Genetic algorithm based parametric optimization for calculation of beta particle detection efficiency in thin plastic scintillation detector

Abstract

TPS (Thin plastic scintillation) detectors have been widely used for beta-ray measurements in systems such as radiation monitoring system, α∙β contamination probe and whole body contamination monitor. In the β-ray measurement process using the TPS detector, β-rays transmit only some energy to the scintillator, so energy information of β-rays can’t be obtained in measured spectrums. Due to this characteristics, simulation studies using TPS detectors are limited. In this thesis, a genetic algorithm based parametric optimization method was proposed to calculate DE of the TPS detector using MCNP simulation. The parameters for response function of the detector and energy calibration were estimated through comparison of experiment and simulation results using the genetic algorithm. In order to verify the optimization results, DEs for Xe-133 and Kr-85 of condenser off-gas radiation monitoring system was calculated and compared with specification. As a result, DEs were close to specification as relative errors of -0.3% and 2.91% respectively.