Search Results (38)

Structural collapses caused by accidents or disasters could create unexpected radiation shielding, resulting in sharp gradients within the radiation field. Traditional radiation mapping methods often fail to accurately capture these complex variations, making the rapid and precise localization of radiation sources a significant challenge in emergency response scenarios. To address this issue, based on standard Gaussian process regression (GPR) models that primarily utilize a single Gaussian kernel to reflect the inverse-square law in free space, a novel multi-kernel Gaussian process regression (MK-GPR) model is proposed for high-fidelity radiation mapping in environments with physical obstructions. MK-GPR integrates two additional kernel functions with adaptive weighting: one models the attenuation characteristics of intervening materials, and the other captures the energy-dependent penetration behavior of radiation. To validate the model, gamma-ray distributions in complex, shielded environments were simulated using GEometry ANd Tracking 4 (Geant4). Compared with conventional methods, including linear interpolation, nearest-neighbor interpolation, and standard GPR, MK-GPR demonstrated substantial improvements in key evaluation metrics, such as MSE, RMSE, and MAE. Notably, the coefficient of determination (R²) increased to 0.937. For practical deployment, the optimized MK-GPR model was deployed to an RK-3588 edge computing platform and integrated into a mobile robot equipped with a NaI(Tl) detector. Field experiments confirmed the system’s ability to accurately map radiation fields and localize gamma sources. When combined with SLAM, the system achieved localization errors of 10 cm for single sources and 15 cm for dual sources. These results highlight the potential of the proposed approach as an effective and deployable solution for radiation source investigation in post-disaster environments. Full article

Radiation mapping is a desirable task to automate because of the inherent risks involved and its tedious nature. A novel system was designed to address this by combining various existing technologies, utilizing behavior-based robotics and Bayesian optimization. The system uses a quadruped robot equipped with a manipulator and gamma detector to take measurements at locations that are selected based on the uncertainty of a surrogate model used to estimate the true radiation field. The robot uses input from the world with depth cameras to avoid collisions with the robot’s body, and unreachable points for the end effector are addressed by both allowing for a soft collision with the environment to occur, prompting the system to abandon that point, and varying the exploration tendency of the optimization based on consecutive collisions. This approach provides unique traversability and adaptability over other strategies in the literature. Experiments were performed by placing a Cesium-137 source on the ground and varying geometric setups and an optimization parameter demonstrating the adaptability to diverse environments and the increased robustness resulting from the designed behavior. The results additionally demonstrate that dynamically adjusting the optimization algorithm’s exploration tendency based on the arm’s collision history improves the system’s ability to navigate cluttered environments and construct accurate radiation maps without getting stuck in unreachable areas. Full article

The use of UAVs to map ionising radiation resulting from radioactive decay is gaining popularity among researchers due to its efficiency and safety. Many studies have been conducted, most of them using expensive sensors. The present research aims to investigate the applicability of an affordable radiation detector in areas where anomalies from natural sources occur. In this research, we use a DJI Matrice 210 V2 RTK quadcopter equipped with a cost-effective Safecast bGeigie Nano Kit radiation sensor to take measurements at different altitudes above ground. We convert these data into GIS-compatible formats and produce accurate isoline maps using the Minimum Curvature interpolation technique. The results show that while the radiation intensity decreases with height, the anomaly was visible but less detailed at all heights investigated. In addition, the study highlights the significant differences in position measurements between RTK GNSS and autonomous GNSS measurements that affect the accuracy of the data. The results will contribute to a more accurate determination of the radiation extent and, thus, to maintaining safety, as well as assisting in emergency surveys and environmental monitoring. Full article

Iron redistribution in the intestine after total body irradiation is an established phenomenon. However, in the literature, there are no reports about the use of X-ray fluorescence microscopy or equivalent techniques to generate semi-quantitative 2D maps of iron in sectioned intestine samples from irradiated mice. In this work, we used X-ray fluorescence microscopy (XFM) to map the elemental content of iron as well as phosphorus, sulfur, calcium, copper and zinc in tissue sections of the small intestine from eight-week-old BALB/c male mice that developed gastrointestinal acute radiation syndrome (GI-ARS) in response to exposure to 8 Gray of gamma rays. Seven days after irradiation, we found that the majority of the iron is localized as hot spots in the intercellular regions of the area surrounding crypts and stretching between the outer perimeter of the intestine and the surface cell layer of villi. In addition, this study represents our current efforts to develop elemental cell classifiers that could be used for the automated generation of regions of interest for analyses of X-ray fluorescence maps. Once developed, such a tool will be instrumental for studies of effects of radiation and other toxicants on the elemental content in cells and tissues. While XFM studies cannot be conducted on living organisms, it is possible to envision future scenarios where XFM imaging of single cells sloughed from the human (or rodent) intestine could be used to follow up on the progression of GI-ARS. Full article

