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Nuclear Science and Engineering
Fusion Science and Technology
Brouillette: Nuclear should be part of California’s energy problem solution
In an op-ed published on September 25 in the Orange County Register, Energy Secretary Dan Brouillette decryed the state of California’s handling of its energy crisis.
Brouillette criticized state leaders for championing a 100 percent renewable energy plan that ignores nuclear and natural gas. He also found fault with the plan to prematurely close the Diablo Canyon nuclear power plant.
Jeffrey A. Favorite, Zoltán Perkó, Brian C. Kiedrowski, Christopher M. Perfetti
Nuclear Science and Engineering | Volume 185 | Number 3 | March 2017 | Pages 384-405
Technical Paper | dx.doi.org/10.1080/00295639.2016.1272990
Articles are hosted by Taylor and Francis Online.
The evaluation of uncertainties is essential for criticality safety. This paper deals with material density and composition uncertainties and provides guidance on how traditional first-order sensitivity methods can be used to predict their effects. Unlike problems that deal with traditional cross-section uncertainty analysis, material density and composition-related problems are often characterized by constraints that do not allow arbitrary and independent variations of the input parameters. Their proper handling requires constrained sensitivities that take into account the interdependence of the inputs. This paper discusses how traditional unconstrained isotopic density sensitivities can be calculated using the adjoint sensitivity capabilities of the popular Monte Carlo codes MCNP6 and SCALE 6.2, and we also present the equations to be used when forward and adjoint flux distributions are available. Subsequently, we show how the constrained sensitivities can be computed using the unconstrained (adjoint-based) sensitivities as well as by applying central differences directly. Three distinct procedures are presented for enforcing the constraint on the input variables, each leading to different constrained sensitivities. As a guide, the sensitivity and uncertainty formulas for several frequently encountered specific cases involving densities and compositions are given. An analytic k∞ example highlights the relationship between constrained sensitivity formulas and central differences, and a more realistic numerical problem reveals similarities among the computer codes used and differences among the three methods of enforcing the constraint.