Performance Analysis of Geiger-Müller and Cadmium Zinc Telluride Sensors Envisaging Airborne Radiological Monitoring in NORM Sites

Basic Performance Evaluation of a Radiation Survey Meter That Uses a Plastic-Scintillation Sensor

After the Fukushima nuclear power plant accident in 2011, many types of survey meters were used, including Geiger-Müller (GM) survey meters, which have long been used to measure β-rays. Recently, however, a novel radiation survey meter that uses a plastic-scintillation sensor has been developed. Although manufacturers' catalog data are available for these survey meters, there have been no user reports on performance. In addition, the performance of commercial plastic-scintillation survey meters has not been evaluated. In this study, we experimentally compared the performance of a plastic-scintillation survey meter with that of a GM survey meter. The results show that the two instruments performed very similarly in most respects. The GM survey meter exhibited count losses when the radiation count rate was high, whereas the plastic-scintillation survey meter remained accurate under such circumstances, with almost no count loss at high radiation rates. For measurements at background rates (i.e., low counting rates), the counting rates of the plastic-scintillation and GM survey meters were similar. Therefore, an advantage of plastic-scintillation survey meters is that they are less affected by count loss than GM survey meters. We conclude that the plastic-scintillation survey meter is a useful β-ray measuring/monitoring instrument.

Neutron and Gamma-Ray Detection System Coupled to a Multirotor for Screening of Shipping Container Cargo

In order to detect special nuclear materials and other radioactive materials in Security and Defense scenarios, normally, a combination of neutron and gamma-ray detection systems is used. In particular, to avoid illicit traffic of special nuclear materials and radioactive sources/materials, radiation portal monitors are placed at seaports to inspect shipping-container cargo. Despite their large volume (high efficiency), these detection systems are expensive, and therefore only a fraction of these containers are inspected. In this work, a novel mobile radiation detection system is presented, based on an EJ-200 plastic scintillator for the detection of gamma rays and beta particles, and a neutron detector EJ-426HD plastic scintillator (with ⁶Li) embedded in a compact and modular moderator. The use of silicon photomultipliers in both detectors presented advantages such as lightweight, compactness, and low power consumption. The developed detection system was integrated in a highly maneuverable multirotor. Monte Carlo simulations were validated by laboratory measurements and field tests were performed using real gamma-ray and neutron sources. The detection and localization within one meter was achieved using a maximum likelihood estimation algorithm for ¹³⁷Cs sources (4 MBq), as well as the detection of ²⁴¹Am-beryllium (1.45 GBq) source placed inside the shipping container.

Radioactive hot-spot localisation and identification using deep learning

The detection of radioactive hot-spots and the identification of the radionuclides present have been a challenge for the security sector, especially in situations involving chemical, biological, radiological, nuclear and explosive threats, as well as naturally occurring radioactive materials. This work proposes a solution based on Machine Learning techniques, with a focus on artificial neural networks (NNs), in order to localise, quantify and identify radioactive sources. Firstly, the created RHLnet model uses observations of radiological intensity counts and corresponding localisations to estimate the number, location and activity of unknown radioactive sources present in a given scenario. Then, another model (RHIdnet) gets the gamma spectrum of the sources to perform the identification of the corresponding radionuclides. For this, a training data set composed of simulated data is used during the training process, and so, using algorithms with the models already trained, fast and accurate predictions are achieved, ensuring the reliability of such a NN-based approach. The proposed solution is tested in simulated and real scenarios, with multiple sources, providing a low number of limitations, related to possible false negatives and false positives. Besides, the results have shown that the algorithm is scalable for very large regions, as well as for very small scenarios. Single and multiple isotope identification on each sample is explored, highlighting the benefits as well as possible improvements. Thus, NNs have demonstrated the capability of being an emerging tool with the potential to make a difference in the nuclear field, by helping in the development of novel techniques and new solutions in order to safeguard human lives.