In the framework of the H2020 CLEANDEM project, a small robotic vehicle was equipped with a series of different sensors that were developed for the preliminary inspection of areas possibly contaminated by radiation. Such unmanned inspection allows to identify dangerous locations prior to the possible start of human operations. One of the developed devices, named the MiniRadMeter, is a compact low-cost sensor that performs gamma and neutron radiation field mapping in the environment. The MiniRadMeter was successfully tested in a simulated field mission with four “hidden” radioactive sources and a neutron generator. In this work, we describe the test procedure and the results, which were supported by the outcome of dedicated Monte Carlo simulations. Full article

In this work an innovative approach was developed to address a significant challenge in the field of radiation dosimetry: the accurate measurement of spatial dose distributions using Fricke gel dosimeters. Hydrogels are widely used in radiation dosimetry due to their ability to simulate the tissue-equivalent properties of human tissue, making them ideal for measuring and mapping radiation dose distributions. Among the various gel dosimeters, Fricke gels exploit the radiation-induced oxidation of ferrous ions to ferric ions and are particularly notable due to their sensitivity. The concentration of ferric ions can be measured using various techniques, including magnetic resonance imaging (MRI) or spectrophotometry. While Fricke gels offer several advantages, a significant hurdle to their widespread application is the diffusion of ferric ions within the gel matrix. This phenomenon leads to a blurring of the dose distribution over time, compromising the accuracy of dose measurements. To mitigate the issue of ferric ion diffusion, researchers have explored various strategies such as the incorporation of additives or modification of the gel composition to either reduce the mobility of ferric ions or stabilize the gel matrix. The computational method proposed leverages the power of artificial intelligence, particularly deep learning, to mitigate the effects of ferric ion diffusion that can compromise measurement precision. By employing Physics Informed Neural Networks (PINNs), the method introduces a novel way to apply physical laws directly within the learning process, optimizing the network to adhere to the principles governing ion diffusion. This is particularly advantageous for solving the partial differential equations that describe the diffusion process in 2D and 3D. By inputting the spatial distribution of ferric ions at a given time, along with boundary conditions and the diffusion coefficient, the model can backtrack to accurately reconstruct the original ion distribution. This capability is crucial for enhancing the fidelity of 3D spatial dose measurements, ensuring that the data reflect the true dose distribution without the artifacts introduced by ion migration. Here, multidimensional models able to handle 2D and 3D data were developed and tested against dose distributions numerically evolved in time from 20 to 100 h. The results in terms of various metrics show a significant agreement in both 2D and 3D dose distributions. In particular, the mean square error of the prediction spans the range $1\times {10}^{-6}$–$1\times {10}^{-4}$, while the gamma analysis results in a 90–100% passing rate with 3%/2 mm, depending on the elapsed time, the type of distribution modeled and the dimensionality. This method could expand the applicability of Fricke gel dosimeters to a wider range of measurement tasks, from simple planar dose assessments to intricate volumetric analyses. The proposed technique holds great promise for overcoming the limitations imposed by ion diffusion in Fricke gel dosimeters. Full article

Many cultivars of annual ornamental horticulture have great phenotypic qualities but are less tolerant to the effects of current climate change and urbanization. A good example of this in Hungarian ornamental breeding is the Rudbeckia hirta cultivar “Őszifény”. The objective of this study was to determine whether gamma mutation breeding (using 5 Gy, 10 Gy, 30 Gy doses) can be employed to enhance genetic variability and create mutants with novel trait values. Furthermore, it is important to ascertain whether the altered genetic traits are proportionate to the observed changes in phenotype. As an original and innovative aspect of the research, this will assist in establishing appropriate dose rates for the species. Changes induced by gamma radiation have been mapped using morphological, histological, and genetic methods. The radiation dose of 5 Gy resulted in plants with the most favorable characteristics, including significant increases in branching and flower number. Additionally, the phenomenon of hormesis was observed. Beyond these, the dose of 30 Gy also had a significant effect because it resulted in plants with many flowers and bushy habits, making them suitable for use as ornamental potted plants. The 10 Gy dose resulted in a heterogeneous stand but showed the greatest genetic variation. These results may contribute to future breeding work and may pave the way for further urban application of R. hirta in the light of urbanization. Full article

