Date of Award

6-2025

Document Type

Thesis

Degree Name

Master of Science in Systems Engineering

Department

Department of Systems Engineering and Management

First Advisor

Darren E. Holland, PhD

Abstract

The Rotating Scatter Mask (RSM) system is a radiation imaging technology currently limited by the mask design and governing identification algorithm parameters. To optimize the RSM design, Dakota—an optimization software—was integrated with a ray tracing code that simulates particle interactions with the RSM detector, and with the Locally Competitive Algorithm (LCA), which reconstructs the source image based on the ray tracing code’s Detector Response Matrix (DRM). Since the original ray tracing code was developed in MATLAB, it was translated into Python to improve compatibility with both Dakota and LCA. The Python version of the ray tracing code was then integrated with the LCA code, requiring both to be reformatted as callable functions. A custom Python driver was developed to facilitate communication between Dakota and the ray tracing and LCA modules. Initial optimization studies used 250 evaluations and 9 parameters to determine suitable settings for Dakota 's Multi-Objective Genetic Algorithm (MOGA). To validate these settings, a longer optimization study with 3,000 evaluations was performed. The final optimization used 902 parameters. The study resulted in 7,179 evaluations and identified five optimized RSM designs. The five designs had maximum average Earth Mover’s Distance and rotation values of 7.48 and 2.31, compared to 26.99 and 16.23 in earlier designs. The RSM system has the potential to more accurately locate lost or smuggled radioactive materials, helping to ensure safety and prevent radiation-related hazards.

AFIT Designator

AFIT-ENV-MS-J-003

Comments

An embargo was observed for posting this thesis on AFIT Scholar.
Approved for public release, distribution unlimited. PA case number 88ABW-2025-0568

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