“Reactors need to run at either higher power or use fuels longer to increase their performance,” said Karim Ahmed, an assistant professor in the Department of Nuclear Engineering. “But then, at these settings, the risk of wear and tear also increases. So, there is a pressing need to come up with better reactor designs, and a way to achieve this goal is by optimizing the materials used to build the nuclear reactors.”
A paper on the results of their work has been published in the journal Frontiers in Materials. Along with Ahmed, Abdurrahman Ozturk, a research assistant in the nuclear engineering department, was the lead author of the paper. Merve Gencturk, a graduate student in the nuclear engineering department, also contributed to the research.
The problem: When energetic radiation infiltrates a nuclear reactor’s structural materials, it can displace atoms from their locations, causing point defects, or force atoms to fill vacant spots, forming interstitial defects. What starts as tiny imperfections grow to form voids and dislocation loops, compromising the material’s mechanical properties over time.
While there is some understanding of the type of defects that occur in these materials upon radiation exposure, Ahmed said that it has taken a lot of work to model how radiation, along with other factors, such as the temperature of the reactor and the microstructure of the material, contribute to the formation defects and their growth.
“The challenge is the computational cost,” he said. “In the past, simulations have been limited to specific materials and for regions spanning a few microns across, but if the domain size is increased to even 10s of microns, the computational load drastically jumps.”
Too much compromise: In particular, the researchers said that to accommodate larger domain sizes, previous studies have compromised on the number of parameters within the simulation’s differential equations. However, an undesirable consequence of ignoring some parameters over others is an inaccurate description of the radiation damage.
To overcome these limitations, Ahmed and his team designed their simulation with all the parameters, making no assumptions on whether one of them was more pertinent than the other. The team used the resources provided by the Texas A&M High Performance Research Computing group to perform the computationally heavy tasks.
Upon running the simulation, the team’s analysis revealed that using all parameters in nonlinear combinations yields an accurate description of radiation damage. In particular, in addition to the material’s microstructure, the radiation condition within the reactor and the reactor design and temperature are also important in predicting the instability in materials due to radiation.
New findings: The researchers’ work also sheds light on why specialized nanomaterials are more tolerant to voids and dislocation loops. They found that instabilities are triggered only when the border enclosing clusters of co-oriented atomic crystals, or grain boundary, is above a critical size. So, nanomaterials with their extremely fine grain sizes suppress instabilities, thereby becoming more radiation tolerant.
“Although ours is a fundamental theoretical and modeling study, we think it will help the nuclear community to optimize materials for different types of nuclear energy applications, especially new materials for reactors that are safer, more efficient and economical,” Ahmed said. “This progress will eventually increase our clean, carbon-free energy contribution.”
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