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Conference Spotlight
2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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NN Asks: What did you learn from ANS’s Nuclear 101?
Mike Harkin
When ANS first announced its new Nuclear 101 certificate course, I was excited. This felt like a course tailor-made for me, a transplant into the commercial nuclear world. I enrolled for the inaugural session held in November 2024, knowing it was going to be hard (this is nuclear power, of course)—but I had been working on ramping up my knowledge base for the past year, through both my employer and at a local college.
The course was a fast-and-furious roller-coaster ride through all the key components of the nuclear power industry, in one highly challenging week. In fact, the challenges the students experienced caught even the instructors by surprise. Thankfully, the shared intellectual stretch we students all felt helped us band together to push through to the end.
We were all impressed with the quality of the instructors, who are some of the top experts in the field. We appreciated not only their knowledge base but their support whenever someone struggled to understand a concept.
Daniel F. Gill, Yousry Y. Azmy
Nuclear Science and Engineering | Volume 167 | Number 2 | February 2011 | Pages 141-153
Technical Paper | doi.org/10.13182/NSE09-98
Articles are hosted by Taylor and Francis Online.
We present an approach to the k-eigenvalue problem in multigroup diffusion theory based on a nonlinear treatment of the generalized eigenvalue problem. A nonlinear function is posed whose roots are equal to solutions of the k-eigenvalue problem; a Newton-Krylov method is used to find these roots. The Jacobian-vector product is found exactly or by using the Jacobian-free Newton-Krylov (JFNK) approximation. Several preconditioners for the Krylov iteration are developed. These preconditioners are based on simple approximations to the Jacobian, with one special instance being the use of power iteration as a preconditioner. Using power iteration as a preconditioner allows for the Newton-Krylov approach to heavily leverage existing power method implementations in production codes. When applied as a left preconditioner, any existing power iteration can be used to form the kernel of a JFNK solution to the k-eigenvalue problem. Numerical results generated for a suite of two-dimensional reactor benchmarks show the feasibility and computational benefits of the Newton formulation as well as examine some of the numerical difficulties potentially encountered with Newton-Krylov methods. The performance of the method is also seen to be relatively insensitive to the dominance ratio for a one-dimensional slab problem.