Localization of Neutron Sources with Mobile Radiation Detectors Based on Drone Technology

Open Access
Duffin, Taylor Gregory
Graduate Program:
Nuclear Engineering
Master of Science
Document Type:
Master Thesis
Date of Defense:
July 10, 2017
Committee Members:
  • Marek Flaska, Thesis Advisor
  • Kenan Unlu, Committee Member
  • Arthur Thompson Motta, Committee Member
  • Radiation Detection
  • Drones
  • Neutron Detection
  • Searching Methods
The threat of nuclear proliferation and nuclear terrorism are strong motivators for systems that can detect special nuclear materials, including those that are heavily shielded or in transit. Previous detection methods have focused on large arrays of detectors to maximize counts coming from a potential source. With the advent of small quad-copter drones available commercially it is theorized that a fleet of these drones mounted with radiation detector would have significant advantages over large arrayed stationary systems. A fleet of drones can cover larger areas, give much more localized counting data and have flexibility to change paths and work as a unit to discover a hidden source in a more efficient manner. In this work, a simulation model is created that represents a fleet of drones mounted with radiation detectors locating a hidden stationary or moving neutron source. The dependence of the model on various system parameters is explored in detail. The system is strongly dependent on detector efficiency and counting time while only moderately dependent on the macroscopic neutron cross-section of the air and the neutron background flux. Using a fleet of drones instead of a single drone is shown to be more efficient in all cases, with gains up to 100x faster for 10 drones searching for a 1 mCi source. Drones that respond with adaptive movement when a suspicious signal is detected allow the source to be located hundreds of seconds faster even for sources with weak activities. The amount of benefit depends on the source strength and other parameters such as efficiency. Moving sources are the most difficult for the fleet of drones to find, but responsive movement can allow detection of a moving source that would otherwise evade the fleet.