Remote detection of fissile material : Cherenkov counters for gamma detection

Abstract

The need for large-size detectors for long-range active interrogation (Al) detection has generated interest in water-based detector technologies. AI is done using external radiation sources to induce fission and to detect, identify, and characterize special nuclear material (SNM) through the gamma rays and neutrons emitted. Long-range applications require detectors with a large solid angle and an ability to significantly suppress lowenergy background from linear electron accelerators. Water Cherenkov Detectors (WCD) were selected because of their transportability, scalability, and an inherent energy threshold. The main objective of this thesis was to design a large-size WCD capable of detecting gamma rays and to demonstrate particle energy discrimination ability. WCD was modeled in detail using Geant4 for optimization purposes. The experimental detector is composed of an aluminum body with a high efficiency (98.5%) diffuse reflector. Cherenkov photons are detected with six 8" hemispherical Hamamatsu photomultiplier tubes (PMT). PMTs are calibrated using two monoenergetic LEDs. The detector was shown to successfully detect gamma rays of energies above the Cherenkov threshold. The detector was able to discriminate between various sources, such as ⁶⁰Co and ²³²Th, even though WCD are known for their poor energy resolution. The detector design and analysis was completed, and it was demonstrated both computationally and experimentally that it is possible to use WCD to detect and characterize gamma rays. One of the accomplishments of this thesis was demonstration of event reconstruction capability of the detector system. A full-detector model was created using Geant4 simulation toolkit. The performance of the detector was predicted using the model and then experimentally verified. The qualitative agreement between the model and the experiment was observed. The event reconstruction was an important part of the detector performance analysis. Post-experimental data processing was done using ROOT.