One Ph.D. student’s research is redefining radiation testing at the University of Utah’s TRIGA Reactor (UUTR)
Radiation hardness testing is used to evaluate how well materials—such as sensors, microchips, and other essential tech used in nuclear science—can withstand radiation without failing.
Testing a materials’ resilience to radiation helps us develop more advanced technologies to use in high-radiation environments, such as space missions, nuclear reactors, and defense systems. Unfortunately, simulating how radiation will affect materials requires very detailed, complex models of the reactor in which the testing will occur.
Joe Johnson, a Ph.D. student at the University of Utah, is changing that. His research is laying the groundwork for using smarter, faster simulation methods that still give accurate results.
The key lies in advanced modeling techniques and variance reduction methods. In a new study published in IEEE Transactions on Nuclear Science, Johnson presents a hybrid simulation method that significantly accelerates radiation hardness testing design—an important step toward enabling efficient and accurate neutron displacement damage (NDD) testing using the University of Utah TRIGA Reactor (UUTR). This development will allow researchers to run test designs much more quickly and efficiently, helping them get reliable answers without needing weeks of computer time.
With up to 100x faster modeling methods, Johnson’s work could position UUTR as a key site for collaborations and commercial interest in radiation testing at the University of Utah, further positioning the Utah Nuclear Engineering Program (UNEP) as a key contributor to the future of nuclear engineering.

Left: Stimulated Neutrons, low and high energy. Right: Speed Up Function, low and high energy. “A” and “B” indicate “Low” and “High” neutron energies from the UUTR. Left: Stimulated Neutrons, low and high energy. Right: Speed Up Function, low and high energy.


Fengze Yang, left, networking at the ITE Conference.

Shouzheng Pan, right, receiving the Best Paper Award.
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