Natural background gamma rays and their effects on human health are essential components of both radiation protection and public concern. In the frame of these aspects, the mapping of the natural gamma dose rate values of the Province of Asti is given. The Asti Fire Brigade Command approved a project relating to the mapping of gamma radiation from the natural background in the territory of Asti. The project engaged both the Nuclear, Biological, Chemical, and Radiological (NBCR) and Topography Applied to Rescue (TAS) components of the Asti Command. Skilled personnel, comprising level 1 TAS operators for data collection and level 2 TAS operators for cartographic analysis, were deployed across the six working days. The methodology involved the use of two digital handheld radiation G-M detectors, in conjunction with a portable GPS unit, including the Global Mapper software. One of the significant findings of this study is the observation that the natural gamma dose rate levels were 201.25% higher in the streets of the city center compared to other areas, predominantly because the building materials in these locations contain a higher amount of natural radionuclides. The results indicated that the level of natural gamma dose rates in the studied region is close to the global average value. Full article

A novel solid-state neutron and gamma radiation monitor-dosimeter based on biopolymer polylactic acid (PLA) is presented. The resulting detector (PLAD) technology takes advantage of property changes of the renewable PLA resin when subject to ionizing nuclear radiation. A simple yet rapid and accurate (±10%) low-cost (<$0.01/detector) mass loss upon dissolution (MLD) technique was successfully developed; MLD is based on a simple mass balance for discerning neutron and/or gamma doses using small (40 mg, ~4 mm diameter) ultra-low-cost (<$0.01) resin beads via dissolution in acetone. The GammaCell^TM Co-60 irradiator, and the PUR-1 12 kW fission nuclear research reactor were utilized, respectively. Irradiation absorbed doses ranged from 1 to 100 kGy. Acetone bath temperature was varied from ~40 °C to ~54 °C. Results revealed a strong dependence of MLD on acetone bath temperature between neutron and gamma photon dose components; this allowed for the unique ability of PLAD to potentially perform as both a neutron-cum-gamma or as a gamma or neutron radiation dosimeter and intensity level detector. A linear trend is found for combined neutron and gamma radiation doses from 0 to 40 kGy when dissolution is conducted above 50 °C. The important potential ability to distinguish neutron from gamma radiation fields was scoped and found to be feasible by determining MLD at 45 °C. The potential was studied for simultaneous use as an in-core neutron and gamma monitor of an operating 3 GWt light-water reactor (LWR). Scoping tests were conducted with the pre-irradiated (@ 20 °C) PLAD resin beads followed by heating to in-core LWR coolant (300 °C) conditions for ~30 s corresponding to the time to reach ~40 kGy total doses in a typical 3 GWt LWR. MLD results were unaffected, indicating the exciting and unique potential for in situ (low-cost, accurate and rapid) simultaneous mapping of neutron and gamma radiation fluxes, related dosimetry, and fission power level monitoring. Full article

The radiation effect of materials is very important and directly related to the safety and reliability of nuclear reactors. Polymer materials, one of the indispensable materials in nuclear power equipment, must withstand the ordeal of high-energy ionizing rays. In this work, through screening different γ-ray dose irradiation conditions, we systematically and comprehensively study the changes in the structure and properties of nitrile butadiene rubber (NBR) before and after γ-ray static irradiation at a high dose rate, and master the rule and mechanism of the γ-ray static irradiation effect of these polymer materials. The mapping relationship between the macroscopic properties, microstructure, and irradiation dose of NBR is accurately characterized. With an increase in total irradiation dose, the C=C double bond reaction occurs, and the C≡N bond, C=C, and C=O participate in the hyper crosslinking reaction. The glass transition temperature (T_g) increases with the cumulative irradiation amount. With the increased total irradiation amount, the degree of rubber cross-linking increases, causing an increased crystallinity and decomposition temperature. A growing amount of gamma irradiation causes the mechanical properties of the rubber to degrade simultaneously, increasing the shore hardness while decreasing the tensile strength and ultimate elongation at break. When the cumulative amount reaches 1 MGy, the ultimate elongation at break decreases significantly. A cumulative dose of radiation resistance of 4 MGy can be achieved by the samples. This work can provide theoretical and experimental support for the long-term stability of nitrile butadiene rubber and its derivatives in nuclear radiation fields and space radiation conditions. Full article

The decommissioning of nuclear installations, as well as the possible necessary accident remediations, requires the physical presence of human operators in potentially radiologically hostile environments. The number of active nuclear reactors worldwide is greater than 400, and most of them are 40 to 50 years old, thus implying that soon they will have to be dismantled. In the framework of the H2020 CLEANDEM project, a small robotic vehicle is being developed that is equipped with a series of different sensors for areas that are significantly contaminated by radiation. In this work, we describe the MiniRadMeter system, a compact low-cost sensor capable of being used to perform quick gamma and neutron radiation field mapping of environments prior to the possible start of human operations. The miniature gamma sensor is a 1 cm³ scintillator counter with moderate spectroscopic features read out by means of a 6 × 6 mm² SiPM, whereas neutrons are detected by means of a silicon diode coupled to a layer of ⁶LiF and placed inside a 6 × 6 × 6 cm³ polyethylene box. The front-end and data acquisition electronics were developed based on a Raspberry Pi4 microcomputer. In this paper, the system performance and the preliminary test results are described. Full article

