Equilibrium Core Optimization of Composite Moderators in Pebble Bed High-Temperature Gas-Cooled Microreactors

As both industry and government move toward meeting their decarbonization goals, nuclear power is increasingly being considered due to its legacy of providing clean and reliable power. Pebble bed (PB) high-temperature gas-cooled reactors (HTGRs) are a generation-IV reactor design being considered because of their past operational experience, intrinsic safety features, and online refueling capabilities. PB-HTGRs are conventionally moderated with graphite, but in the high-temperature and high-fluence environment of PB-HTGRs, graphite undergoes several undesirable property changes that limit the lifetime of the graphite components in the reactor.

Composite moderators have been proposed as an alternative to graphite as a moderating material in HTGRs because of their desirable properties in the high-temperature and high-fluence environment of HTGRs. Two-phase composite moderators are comprised of a highly moderating phase that is entrained in a radiation-stable matrix phase.

This work seeks to optimize a micro-modular PB-HTGR design for the use of the composite moderator MgO-ZrH, through adjustments to the core height. The optimization makes use of the novel A-ZEM (axial zone equilibrium modeling) method. The best-performing PB-HTGR had a core height of 285.5 cm, achieving a discharge burnup of 131.460 GWd/tonne heavy metal, an improvement of 24.34% compared to the reference graphite moderated model and 16.51% compared to a prismatic HTGR moderated with MgO-ZrH.

An additional goal of this work was to determine the applicability of the linear reactivity model (LRM), a fuel management model, as a scoping tool for PB-HTGRs. Comparing the theoretical discharge burnup calculated by the LRM to the equilibrium discharge burnup, differences did not exceed 10%. Therefore, it was concluded that the LRM can be an effective scoping tool for PB-HTGRs to allow for understanding the key equilibrium metric of discharge burnup without requiring the generation of an equilibrium model.