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2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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Researchers use one-of-a-kind expertise and capabilities to test fuels of tomorrow
At the Idaho National Laboratory Hot Fuel Examination Facility, containment box operator Jake Maupin moves a manipulator arm into position around a pencil-thin nuclear fuel rod. He is preparing for a procedure that he and his colleagues have practiced repeatedly in anticipation of this moment in the hot cell.
Thomas A. Brunner, Terry S. Haut, Paul F. Nowak
Nuclear Science and Engineering | Volume 194 | Number 11 | November 2020 | Pages 939-951
Technical Paper | doi.org/10.1080/00295639.2020.1747262
Articles are hosted by Taylor and Francis Online.
We apply a nonlinearly preconditioned, quasi-Newton framework to accelerate the numerical solution of the thermal radiative transfer (TRT) equations. This framework was inspired by the unpublished method that has existed for years in Teton, Lawrence Livermore National Laboratory’s deterministic TRT code. In this paper, we cast this iteration scheme within a formal nonlinear preconditioning framework and compare its performance against other iteration schemes in the framework. With proper choices of iteration controls for the various levels of the solver, we can recover the standard linearized one-step method, a full nonlinear Newton scheme, as well as the method in Teton.
In brief, the nonlinear preconditioning TRT scheme formally eliminates the material temperature equation from the nonlinear system in a nonlinear analog of a Schur complement. This nonlinear elimination step involves solving a decoupled nonlinear equation for each spatial degree of freedom and is therefore inexpensive. By applying a quasi-Newton iteration scheme on the new system, we obtain a three-level iteration scheme that is at least as efficient as commonly used TRT schemes. The new method allows full convergence to the nonlinear backward Euler time-discretized system, increasing accuracy and robustness, while using a similar number of linear iterations as the more common linearized one-step methods Eq. (4).