Simple procedure for optimizing model of NaI(Tl) detector using Monte Carlo simulation

COMPARISON OF THE BACKGROUND GAMMA-RAY SPECTRUM FROM SOIL OBTAINED BY DIRECT MEASUREMENT AND BY CALCULATION USING MCNP6 WITH NAI(TL) SCINTILLATION DETECTOR

Efficiency calibration is an essential part of any gamma-spectrometric or non-spectrometric measurement. The article describes all steps leading to the reconstruction of the gamma-ray spectrum from the soil - mathematical calibration of the NaI(Tl) detector and optimization of the model in the MCNP6 code, determination of radionuclide vector of soil around NPPs in Slovakia, calculation of the detector response matrix using the calculation code MCNP6 and finally the reconstruction of the gamma-ray spectrum. The results were compared in the energy range of 50-1620 keV for the spectrum obtained by direct measurement of the soil sample and for the spectrum obtained by calculation using the code MCNP6. The relative deviation in the whole spectrum between direct measurement and calculation is not more than 2%, which can be considered as the satisfactory result. The detector model thus created can be used to calculate the response matrix for any geometry arrangement.

A study on the sensitivity of the measurement of liquid density at different scattering angles using a gamma scattering technique

This study aims to evaluate the sensitivity of the measurement of liquid density at different scattering angles using a gamma scattering technique. To perform this, the linear calibration curves of the ratio R (R is the ratio of the area under a single scattering peak for a liquid relative to that for water) versus the liquid density were constructed at different scattering angles. The sensitivity of the measurement is defined as the slope coefficient of these linear calibration curves. The results obtained from the Monte Carlo simulation data showed that the sensitivity of the measurement at different scattering angles including 70°, 80°, 90°, 100°, 110°, 120°, 130°, and 140° changes in the range from 0.44 to 0.48. Also, the results obtained from the experiment when performing the measurements at scattering angles of 90°, 100°, 110°, and 120° ranged from 0.46 to 0.48. This confirms that the dependence of the sensitivity of the measurement on scattering angle is insignificant. Besides, for every experimental dataset, we used each of 8 above-obtained calibration curves, in turn, to determine the densities of 8 liquids which yield the relative deviation between the measured density and the reference one is mostly less than 5%, the relative deviation of remaining cases (64 of 256 measurements) is in the range of 5.0%-9.9%.

An artificial neural network based approach for estimating the density of liquid applied in gamma transmission and gamma scattering techniques

The study presents a new ANN-based approach to determine the density of a liquid applied in the gamma transmission and gamma scattering techniques. This approach used the Monte Carlo simulation combined with an artificial intelligence technique and experimental data to estimate the density of liquids. Two advantages of the proposed approach: (1) it is able to determine the density of a liquid by only measuring the gamma spectrum (transmission spectrum or scattering spectrum) without knowing the composition of the liquid, and (2) it is able to determine the density of a liquid when it is contained in a tube of various diameters. The artificial neural network model was trained by data obtained from simulation and then was used to predict the density of seven liquids with density in the range of 0.6 g cm^-3 to 2.0 g cm^-3 for the purpose of validating the proposed approach. For the gamma transmission technique, there are 25/28 samples with relative deviations between reference and predicted densities of less than 5%. The remaining three samples have deviations in the range from 5.2% to 6.3%. For the gamma scattering technique, there are 17/21 samples with a relative deviation of less than 5%. The remaining four samples have a deviation in the range from 5.2% to 6.9%. The results proved that the artificial intelligence technique combined with Monte Carlo based on gamma transmission and gamma scattering techniques is an effective approach for estimating the density of a liquid.

A revision of the virtual point detector model for calculating Nai(Tl) detector efficiency

In present work, the validity of the virtual point detector (VPD) model for the NaI(Tl) detectors is studied and confirmed in the photon energy range of 60-1408 keV. The full energy peak efficiency (FEPE) of two NaI(Tl) detectors, which have scintillation crystal dimensions of 5.08 × 5.08 cm and 7.62 × 7.62 cm respectively, is measured for "point-like" radioactive sources on the symmetry axis with source-to-detector distances in the range of 2-40 cm. It is found that the VPD model is valid to fit too well to the experimental FEPE for the two surveyed NaI(Tl) detectors. The dependence of the VPD position on the incident photon energy for the NaI(Tl) detectors with different scintillation crystal dimensions is shown based on experimental data. A semi-empirical equation involving incident photon energy and source-to-detector distance is proposed to calculate the FEPE for the NaI(Tl) detectors. The calculated results for the two surveyed NaI(Tl) detectors by this equation are in a good agreement with experimental results for photon energies in the range of 344-1408 keV. However, the difference between experimental and calculated results is quite significant for source-to-detector close geometries for photon energies lower than 344 keV.