Today, there are 94 nuclear reactors operating in the US, greater than in some other country on this planet, and these units collectively provide nearly 20 percent of the nation’s electricity. That could be a major accomplishment, based on Dean Price, but he believes that our country needs rather more out of nuclear energy, especially at a moment when alternatives to fossil fuel-based power plants are desperately being sought. He became a nuclear engineer for this very reason — to ensure that that nuclear technology is as much as the duty of delivering on this time of considerable need.
“Nuclear energy has been an incredible a part of our nation’s energy infrastructure for the past 60 years, and the number of people that maintain that infrastructure is incredibly small,” says Price, an MIT assistant professor within the Department of Nuclear Science and Engineering (NSE), in addition to the Atlantic Richfield Profession Development Professor in Energy Studies. “By becoming a nuclear engineer, you change into one among a select number of individuals liable for carbon-free energy generation in the US.”
That was a mission he was desperate to participate in, and the goals he set for himself were removed from modest: He desired to help design and usher in a brand new class of nuclear reactors, constructing on the protection, economics, and reliability of the present nuclear fleet.
Price has never wavered from this objective, and he’s only found encouragement along the best way. The nuclear engineering community, he says, “is small, close-knit, and really welcoming. When you get into it, most individuals are usually not inclined to do anything.”
Illuminating the relationships between physical processes
In his first research project as an undergraduate on the University of Illinois Urbana at Champaign, Price studied the protection of the steel and concrete casks used to store spent reactor fuel rods after they’ve cooled off in tanks of water, typically for several years. His evaluation indicated that this storage method was quite secure, although the query as to what should ultimately be done with these fuel casks, by way of long-term disposal, stays open on this country.
After starting graduate studies on the University of Michigan in 2020, Price took up a unique line of research that he’s still engaged in today. That area of study, called multiphysics modeling, involves taking a look at various physical processes occurring within the core of a nuclear reactor to see how they interact — an alternative choice to studying these processes one by one.
One key process, neutronics, concerns how neutrons buzz around within the reactor core causing nuclear fission, which is what generates the ability. A second process, called thermal hydraulics, involves cooling the reactor to extract the warmth generated by neutrons. A multiphysics simulation, analyzing how these two processes interact, could show how the warmth carried away because the reactor produces power affects the behavior of neutrons, because the warmer the fuel is, the less likely it’s to cause fission.
“If you happen to ever want to alter your power level, or do anything with the reactor, the temperature of the fuel is a critical input that you might want to know,” says Price. “Multiphysics modeling allows us to correlate the fission neutronics processes with a thermal property, temperature. That, in turn, may help us predict how the reactor will behave under different conditions.”
Multiphysics modeling for light water reactors, that are those operating today with capacities on the order of 1,000 megawatts, are pretty much established, Prices says. But methods for modeling advanced reactors — small modular reactors (SMRs with capacities starting from around 20 to 300 MW) and microreactors (rated at 1 to twenty MW) — are far less advanced. Only a really small variety of these reactors are operating today, but Price is focusing his efforts on them due to their potential to provide power more cheaply and more safely, together with their greater flexibility in power and size.
Although multiphysics simulations have supplied the nuclear community with a wealth of data, they will require supercomputers to resolve, or find approximate solutions to, coupled and very difficult nonlinear equations. Within the hopes of greatly reducing the computational burden, Price is actively exploring artificial intelligence approaches that might provide similar answers while bypassing those burdensome equations altogether. That has been a central theme of his research agenda since he joined the MIT faculty in September 2025.
An important role for artificial intelligence
What artificial intelligence and machine-learning methods, particularly, are good at is finding patterns concealed inside data, reminiscent of correlations between variables critical to the functioning of a nuclear plant. For instance, Price says, “when you tell me the ability level of your reactor, it [AI] could let you know what the fuel temperature is and even let you know the third-dimensional temperature distribution in your core.” And if this could be kept away from solving any complicated differential equations, computational costs may very well be greatly reduced.
Price is investigating several applications where AI could also be especially useful, reminiscent of helping with the design of novel sorts of reactors. “We could then depend on the protection frameworks developed over the past 50 years to perform a security evaluation of the proposed design,” he says. “In this fashion, AI is not going to be directly interfacing with anything that’s safety-critical.” As he sees it, AI’s role could be to enhance established procedures, somewhat than replacing them, helping to fill in existing gaps in knowledge.
When a machine-learning model is given a sufficient amount of information to learn from, it may well help us higher understand the connection between key physical processes — again without having to resolve nonlinear differential equations.
“By really pinning down those relationships, we are able to make higher design decisions within the early stages,” Price says. “And when that technology is developed and deployed, AI may help us make more intelligent control decisions that can enable us to operate our reactors in a safer and more economical way.”
Giving back to the community that nurtured him
Simply put, one among his chief goals is to bring the advantages of AI to the nuclear industry, and he views the chances as vast and largely untapped. Price also believes that he’s well-positioned as a professor at MIT to bring us closer to the nuclear future that he envisions. As he sees it, he’s working not only to develop the following generation of reactors, but additionally to assist prepare the following generation of leaders in the sphere.
Price became acquainted with some prospective members of that “next generation” in a design course he co-taught last fall with Curtis Smith, the KEPCO Professor of the Practice of Nuclear Science and Engineering. For Price, that introduction lasted just just a few months, nevertheless it was long enough for him to find that MIT students are exceptionally motivated, hard-working, and capable. Not surprisingly, those occur to be the identical qualities he’s hoping to seek out in the scholars that join his research team.
Price vividly recalls the support he received when taking his first, tentative steps on this field. Now that he’s moved up the ranks from undergraduate to professor, and purchased a considerable body of data along the best way, he wants his students “to experience that very same feeling that I had upon entering the sphere.” Beyond his specific goals for improving the design and operation of nuclear reactors, Price says, “I hope to perpetuate the identical fun and healthy environment that made me love nuclear engineering in the primary place.”
