Braden Goddard, Ph.D., assistant professor in the Department of Mechanical and Nuclear Engineering, has received a grant from the U.S. Department of Energy’s Nuclear Energy University Program (NEUP) to create a database for use in nuclear material control of pebble bed reactors (PBR).
Advances in material science and technology have revitalized the nuclear energy industry, allowing for the design and construction of advanced nuclear reactors. New high-temperature materials developed by researchers allow ideas from as early as 1970, like pebble bed reactors, to be re-explored and make nuclear power more efficient and sustainable.
Pebble bed reactors are one of many ideas from as early as 1970 that researchers are once again exploring to make nuclear power more efficient and sustainable now that science has developed new high-temperature materials.
“Imagine a gumball machine,” said Goddard, “A pebble bed reactor functions similarly. The pebbles are the gumballs, which are fed into a reservoir. As they make their way through the reactor, heat generated from the radiation is removed by a gas which then spins an electrical turbine to generate electricity. The pebbles then exit from the bottom of the reservoir and those that can be reused are returned to the top of the reservoir.”
Each pebble contains thousands of microscopic uranium particles encased in silicon-carbide cladding. As the pebble passes through the PBR, the path it follows affects how much fissioning occurs within the uranium. This means pebbles deplete at different rates based on how they travel through the reactor.
Goddard’s database seeks to characterize the state of a pebble after it leaves the PBR by determining precisely how much plutonium and uranium remains in the pebble. This informs PBR operators if the pebble can be reused or if it needs to be sent off as waste. Better characterizing these pebbles improves the sustainability and security of PBRs while reducing the amount of waste generated.
Measuring gamma radiation from the radioactive isotope cesium-137 created from the fission of uranium is the traditional method of determining how much nuclear fuel is still viable. However, this system does not work for PBRs because the correlation between the uranium fuel and the gamma radiation it emits is not consistent between pebbles. To remedy this, Goddard will measure both gamma and neutron radiation emitted by all radioactive isotopes in the pebble, which varies depending on the route the pebble takes through the reactor. Partners like Brookhaven National Laboratory and similar institutions within the United States will assist in the research by applying machine learning techniques to the gamma and neutron radiation signature.
“Nuclear reactor operators have instruments that tell them what’s going on inside the reactor, but it’s not the same as knowing how much uranium mass you have in fuel going into or coming out of the reactor,” said Goddard.
Goddard and his colleague, Zeyun Wu, Ph.D., will use computer modeling to run countless simulations and map every possible course a pebble can take through a PBR. The resulting catalog of data will allow PBR operators to characterize the state of any pebble leaving the PBR and assess if it can be reused or if it is ready to be stored at a nuclear waste facility. The catalog also serves as a material inventory, allowing nuclear facilities to better track waste material.