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The human factor in licensing and operating the next generation of nuclear plants
As human factors specialists working at the intersection of human performance and nuclear operations, we are witnessing one of the nuclear sector’s most significant transitions in decades. The emergence of small modular reactors, microreactors, and other advanced designs is reshaping the industry’s landscape. Digital instrumentation and controls, passive safety systems, and increased automation are creating opportunities for greater safety margins and more flexible operation. These same features also fundamentally redefine what it means to “operate” a nuclear plant. Interactions among human roles, automation, and passive systems shape how people maintain awareness, exercise judgment, and intervene when necessary. These developments affect both operational realities and the regulatory foundations on which nuclear safety is built.
Scott A. Comes, Paul J. Turinsky
Nuclear Technology | Volume 83 | Number 1 | October 1988 | Pages 31-48
Technical Paper | Fuel Cycle | doi.org/10.13182/NT88-A34173
Articles are hosted by Taylor and Francis Online.
A methodology has been developed for determining the family of near-optimum fuel management schemes that minimize the levelized fuel cycle costs of a light water reactor over a multicycle planning horizon. Feed batch enrichments and sizes, burned batches to reinsert, and burnable poison loadings are determined for each cycle in the planning horizon. Flexibility in the methodology includes the capability to assess the economic benefits of various partially burned batch reload strategies as well as the effects of using split feed enrichments and enrichment palettes. Constraint limitations are imposed on feed enrichments, discharge burnups, moderator temperature coefficient, and cycle energy requirements. The methodology, incorporated into a code named OCEON, uses a zero-dimensional reactor physics model and a rapid fuel cycle cost routine to select minimum cost cycling schemes that satisfy all constraints. These candidate schemes are then examined with a two-dimensional nodal reactor physics model to more accurately calculate feed enrichments, batch burnups, and fuel cycle costs. The use of Monte Carlo integer programming to direct the optimization process allows for the determination of a family of low cost schemes from which the fuel manager can select the strategy that best fits his needs.