Earticle

Background: A nondestructive test is commonly used to inspect the surface defects and internal structure of an object without any physical damage. X-rays generated from an electron accelerator or a tube are one of the methods used for nondestructive testing. The high penetration of X-rays through materials with low atomic numbers makes it difficult to discriminate between these materials using X-ray imaging. The interaction characteristics of neutrons with materials can supplement the limitations of X-ray imaging in material discrimination. Materials and Methods: The radiation image acquisition process for air-cargo security inspection equipment using X-rays and neutrons was simulated using a GEometry ANd Tracking (Geant4) simulation toolkit. Radiation images of phantoms composed of 13 materials were obtained, and the R-value, representing the attenuation ratio of neutrons and gamma rays in a material, was calculated from these images. Results and Discussion: The R-values were calculated from the simulated X-ray and neutron images for each phantom and compared with those obtained in the experiments. The R-values obtained from the experiments were higher than those obtained from the simulations. The difference can be due to the following two causes. The first reason is that there are various facilities or equipment in the experimental environment that scatter neutrons, unlike the simulation. The other is the difference in the neutron signal processing. In the simulation, the neutron signal is the sum of the number of neutrons entering the detector. However, in the experiment, the neutron signal was obtained by superimposing the intensities of the neutron signals. Neutron detectors also detect gamma rays, and the neutron signal cannot be clearly distinguished in the process of separating the two types of radiation. Despite these differences, the two results showed similar trends and the viability of using simulation-based radiation images, particularly in the field of security screening. With further research, the simulation-based radiation images can replace ones from experiments and be used in the related fields. Conclusion: The Korea Atomic Energy Research Institute has developed air-cargo security inspection equipment using neutrons and X-rays. Using this equipment, radiation images and Rvalues for various materials were obtained. The equipment was reconstructed, and the R-values were obtained for 13 materials using the Geant4 simulation toolkit. The R-values calculated by experiment and simulation show similar trends. Therefore, we confirmed the feasibility of using the simulation-based radiation image.

Background: Recently, biological adsorbents have been developed for removing radionuclides from radioactive liquid waste due to their high selectivity, eco-friendliness, and renewability. However, since they can be damaged by radiation in radioactive waste, a method for estimating the bio-adsorbent performance as a time should consider the radiation damages in terms of their renewability. This paper aims to develop a simulation method that applies a deep learning technique to rapidly and accurately estimate the adsorption performance of bio-adsorbents when inserted into liquid radioactive waste. Materials and Methods: A model that describes various interactions between a bio-adsorbent and liquid has been constructed using numerical methods to estimate the adsorption capacity of the bio-adsorbent. To generate datasets for machine learning, Monte Carlo N-Particle (MCNP) simulations were conducted while considering radioactive concentrations in the adsorbent column. Results and Discussion: Compared with the result of the conventional method, the proposed method indicates that the accuracy is in good agreement, within 0.99% and 0.06% for the R2 score and mean absolute percentage error, respectively. Furthermore, the estimation speed is improved by over 30 times. Conclusion: Note that an artificial neural network can rapidly and accurately estimate the survival rate of a bio-adsorbent from radiation ionization compared with the MCNP simulation and can determine if the bio-adsorbents are reusable.

