Hunter Belanger ’18, ’19G, Ph.D., assistant professor in Rensselaer Polytechnic Institute’s Department of Mechanical, Aerospace, and Nuclear Engineering (MANE), is one of four researchers nationwide to receive a Department of Energy Distinguished Early Career Award.

The five-year, $625,000 grant will fund Belanger’s research aimed at making nuclear power safer and more efficient, supporting state and national efforts to transition away from carbon-emitting energy sources. 

Belanger’s DOE-funded project will develop accurate computer models of something called neutron noise. Neutron noise occurs when the components within a nuclear reactor vibrate and stir up the neutrons in the reactor. These vibrations can disrupt the reactor’s power output. Perturbations can also cause damage, or they may signal that a repair is needed.

Currently, it’s impossible to pinpoint the source of neutron noise within a reactor because radiation would immediately destroy any sensors or electronics placed inside. Sensors outside reactors can pick up power fluctuations but can’t identify their cause. 

Instead, nuclear engineering researchers rely on computers to simulate what goes on inside a reactor. Belanger will use Monte Carlo simulations to digitally represent different reactor perturbations.

“Right now, when the sensors outside a reactor pick up a certain level of vibration, it’s like when the ‘check engine’ light comes on in your car. That light can indicate any number of issues, or there might not be an issue at all. However, with a nuclear reactor, which operates 24/7, 365 days a year, you can’t simply stop everything and check under the hood. This is why computer simulation is so useful,” Belanger said. 

In his project, Belanger will simulate several types of perturbations that can occur in a nuclear reactor. These include warped fuel rods, vibrations of the pressurized reactor vessel, and fluctuations in the temperature and density of the water that cools the reactor. 

Belanger explained that these simulations could be used to train machine learning tools to identify reactor issues that can cause the types of power fluctuations detected outside the nuclear reactor. 

In place of a vague “check engine” light, nuclear plant operators could have real-time data about potential problems with a reactor. With this precise information, nuclear power plants could run more efficiently because they would not need to reduce power output or shut down reactors for repairs unless necessary. 

Belanger said he is honored to receive the Distinguished Early Career Award from the DOE and credits faculty mentors at RPI for sparking his interest in nuclear engineering. 

“Though I was a physics major at RPI, the courses I took in the MANE department in reactor physics and neutron transport made me want to pursue a Ph.D. in nuclear engineering. I ended up studying in France, where about 70% of the country’s power comes from nuclear energy,” Belanger said. “I am now fortunate to be back at RPI in the MANE department, where I get to pursue my research and mentor the next generation of nuclear engineers.”