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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.
Douglas E. Peplow
Nuclear Technology | Volume 174 | Number 2 | May 2011 | Pages 289-313
Technical Paper | Special Issue on the SCALE Nuclear Analysis Code System / Radiation Protection | doi.org/10.13182/NT174-289
Articles are hosted by Taylor and Francis Online.
Monte Carlo shielding analysis capabilities in SCALE 6 are centered on the Consistent Adjoint Driven Importance Sampling (CADIS) methodology. CADIS is used to create an importance map for space/energy weight windows as well as a biased source distribution. New to SCALE 6 are the Monaco functional module, a multigroup fixed-source Monte Carlo transport code, and the Monaco with Automated Variance Reduction using Importance Calculations (MAVRIC) sequence. MAVRIC uses the Denovo code (also new to SCALE 6) to compute coarse-mesh discrete ordinates solutions that are used by CADIS to form an importance map and biased source distribution for the Monaco Monte Carlo code. MAVRIC allows the user to optimize the Monaco calculation for a specific tally using the CADIS method with little extra input compared with a standard Monte Carlo calculation. When computing several tallies at once or a mesh tally over a large volume of space, an extension of the CADIS method called FW-CADIS can be used to help the Monte Carlo simulation spread particles over phase space to obtain more uniform relative uncertainties.