This work presents the application of a novel evolutional algorithmic approach to determine and reconstruct the specific 3-dimensional source location of gamma-ray emissions within the shelter object, the sarcophagus of reactor Unit 4 of the Chornobyl Nuclear Power Plant. Despite over 30 years having passed since the catastrophic accident, the high radiation levels combined with strict safety and operational restrictions continue to preclude many modern radiation detection and mapping systems from being extensively or successfully deployed within the shelter object. Hence, methods for reconstructing the intense and evolving gamma fields based on the limited inventory of available data are crucially needed. Such data is particularly important in planning the demolition of the unstable structures that comprise the facility, as well as during the prior operations to remove fuel containing materials from inside the sarcophagus and reactor Unit 4. For this approach, a simplified model of gamma emissions within the shelter object is represented by a series of point sources, each regularly spaced on the shelter object’s exterior surface, whereby the calculated activity values of these discrete sources are considered as a population in terms of evolutionary algorithms. To assess the numerical reconstruction, a fitness function is defined, comprising the variation between the known activity values (obtained during the commissioning of the New Safe Confinement at the end of 2019 on the level of the main crane system, located just below the arch above the shelter object) and the calculated values at these known locations for each new population. The final algorithm’s performance was subsequently verified using newly obtained information on the gamma dose-rate on the roof of the shelter object during radiation survey works at the end of 2021. With only 7000 iterations, the algorithm attained an MAPE percentage error of less than 23%, which the authors consider as satisfactory, considering that the relative error of the measurements is ±17%. While a simple initial application is presented in this work, it is demonstrated that evolutional algorithms could be used for radiation mapping with an existing network of radiation sensors, or, as in this instance, based on historic gamma-field data. Full article

At present, much emphasis is placed on the health risks associated with radioactivity present in the environment, especially since the accident at the Fukushima Daiichi Nuclear Power Plant. In this study, a walking survey was conducted in Hirosaki City using a NaI(Tl) scintillation spectrometer to estimate and map the distribution of the ambient dose equivalent rate to monitor the radiological safety of the general public in Hirosaki City, where many nuclear facilities are located nearby. The average (±standard deviation) ambient dose equivalent rate was 0.056 ± 0.020 µSv h⁻¹. By comparison with the measurement data, it was found that the values of 85% of the data obtained using the walking survey technique deviated within ±20% relative to those obtained by spot measurements. Furthermore, the distribution of dose rates obtained in the nighttime survey was not significantly different from those obtained in the daytime. Full article

In this work, black nanocarbon-loaded 0–100 parts-per-hundred (phr) PbO-filled acrylonitrile butadiene rubber (NBR)/styrene-butadiene rubber (SBR) blend composites were prepared by using an ordinary standard rubber mixer. Both mechanical and gamma attenuation properties of the prepared samples were investigated. Maximum tensile strength and elongation at break were obtained at 40 phr PbO concentration. The obtained values for the mass attenuation coefficient with the increased PbO concentration from 0–100 phr ranged from 0.12–0.22 cm²/g at 0.239 MeV. Scanning electron microscope (SEM) with the elemental mapping analysis results showed high homogeneity at 40 phr of the prepared rubber composites, with some areas of elemental agglomeration at a high concentration of lead oxide. The obtained results highly recommend the use of the prepared nanocarbon-reinforced PbO/NBR/SBR blend compared to those previously used as personal protective equipment in radiation-shielding applications. Full article

A detailed investigation of geogenic radon potential (GRP) was carried out near Graiguenamanagh town (County Kilkenny, Ireland) by performing a spatial regression analysis on radon-related variables to evaluate the exposure of people to natural radiation (i.e., radon, thoron and gamma radiation). The study area includes an offshoot of the Caledonian Leinster Granite, which is locally intruded into Ordovician metasediments. To model radon release potential at different points, an ordinary least squared (OLS) regression model was developed in which soil gas radon (SGR) concentrations were considered as the response value. Proxy variables such as radionuclide concentrations obtained from airborne radiometric surveys, soil gas permeability, distance from major faults and a digital terrain model were used as the input predictors. ArcGIS and QGIS software together with XLSTAT statistical software were used to visualise, analyse and validate the data and models. The proposed GRP models were validated through diagnostic tests. Empirical Bayesian kriging (EBK) was used to produce the map of the spatial distribution of predicted GRP values and to estimate the prediction uncertainty. The methodology described here can be extended for larger areas and the models could be utilised to estimate the GRPs of other areas where radon-related proxy values are available. Full article