Developing a Methodology for Characterizing the Effects of Building Materials’ Natural Radiation Background on a Radiation Portal Monitoring System

Abstract

Trafficking of radioactive material, particularly special nuclear material (SNM), has long been a worldwide concern. To interdict this material the US government has installed radiation portal monitors (RPMs) around the globe. Building materials surrounding an RPM can greatly effect the detector’s background radiation levels due to Naturally Occurring Radioactive Material (NORM). In some cases this effect is so great that the initial RPM setup had to be rebuilt.

This thesis develops a methodology for quick and efficient determination of the specific activity and composition of building materials surrounding a RPM to predict background levels, therefore determining the minimum detectable quantity (MDQ) of material. This methodology builds on previous work by Ryan et al by generating material and source cards for a detailed Monte Carlo N-Particle (MCNP) deck, based on an experimental RPM setup to predict the overall gamma background at a site.

Gamma spectra were acquired from samples of building materials and analyzed to determine the specific activity of the samples. A code was developed to estimate the elemental composition of building materials using the gamma transmission of the samples. These results were compared to previous Neutron Activation Analysis (NAA) on the same samples. It was determined that densitometry provided an elemental approximation within 5% of that found through NAA. Using the specific activity and material composition, an MCNP deck was used to predict the gamma background levels in the detectors of a typical RPM. These results were compared against actual measurements at the RPM site, and shown to be within 10% of each other.