Defining an equivalent geometry for Monte Carlo calculations of a high-purity Ge detector with high relative efficiency using a genetic algorithm

Detailed geometric information of a high-purity Ge (HPGe) detector is a very important issue for Monte Carlo simulation of the detector. Commonly, users have no geometric information about the detector and information given by the manufacturer is not completely valid for simulation. An equivalent geometry of detector, the parameters of which can be used for Monte Carlo simulation, is optimised using a genetic algorithm for a large-volume HPGe detector in this study. A mixed-point gamma calibration standard, emitting 12 useful gamma-radiation energies within 59.5–1836.1 keV, is placed at 74 different locations around the detector for this purpose. A high-quality solution is generated starting from an initial population of randomly-generated detector geometries using a genetic algorithm. Fitness of each geometry is obtained by comparing full energy peak efficiencies computed by Monte Carlo simulation with experimental values for each energy and position. Efficiencies with relative errors less than 5% for high energies and less than 7% for lower energies, except 59.5 keV, are obtained using optimised equivalent geometry parameters for the Monte Carlo simulation. Also, the necessity of using crystal dimensions smaller than real dimensions for Monte Carlo simulations of high-volume HPGe detectors is discussed. In addition, for Monte Carlo simulation of high-volume HPGe detectors, it is demonstrated that the use of smaller crystal dimensions than the real dimensions is necessary to obtain experimentally measured efficiencies of the detector. •Problems in Monte Carlo simulations of high-volume Germanium detectors are discussed.•Defining new equivalent geometry parameters for these simulations are proposed.•New geometry parameters are described by a genetic algorithm.•Necessity of simulating high-volume Ge detectors with smaller dimensions are stated.•Energy cumulative distribution function is used to simulate true coincidence effects.