NE Associate Professor Nick Brown will lead a new study funded by the Department of Energy Office of Fusion Energy Science aimed at supporting the optimization and design of fusion engineering. The grant, which was awarded $1,080,000, is named “Development of integrated neutronics and thermal analysis capabilities to support design and optimization of fusion engineering demonstration facility systems and blanket.”
This research will advance design optimization of fusion engineering demonstration facility blanket during the research and development phase for a demonstration plant.
“This work will help advance the readiness of fusion systems for an eventual fusion power plant,” said Brown. “We are very excited for this opportunity.”
Engineering demonstration facilities are essentially test reactors designed to help increase the technology readiness level of a reactor design. Additionally, the blanket is the key nuclear component that actually extracts the power at high temperatures and achieves tritium self-sufficiency. Among other things, the neutronics, or transport of neutrons, also determines the applicable heating rates.
The team hopes to establish evaluation tools for coupled neutronics, thermal-hydraulics, and tritium transport design and analysis of blanket systems. All these capabilities are prerequisite for further design optimization studies of a blanket fuel cycle system.
“This award is, in fact, a continuation of a successful equal-partnership initiated between myself and Professor Brown that secured $512K in research funding via ORNL from mid-2020 through mid-2021 to promote the integration of fusion neutronics and thermal hydraulics for blanket design optimization,” said Maldonado. “We expect this project to support four to five students through their MS and/or PhD degrees during the next three years.”
One of the needs in the blanket and fuel cycle area is integrated simulation capability for neutron transport and thermal-hydraulics of the fusion system blanket. This can provide global information under normal operation and accident scenarios for detailed analysis.
The research approach will include a focus on robust Sensitivity and Uncertainty analysis. Uncertainties in design parameters will illuminate the relative importance of these parameters, as well as the quantification of their uncertainties.