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Particle Swarm Optimization For Critical Experiment Design, Cole Michael Kostelac

Masters Theses

“Critical experiments are used by nuclear data evaluators and criticality safety engineers to validate nuclear data and computational methods. Many of these experiments are designed to maximize the sensitivity to a certain nuclide-reaction pair in an energy range of interest. Traditionally, a parameter sweep is conducted over a set of experimental variables to find a configuration that is critical and maximally sensitive. As additional variables are added, the total number of configurations increases exponentially and quickly becomes prohibitively computationally expensive to calculate, especially using Monte Carlo methods.

This work presents the development of a particle swarm optimization algorithm to design …