Bayesian optimization of a collimated HPGe detector model for Segmented Gamma Scanning

Abstract

Segmented Gamma Scanning (SGS) is an important technique for quantifying gamma-emitting isotopes in radioactive waste packages. Collimated High-Purity Germanium (HPGe) detectors are commonly employed due to their superior resolution. However, calibrating HPGe detectors equipped with complex collimators poses challenges, especially regarding the modeling of the spatial response of the detector. This work introduces a calibration methodology for the Full Energy Peak Efficiency (FEPE) of HPGe detectors equipped with variable aperture collimators using Bayesian optimization to handle their complex geometries. The method and the model were then validated for the full range of application of the detector-collimator arrangement using experimental FEPE measurements, demonstrating the model's potential for accurate SGS simulations.