What if there have been a strategy to solve one of the vital significant obstacles to using nuclear energy — the disposal of high-level nuclear waste (HLW)? Dauren Sarsenbayev, a third-year doctoral student on the MIT Department of Nuclear Science and Engineering (NSE), is addressing the challenge as a part of his research.
Sarsenbayev focuses on one in all the first problems related to HLW: decay heat released by radioactive waste. The essential premise of his solution is to extract the warmth from spent fuel, which concurrently takes care of two objectives: gaining more energy from an existing carbon-free resource while decreasing the challenges related to storage and handling of HLW. “The worth of carbon-free energy continues to rise annually, and we wish to extract as much of it as possible,” Sarsenbayev explains.
While the protected management and disposal of HLW has seen significant progress, there may be more creative ways to administer or make the most of the waste. Such a move can be especially essential for the general public’s acceptance of nuclear energy. “We’re reframing the issue of nuclear waste, transforming it from a liability to an energy source,” Sarsenbayev says.
The nuances of nuclear
Sarsenbayev needed to do a little bit of reframing himself in how he perceived nuclear energy. Growing up in Almaty, the biggest city in Kazakhstan, the collective trauma of Soviet nuclear testing loomed large over the general public consciousness. Not only does the country, once an element of the Soviet Union, carry the scars of nuclear weapon testing, Kazakhstan is the world’s largest producer of uranium. It’s hard to flee the collective psyche of such a legacy.
At the identical time, Sarsenbayev saw his native Almaty choking under heavy smog every winter, as a result of the burning of fossil fuels for warmth. Determined to do his part to speed up the strategy of decarbonization, Sarsenbayev gravitated to undergraduate studies in environmental engineering at Kazakh-German University. It was during this time that Sarsenbayev realized practically every energy source, even the promising renewable ones, got here with challenges, and decided nuclear was the strategy to go for its reliable, low-carbon power. “I used to be exposed to air pollution from childhood; the horizon can be just black. The largest incentive for me with nuclear power was that so long as we did it properly, people could breathe cleaner air,” Sarsenbayev says.
Studying transport of radionuclides
A part of “doing nuclear properly” involves studying — and reliably predicting — the long-term behavior of radionuclides in geological repositories.
Sarsenbayev discovered an interest in studying nuclear waste management during an internship at Lawrence Berkeley National Laboratory as a junior undergraduate student.
While at Berkeley, Sarsenbayev focused on modeling the transport of radionuclides from the nuclear waste repository’s barrier system to the encircling host rock. He discovered find out how to use the tools of the trade to predict long-term behavior. “As an undergrad, I used to be really fascinated by how far in the long run something might be predicted. It’s form of like foreseeing what future generations will encounter,” Sarsenbayev says.
The timing of the Berkeley internship was fortuitous. It was on the laboratory that he worked with Haruko Murakami Wainwright, who was herself getting began at MIT NSE. (Wainwright is the Mitsui Profession Development Professor in Contemporary Technology, and an assistant professor of NSE and of civil and environmental engineering).
Seeking to pursue graduate studies in the sector of nuclear waste management, Sarsenbayev followed Wainwright to MIT, where he has further researched the modeling of radionuclide transport. He’s the primary writer on a paper that details mechanisms to extend the robustness of models describing the transport of radionuclides. The work captures the complexity of interactions between engineered barrier components, including cement-based materials and clay barriers, the standard medium proposed for the storage and disposal of spent nuclear fuel.
Sarsenbayev is pleased with the outcomes of the model’s prediction, which closely mirrors experiments conducted on the Mont Terri research site in Switzerland, famous for studies within the interactions between cement and clay. “I used to be fortunate to work with Doctor Carl Steefel and Professor Christophe Tournassat, leading experts in computational geochemistry,” he says.
Real-life transport mechanisms involve many physical and chemical processes, the complexities of which increase the scale of the computational model dramatically. Reactive transport modeling — which mixes the simulation of fluid flow, chemical reactions, and the transport of gear through subsurface media — has evolved significantly over the past few a long time. Nevertheless, running accurate simulations comes with trade-offs: The software can require days to weeks of computing time on high-performance clusters running in parallel.
To reach at results faster by saving on computing time, Sarsenbayev is developing a framework that integrates AI-based “surrogate models,” which train on simulated data and approximate the physical systems. The AI algorithms make predictions of radionuclide behavior faster and fewer computationally intensive than the standard equivalent.
Doctoral research focus
Sarsenbayev is using his modeling expertise in his primary doctoral work as well — in evaluating the potential of spent nuclear fuel as an anthropogenic geothermal energy source. “Actually, geothermal heat is essentially as a result of the natural decay of radioisotopes in Earth’s crust, so using decay heat from spent fuel is conceptually similar,” he says. A canister of nuclear waste can generate, under conservative assumptions, the energy equivalent of 1,000 square meters (a bit of under 1 / 4 of an acre) of solar panels.
Since the potential for warmth from a canister is important — a typical one (depending on how long it was cooled within the spent fuel pool) has a temperature of around 150 degrees Celsius — but not enormous, extracting heat from this source makes use of a process called a binary cycle system. In such a system, heat is extracted not directly: the canister warms a closed water loop, which in turn transfers that heat to a secondary low-boiling-point fluid that powers the turbine.
Sarsenbayev’s work develops a conceptual model of a binary-cycle geothermal system powered by heat from high-level radioactive waste. Early modeling results have been published and look promising. While the potential for such energy extraction is on the proof-of-concept stage in modeling, Sarsenbayev is hopeful that it should find success when translated to practice. “Converting a liability into an energy source is what we wish, and this solution delivers,” he says.
Despite work being all-consuming — “I’m almost obsessive about and love my work” — Sarsenbayev finds time to jot down reflective poetry in each Kazakh, his native language, and Russian, which he learned growing up. He’s also enamored by astrophotography, taking pictures of celestial bodies. Finding the proper night sky could be a challenge, however the canyons near his home in Almaty are an especially good fit. He goes on photography sessions at any time when he visits home for the vacations, and his love for Almaty shines through. “Almaty means ‘the place where apples originated.’ This a part of Central Asia may be very beautiful; although we have now environmental pollution, it is a place with a wealthy history,” Sarsenbayev says.
Sarsenbayev is very keen on finding ways to speak each the humanities and sciences to future generations. “Obviously, you have got to be technically rigorous and get the modeling right, but you furthermore may have to know and convey the broader picture of why you’re doing the work, what the tip goal is,” he says. Through that lens, the impact of Sarsenbayev’s doctoral work is important. The tip goal? Removing the bottleneck for nuclear energy adoption by producing carbon-free power and ensuring the protected disposal of radioactive waste.