Background: Radiation protection is crucial in various fields due to the harmful effects of radiation. Shielding is used to reduce radiation exposure, but gamma radiation poses challenges due to its high energy and penetration capabilities. Materials and Methods: This work investigates the radiation shielding properties of polyvinylidene fluoride (PVDF) samples containing different weight fraction of tungsten carbide (WC), tungsten trioxide (WO3), and tungsten disulfide (WS2). Parameters such as the mass attenuation coefficient (MAC), half-value layer (HVL), mean free path (MFP), effective atomic number (Zeff), and macroscopic effective removal cross-section for fast neutrons (ΣR) were calculated using the Phy-X/PSD software. EpiXS simulations were conducted for MAC validation. Results and Discussion: Increasing the weight fraction of the additives resulted in higher MAC values, indicating improved radiation shielding. PVDF–xWC showed the highest percentage increase in MAC values. MFP results indicated that PVDF–0.20WC has the lowest values, suggesting superior shielding properties compared to PVDF–0.20WO3 and PVDF– 0.20WS2. PVDF–0.20WC also exhibited the highest Zeff values, while PVDF–0.20WS2 showed a slightly higher increase in Zeff at energies of 0.662 and 1.333 MeV. PVDF–0.20WC has demonstrated the highest ΣR value, indicating effective shielding against fast neutrons, while PVDF– 0.20WS2 had the lowest ΣR value. The Monte Carlo N-Particle Transport version 5 (MCNP5) simulations showed that PVDF–xWC attenuates gamma radiation more than pure PVDF, significantly decreasing the dose equivalent rate. Conclusion: Overall, this research provides insights into the radiation shielding properties of PVDF mixtures, with PVDF–xWC showing the most promising results.

Background: The thermoluminescent dosimeter (TLD) and Monte Carlo (MC) dosimetry are carried out to determine the occupational dose for personnel in the handling of 125I seed sources. Materials and Methods: TLDs were placed in different layers of the Alderson-Rando phantom in the thyroid, lung and also eyes and skin surface. An 125I seed source was prepared and its activity was measured using a dose calibrator and was placed at two distances of 20 and 50 cm from the Alderson-Rando phantom. In addition, the Monte Carlo N-Particle Extended (MCNPX 2.6.0) code and a computational phantom with a lattice-based geometry were used for organ dose calculations. Results and Discussion: The comparison of TLD and MC results in the thyroid and lung is consistent. Although the relative difference of MC dosimetry to TLD for the eyes was between 4% and 13% and for the skin between 19% and 23%, because of the existence of a higher uncertainty regarding TLD positioning in the eye and skin, these inaccuracies can also be acceptable. The isodose distribution was calculated in the cross-section of the head phantom when the 125I seed was at two distances of 20 and 50 cm and it showed that the greatest dose reduction was observed for the eyes, skin, thyroid, and lungs, respectively. The results of MC dosimetry indicated that for near the head positions (distance of 20 cm) the absorbed dose rates for the eye lens, eye and skin were 78.1±2.3, 59.0±1.8, and 10.7±0.7 μGy/mCi/hr, respectively. Furthermore, we found that a 30 cm displacement for the 125I seed reduced the eye and skin doses by at least 3- and 2-fold, respectively. Conclusion: Using a computational phantom to monitor the dose to the sensitive organs (eye and skin) for personnel involved in the handling of 125I seed sources can be an accurate and inexpensive method.

Background: Isotopes of the projectile may be produced along the beam path during the irradiation of a target by a heavy ion due to inelastic interactions with the media. This study analyzed the production cross-section of carbon (C) and Helium (He) projectile’s isotopes resulting from the interactions of these beams with different materials along the beam path. Materials and Methods: In this study, we transport C and He ion beams through different materials. This transportation was made by the Monte Carlo simulation. Particle and Heavy Ion Transport code System (PHITS) has been used for this calculation. Results and Discussion: It has been found that 10C, 11C, and 13C from the 12C ion beam and 3He from the 4He ion beam are significant projectile’s isotopes that have higher flux than other isotopes of these projectiles. The 4He ion beam has a higher projectile’s isotope production crosssection along the beam path, which adds more impurities to the beam than the 12C ion beam. These projectile’s isotopes from both the 12C and 4He ion beams have higher production crosssections in hydrogenous materials like water or polyethylene. Conclusion: It is important to distinguish these projectile’s isotopes from the primary beam particles to obtain a precise and accurate cross-section result by minimizing the error during measurement with a nuclear track detector. This study will show the trend of the production probability of projectile’s isotopes for these ion beams.