PhD thesis defense | Kaciel Béraud

Enhancing 3-dimensional radiation mapping and dose estimation with machine learning techniques and novel directional spectrometer

In radiation-rich environments, it is necessary to quantify the risk to human health from ionising radiation. Accurate radiation dose evaluation cannot be evaluated in real time; only a compute-heavy offline analysis can estimate it. This thesis details the development of the second version of a novel portable dual-mode directional radiation survey meter capable of accurate source localisation for security and dosimetry applications, called nFacet 3D.
 
nFacet 3D is a segmented scintillator-based detector sensitive to neutrons, gamma rays and muons. A detailed technical description of the detector, covering the mechanical design, electronic logic, software acquisition and graphical user interface, is provided, including a proof-of-concept study to improve the low-energy sensitivity by the addition of a new crystal scintillator. A simulation is used to determine the efficiency and sensitivity of the system for neutrons and gamma rays for multiple system configurations. The energy sensitivity and direction sensitivity have been demonstrated through a series of measurement campaigns.
 

November 6, 2026

LPC Caen

LABORATOIRE DE PHYSIQUE CORPUSCULAIRE DE CAEN

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UMR-6534

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