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Nuclear Science and Engineering
Fusion Science and Technology
The consequences of closure: The local cost of shutting down a nuclear power plant
When on May 7, 2013, the Kewaunee nuclear power plant in rural Wisconsin was shut down, it took with it more than 600 full-time jobs and more than $70 million in lost wages, not including temporary employment from refueling and maintenance outages. Taking into account indirect business-to-business activity, the total economic impact of the closure of the single-unit pressurized water reactor was estimated to be more than $630 million to the surrounding three-county area.
Thomas A. Brunner, Terry S. Haut, Paul F. Nowak
Nuclear Science and Engineering | Volume 194 | Number 11 | November 2020 | Pages 939-951
Technical Paper | dx.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 This framework was inspired by the unpublished method that has existed for years in Teton, Lawrence Livermore National Laboratory’s deterministic TRT code.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).