particularly molten salt reactors (MSRs) of the fluid fuel type, has been growing in the last two decades. Starting with a resurgence of interest in Europe, there have been a growing number of methods proposed and codes developed to model the kinetics of CFRs, which is a capability essential to the design and evaluation of such reactors. This work first reviews the physical phenomena unique to CFRs in light of current research and how CFR kinetics are impacted by these considerations. In general, it is found that the movement of delayed neutron precursors (DNPs) through the primary loop has significant impacts on transients at low reactor powers or those with significant spatial components such as a change in the primary loop mass flow rate. Effects on the neutron flux are exceedingly minimal and entirely negligible. An extensive review of published models and methods for simulating CFR kinetics is presented, along with transient simulations in fast and thermal neutron flux systems using representative codes from each of the main modeling categories. Comparisons among methods are presented as are recommendations for their use or nonuse in various transient and work-flow scenarios. In general, it is recommended that time-resolved, multigroup neutron diffusion approaches be used to establish ranges of applicability for point reactor kinetics (PRK)–based approaches that themselves may not be applicable for all modeling situations. In such cases, it is suggested that quasi-static approaches be used where PRK-based approaches cannot be used. Finally, a review of common assumptions used in these models is presented, along with an evaluation of their impact on model performance. It is found that neglecting turbulent diffusion in open core–type CFRs is a poor assumption that leads to an underestimation of the reduction of the delayed neutron fraction. Additionally, it is seen that exclusion of secondary heat transfer loops in models leads to underestimation of transient peaks and troughs.

Keywords:

• Circulating fuel reactors
• fluid
• kinetics
• precursor
• molten salt reactor

Acknowledgments

This material is based upon work supported under a U.S. Department of Energy, Office of Nuclear Energy, Integrated University Program Graduate Fellowship (D. W). This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC0500OR22725 with the U.S. Department of Energy (J. J. P). The authors would also like to thank Manuele Aufiero, Nicholas Brown, Carlo Fiorina, Max Fratoni, Jiří Křepel, Kelly Rowland, and Matteo Zanetti for helpful conversations, clarifications, and materials. Last, the authors would like to acknowledge the constructive and insightful feedback provided by the anonymous reviewers of this manuscript, which significantly improved its overall quality.

Notes

^a All uses of the superscripted and subscripted in this paper denote belonging to DNP group .

^b In Table III, “Slug” refers to a uniform velocity profile across the reactor core. The other flow regimes seen in Table III are explained in Figs. 20 and 21. Table III shows the reactivity change in a simulated MSRE corresponding to different fluid fuel flow patterns. The reactivity change is given both overall and broken down into contributions from each DNP group.

^c In Ref. 9, the term “slug flow” is used to indicate a uniform fluid velocity profile, not a liquid-vapor mixture with large pockets of vapor separated by “slugs” of liquid as the term is commonly used to mean. For clarity, the less-ambiguous term “uniform” is used in this paper when referring to fluid velocity profiles termed “slug flow” in the aforementioned work.

^d See the Appendix for an explanation of Table IV as well as Tables A.1 through A.5 for more computational tools and more detailed information.

^e See the Appendix for an explanation of Table V as well as Tables A.1 through A.5 for more computational tools and more detailed information.

^f See the Appendix for an explanation of Table VI as well as Tables A.1 through A.5 for more computational tools and more detailed information.

^g See the Appendix for an explanation of Table VIII as well as Tables A.1 through A.5 for more computational tools and more detailed information.