SUMMARY

The time and cost of the development of radiation shielding systems can be greatly reduced by an automated tool which designs these systems with minimal input from a human analyst. Such an automated tool can be created by using a Genetic Algorithm (GA) coupled with a Response Matrix Method (RMM) transport solver. Radiation shielding problems often involve layers of materials in simple arrangements. Here, a 1-dimensional slab geometry RMM implementation is used to rapidly evaluate a fixed-source neutron transport problem much faster than is possible with direct Monte Carlo methods. This RMM enables the GA implementation to evaluate tens of thousands of configurations of varying thicknesses of shielding materials for design and optimization problems. Like many engineering problems before it, radiation shielding design problems can be formulated for optimization by a GA. A fitness function is defined to quantify how well a shield satisfies some desired criteria. Then the properties of potential shields are evolved over hundreds of generations in order to arrive at an optimized arrangement of materials of various thicknesses. The nonlinearity of radiation transport and large solution space of possible shielding designs are well-suited to be explored using a GA. Although the principal application considered is shielding design, these methods and implementations can be used to solve any fixed-source problem with a sufficiently simple geometry.