UMass Lowell and MIT back fission and fusion future for Massachusetts

Massachusetts Gov. Maura Healey wants to accelerate the state's leadership in both fission and fusion, and earlier this month asked the University of Massachusetts-Lowell to develop road maps to support research, manufacturing, and deployment of advanced nuclear and fusion energy in the state to "affordably, reliably, and sustainably" meet growing electricity demand in New England.

Massachusetts is currently home to two research reactors, at UMass Lowell and the Massachusetts Institute of Technology. It's also home to MIT's Plasma Science and Fusion Center and Commonwealth Fusion Systems, which spun out of MIT in 2018 and is now developing a compact tokamak magnetic confinement fusion power plant at its headquarters in Devens, Mass., for first deployment in Virginia. MIT continues to support CFS, most recently by developing a machine learning model to manage plasma disruptions in tokamaks.

Roadmap specifics: At UMass Lowell, Sukesh Aghara-a professor of nuclear engineering, associate dean for research of the Francis College of Engineering, and a former chair of the Nuclear Engineering Department Heads Organization-will lead the development of the road maps over the next four months.

UMass Lowell plans to engage stakeholders from across the UMass system, industry, government, and communities to "assess existing capabilities, identify key gaps, and define opportunities for Massachusetts to lead in shaping the state's and region's advanced nuclear and fusion energy ecosystems." The road maps will outline steps to leverage Massachusetts's existing innovation ecosystem, scale workforce development programs to support long-term industry growth, develop strategies for inclusive community engagement, and coordinate planning efforts with other New England states. The road maps will not consider specific sites or restarting decommissioned facilities but will serve as a foundational document to inform future legislative, regulatory, and investment decisions.

In a recent invited contribution to Nuclear News, Aghara wrote that "in an era when affordable, clean energy is as much an economic imperative as it is an environmental one, the Commonwealth of Massachusetts has an opportunity to lead not just through legislation but through partnership-between state leadership and its world-class universities."

New MIT fusion research: On October 7, MIT announced that research at MIT's PSFC, supported in part by CFS, has led to a new model of plasma dynamics that could improve the reliability of magnetic confinement fusion power plants during critical moments of rampdown after a plasma becomes unstable.

An unstable plasma can potentially damage plasma-facing walls inside the machine, and paradoxically, ramping down the plasma to avoid damage can cause a sudden disruption that destabilize the plasma and lead to damage requiring time-consuming repair.

MIT's development of a method to predict how plasma will behave during a rampdown was described in an open-access Nature Communications paper published this week. According to MIT, the team combined machine learning tools with a physics-based model of plasma dynamics to simulate a plasma's behavior, training and testing the model on plasma data from an experimental tokamak in Switzerland. They found that the method quickly "achieved a high level of accuracy using a relatively small amount of data."

Typical machine learning applications rely on a neural network that gradually fine-tunes a model by detecting anomalies in a large set of data. The researchers saved time by applying a neural network to an existing physics-based simulation of plasma dynamics. Using a combination of machine learning and a physics-based plasma simulation, the team could get results with a smaller data set: "only a couple hundred pulses at low performance, and a small handful of pulses at high performance."

The data they used for the new study came from the TCV, the "variable configuration tokamak" operated by the Swiss Plasma Center at the Swiss Federal Institute of Technology Lausanne.

"For fusion to be a useful energy source it's going to have to be reliable," said lead author Allen Wang, a graduate student in aeronautics and astronautics and a member of the Disruption Group at MIT's PSFC. "To be reliable, we need to get good at managing our plasmas."

Management comes into play with an algorithm the researchers developed to translate the model's predictions into a set of "trajectories," or instructions for a tokamak controller to adjust the magnets or temperature, for example, to maintain the plasma's stability. By implementing the algorithm on several TCV runs, the researchers found that it "produced trajectories that safely ramped down a plasma pulse, in some cases faster and without disruptions compared to runs without the new method."