Better helium reporting to improve fission and fusion materials modeling
Helium generation predictions vary by as much as 200%, a new standardized reporting method can help move the field forward.
Key Takeaways
- Helium generated as a byproduct of nuclear fission and fusion has been treated as a material constant, but generation rates vary by as much as 200% depending on the simulation, according to a University of Michigan Engineering and Oak Ridge National Laboratory study.
- A systematic series of simulations with slightly varying material, reactor and model properties found each variable strongly influenced helium generation predictions.
- The research team proposes a standardized reporting method for helium generation rates to improve research across the field and enable better advanced fission and fusion energy systems.
Standardizing calculations of the helium byproducts generated in advanced fission and fusion energy system materials can increase reactor safety and longevity, according to a study led by University of Michigan Engineering with collaborators at Oak Ridge National Laboratory and its management contractor UT-Battelle. This research was primarily funded by the Department of Energy.
Through a series of simulations, the researchers found that modeling assumptions and key alloy elements—like carbon, nitrogen and nickel—significantly influence helium generation predictions. If left unaddressed, excess helium in real-world reactors could lead to faster component failure as materials swell and become brittle.
“If used, our reporting methods will improve the experimental and modeling fidelity of the nuclear materials databases being generated both domestically and internationally, driving the rapid deployment of advanced nuclear,” said Kevin Field, a professor of nuclear engineering and radiological sciences at U-M and corresponding author of the study published in the Journal of Physics: Energy.
Calculating helium generation
Both fission and fusion reactors produce helium through a process called neutron transmutation. The reactions spit off high-energy neutrons that collide with the surrounding metal vessel. The metal atoms capture the neutron and transform it into a new element, releasing helium gas as a byproduct.
Helium generation rates are represented as atomic parts per million per displacement per atom, or He/dpa. Essentially this metric estimates how much helium would be produced per atom knocked out of its spot on the metal’s crystal lattice by radiation over a specific time period.
While an incorrect prediction of the helium generation rate could mean frequent repairs on an expensive reactor, previous studies have treated it as a fixed material constant, ignoring possible uncertainties.
“We developed this study by revisiting old calculations on the helium generation rate in some materials of interest, which led us down a rabbit hole into how many uncertainties were present and must be accounted for in order to do these calculations correctly,” said Alexander Birmingham, a recent graduate of U-M majoring in physics and lead author of the study.
A systematic test of simulations
The research team developed a custom Python-based program called F-SCATTER. The program automates thousands of simulations using FISPACT-II, a multiphysics software for advanced nuclear simulation.
Each simulation fluctuates the variables—alloy composition (within accepted manufacturing standards), neutron energies, computational methodologies and nuclear data library—within set boundaries to determine their influence on helium predictions.
Computation methodologies refer to three different ways to extract helium generation from FISPACT-II data. 1) Rates method: Calculate the ratio of helium and damage rates at each timestep. 2) Time-rates method: Add up all helium rates and damage rates over the time period and then find the ratio. 3) Totals method: Use the helium value provided by the software at each timestep divided by the summed damage rates.
Helium generation predictions vary widely
When put to the test on four advanced metal alloys, simulations revealed that helium generation rates depend strongly on each variable tested. While neutron energies were expected to sway results, the choice of nuclear data library generated helium generation prediction differences often as high as 231%, while sometimes as extreme as 859%.
Alloy composition was another major source of uncertainty with helium generation predictions varying widely, with errors as high as 98% in one case. Often only a single element present in the alloy, like nitrogen or nickel, impacts predicted rates as they release more helium in higher probability reactions. This finding has implications for the industry, particularly where and how they get their alloys to build fusion and fission energy systems as different metal producers have different composition control.
“We were really surprised by how much the nuclear data library and calculation method impacted the final answer. It’s so significant that it’s like forgetting to add salt in a savory dish, resulting in a sweet final dish,” said Field.
Of the computation methods investigated, the time-rates method was the most reliable, achieving a consistent calculation across different neutron energies. The totals method tended to underestimate helium while the rates method missed transmutation rate changes over time.
A standardized method for helium generation predictions
The researchers propose a standardized method for determining and reporting gaseous transmutation rates for current and future nuclear power.
Best practices include reporting the calculated range of expected helium production rather than a single point value, specifying the unique heat designation and trace elements of the alloy and documenting both the reactor’s raw and digitally upscaled neutron spectra. Together, these standards account for the material impurities and modeling uncertainties that come with real-world data.
“Helium production has a strong influence on high temperature embrittlement and dimensional stability for structural materials in both fusion and fission systems. As industries move to assess and deploy their technologies, having a standard method of analysis with a sense of uncertainty is needed for comparisons across materials systems and environments,” said Stephen Taller, an Alvin M. Weinberg Fellow and R&D Staff Scientist at Oak Ridge National Laboratory.
This research was supported by the Department of Energy Office of Nuclear Energy’s Nuclear Energy University Programs (DE-NE0009419) and under a University Nuclear Leadership Program Graduate Fellowship. Taller’s contributions were supported by the Department of Energy Office of Nuclear Energy, Advanced Materials and Manufacturing Technologies (AMMT) and Advanced Fuels Campaign (AFC) programs (DE-AC05-00OR22725) with UT-Battelle, LLC.