Scientists in the United States have come up with a physics-based algorithm that could one day make it possible for nuclear microreactors to adjust the power output based on need.

The study was funded by the US Department of Energy Office of Nuclear Energy and was led by the University of Michigan.

Nuclear microreactors would be able to generate up to 20 megawatts of thermal energy for heat or electricity. Their small size could make them an efficient energy source in remote locations, military installations, or even ships.

Further, they can even be integrated into electrical grids, where they would be able to provide a stable energy flow. However, there would be a need for them to adjust the power output to match the grid’s shifting demand.

While in large reactors, there are human operatives who make the adjustments, it could get difficult or infeasible to deploy personnel in remote locations for a nuclear microreactor.

Autonomous output adjustment for nuclear microreactors

The University of Michigan-led team focused the study on High-Temperature Gas-Cooled Reactors (HTGR), which can be scaled from microreactor to large modules. The study was based on the Holos-Quad (Gen 2+) model, a HTGR-type microreactor design.

The research team leveraged model predictive control (MPC), a method that predicts future behavior to optimize control over a defined period of time under certain constraints, according to a press release by the university.

They developed an MPC controller that optimized the rotation of control drums that surround the microreactor’s central core, that decrease power when facing inwards and increase power when facing outwards.

The team also integrated PROTEUS – a simulation toolset for high-fidelity reactor physics analysis – to ensure the model was accurately representing the nuclear microreactor’s operation.

Testing the algorithm

According to the release, when asked to ramp the power up or down at 20 percent per minute, the control algorithm stayed within 0.234 percent of the target.

Moreover, it was able to do this without the help of artificial intelligence (AI), “meaning everything about the automated control for load follow operation is grounded in physics and mathematics and readily explainable—an essential feature for passing regulatory review.”

“Many startup and legacy companies in the U.S. are pushing towards near-term and broad deployment of nuclear microreactors, and our work establishes a clear avenue to achieve that in an economically viable way,” said Brendan Kochunas, an associate professor of nuclear engineering and radiological sciences at U-M and corresponding author of the study. 

He went on to add that the method can help vendors design reactors with autonomous control systems that are safer and more secure.

There are several nuclear microreactor projects being pursued by different companies in the US alone. The US Air Force had recently awarded a Direct to Phase II (D2P2) innovation research contract to Nano Nuclear Energy to explore the feasibility of deploying its Kronos micro modular nuclear reactor at Joint Base Anacostia-Bolling (JBAB) in Washington, D.C.

Washington-based Last Energy had also decided to build 30 nuclear microreactors in Haskell County, Texas. Therefore, the physics-based method could prove vital to these operations in the long run, once it is validated.

Further sensitivity tests conducted by the researchers confirmed that the MPC controller worked for a wide range of model inputs, validating feasibility for autonomous control.

“The control algorithm’s success and integration with high-fidelity simulation tools demonstrates that we can now design nuclear reactors and their instrumentation and control systems together from the ground up, rather than trying to back fit the I&C (instrumentation and control) systems to a mostly complete reactor design,” Kochunas said. 

The study has been published in the journal Progress in Nuclear Energy.