Radiological Scouting, Monitoring and Inspection Using Drones

Human populations and natural ecosystems are bound to be exposed to ionizing radiation from the deposition of artificial radionuclides resulting from nuclear accidents, nuclear devices or radiological dispersive devices (“dirty bombs”). On the other hand, Naturally Occurring Radioactive Material industries such as phosphate production or uranium mining, contribute to the on site storage of residuals with enhanced concentrations of natural radionuclides. Therefore, in the context of the European agreements concerning nuclear energy, namely the European Atomic Energy Community Treaty, monitoring is an essential feature of the environmental radiological surveillance. In this work, we obtain 3D maps from outdoor scenarios, and complete such maps with measured radiation levels and with its radionuclide signature. In such scenarios, we face challenges such as unknown and rough terrain, limited number of sampled locations and the need for different sensors and therefore different tasks. We propose a radiological solution for scouting, monitoring and inspecting an area of interest, using a fleet of drones and a controlling ground station. First, we scout an area with a Light Detection and Ranging sensor onboard a drone to accurately 3D-map the area. Then, we monitor that area with a Geiger–Müller Counter at a low-vertical distance from the ground to produce a radiological (heat)map that is overlaid on the 3D map of the scenario. Next, we identify the hotspots of radiation, and inspect them in detail using a drone by landing on them, to reveal its radionuclide signature using a Cadmium–Zinc–Telluride detector. We present the algorithms used to implement such tasks both at the ground station and on the drones. The three mission phases were validated using actual experiments in three different outdoor scenarios. We conclude that drones can not only perform the mission efficiently, but in general they are faster and as reliable as personnel on the ground.

Advantages of Gamma-Radiometric and Spectrometric Low-Altitude Geophysical Surveys by Unmanned Aerial Systems with Small Scintillation Detectors

Unmanned aerial systems (UAS) for airborne gamma-ray surveys in radioecological and geological research are being increasingly used, since they provide radiation safety for personnel and high survey performance. Improvement of detection modules is one of the main directions in which UAS-gamma is developing. Semiconductor detectors are used increasingly as they have a small mass and are convenient for light unmanned aerial vehicles (UAVs). Simultaneously, in our opinion, the potential of traditional scintillation detectors is not exhausted because they are cheaper and more affordable. Radiometric and spectrometric detection modules based on scintillation detectors can even be created at home. The main disadvantage of scintillation detectors is the need for large crystals with significant mass to obtain high data quality. Traditional aerial gamma surveys with operated aircraft systems use scintillation detectors with a volume of tens or hundreds of litres. In this paper, we present the comparison result of radiometric and spectrometric surveys with small volume detectors made at different altitudes and ground surveys. We prove that with properly designed and applied ultralight UAS for aerial gamma spectrometry it is possible to obtain high-quality and informative data.

State-of-the-Art Mobile Radiation Detection Systems for Different Scenarios

In the last decade, the development of more compact and lightweight radiation detection systems led to their application in handheld and small unmanned systems, particularly air-based platforms. Examples of improvements are: the use of silicon photomultiplier-based scintillators, new scintillating crystals, compact dual-mode detectors (gamma/neutron), data fusion, mobile sensor networks, cooperative detection and search. Gamma cameras and dual-particle cameras are increasingly being used for source location. This study reviews and discusses the research advancements in the field of gamma-ray and neutron measurements using mobile radiation detection systems since the Fukushima nuclear accident. Four scenarios are considered: radiological and nuclear accidents and emergencies; illicit traffic of special nuclear materials and radioactive materials; nuclear, accelerator, targets, and irradiation facilities; and naturally occurring radioactive materials monitoring-related activities. The work presented in this paper aims to: compile and review information on the radiation detection systems, contextual sensors and platforms used for each scenario; assess their advantages and limitations, looking prospectively to new research and challenges in the field; and support the decision making of national radioprotection agencies and response teams in respect to adequate detection system for each scenario. For that, an extensive literature review was conducted.