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result(s) for
"radioactive sources"
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Virtual radioactive source system for exercises modeling high doses
This article presents the possibilities of working in a virtual high-dose rate field following a procedure developed at the Nuclear Security Department of the Centre for Energy Research (EK NSD) in Budapest. Real-life simulation of a radiation survey and a radiation risk assessment as well as searching for lost radioactive sources, monitoring surface contamination (SC), in addition to localizing and overseeing materials out of regulatory control (e.g., at a radiological crime scene) are only possible under inactive conditions or in low-dose rate environments in accordance with the as low as resonably achievable (ALARA) principle. A virtual radioactive source system (VRSS) developed at the Nuclear Security Department (NSD) makes it possible to simulate “measured” values very accurately, even in a high-dose rate environment, but without exposing trainees to radiation hazards.
Journal Article
Study on Ignition Time of Radiation Cargo in Irradiation Room under Stuck Radioactive Sources
Ignition temperatures of common radiation cargo in irradiation room were measured through the experiments, minimum ignition temperature is 210 °C. In order to discuss the temperature variation and temperature field under stuck radioactive sources, the fire scenario was presented and simulated by FDS. The results show that temperatures rise rapidly when stuck radioactive source broke out within an hour. As the growth of the time, temperatures in irradiation room are rising, but the rising rate is slowing. The temperature field in the irradiation room tends to be the same after three hours. The stuck radioactive source occurred after 2.4 days later, local temperatures can reach 210 °C, and radiation cargo may be ignited.
Journal Article
Autonomous Search of Radioactive Sources through Mobile Robots
The research of robotic autonomous radioactivity detection or radioactive source search plays an important role in the monitoring and disposal of nuclear safety and biological safety. In this paper, a method for autonomously searching for radioactive sources through mobile robots was proposed. In the method, by using a partially observable Markov decision process (POMDP), the search of autonomous unknown radioactive sources was realized according to a series of radiation information measured by mobile robot. First, the factors affecting the accuracy of radiation measurement during the robot’s movement were analyzed. Based on these factors, the behavior set of POMDP was designed. Secondly, the parameters of the radioactive source were estimated in the Bayesian framework. In addition, through the reward strategy, autonomous navigation of the robot to the position of the radiation source was achieved. The search algorithm was simulated and tested, and the TurtleBot robot platform was used to conduct a real search experiment on the radio source Cs-137 with an activity of 37 MBq indoors. The experimental results showed the effectiveness of the method. Additionally, from the experiments, it could been seen that the robot was affected by the linear velocity, angular velocity, positioning accuracy and the number of measurements in the process of autonomous search for the radioactive source. The proposed mobile robot autonomous search method can be applied to the search for lost radioactive sources, as well as for the leakage of substances (nuclear or chemical) in nuclear power plants and chemical plants.
Journal Article
Use of Multi-Rotor Unmanned Aerial Vehicles for Radioactive Source Search
In recent years, many radioactive sources have been lost or stolen during use or transportation. When the radioactive source is lost or stolen, it is challenging but imperative to quickly locate the source before it causes damage. Nowadays, source search based on fixed-wing unmanned aerial vehicles (UAVs) can significantly improve search efficiency, but this approach has higher requirements for the activity of the uncontrolled radioactive source and the take-off sites. The aim of this study was to design and demonstrate a platform that uses low-cost multi-rotor UAVs to automatically and efficiently search for uncontrolled radioactive sources even with lower activity. The hardware of this platform consists of a multi-rotor UAV, radiation detection sensor, main control module, gimbal and camera, and ground control station. In the search process, the ground control station and UAV communicate wirelessly in real time. To accommodate different search scenarios, the study proposed three search algorithms with a theoretical comparison. Then, field experiments based on the traversal search algorithm showed that the search system based on multi-rotor UAVs could effectively and accurately conduct contour mapping of a region and locate the radioactive source with an error of 0.32 m. The platform and algorithms enable accurate and efficient searching of radioactive sources, providing an innovative demonstration of future environmental risk assessment and management.
Journal Article
Machine learning for localization of radioactive sources via a distributed sensor network
In this paper, we focus on the detection and localization of radioactive sources by exploiting supervised machine learning. Machine learning is utilized in a wide variety of applications due to its effectiveness in prediction and autonomous decision-making. However, applying machine learning would only be effective when representative features for the application can be acquired, through which learning algorithms can be trained. Hence, first, we present a feature extraction technique for radioactive source localization, and then propose a parameter estimation method via machine learning. A distributed sensor network is employed to assist in estimating the radioactive source’s location and intensity. We propose a feature extraction method that evaluates a feature vector using the reading and position of each sensor located in a region where a radiation source is detected. The feature extraction is based on a data fusion process, where a single feature value is provided to represent both the reading value and position coordinates corresponding to a given sensor. After the feature extraction, we apply the decision tree machine learning method for regression to localize a radioactive source. To examine the effectiveness of the proposed work, a performance comparison is carried out with recent existing methods in terms of the estimation accuracy and the execution time. Experimental results show that the proposed algorithm provides accurate source intensity estimation and achieves a good compromise between localization accuracy and execution time.
Journal Article
RESULTS OF TEST CAMPAIGNS COMPARING SOME FIELD INSTRUMENTATIONS USED BY FIRST RESPONDERS DURING RADIOLOGICAL AND NUCLEAR EMERGENCIES
The authors in this work present the results of a comparison between field or portable instruments that can be used by first responders in case of a radiological or nuclear emergency. The comparison is performed through the use of four sources with different shapes and nature (a solid cylindrical shape of Am-241; a stone with copper matrix and extraction material ofTh-232; a railway ballast stone of Cs-137; and a needle of Ra-226) and with four instruments with different detection technologies (HDS-101, FH-40, AutoMess 6150AD andXMMIRA). The tests with the portable instruments are performed by placing the sources at 1 m distance and in contact with the instruments to report the difference in reaction, data collection and determining indications of the best solution for the emergency.
Journal Article
PbF2 as a key modulator of gamma radiation shielding in PbO–PbF2–B2O3–SiO2 glass systems
The radiation shielding properties of lead fluoroborate glasses containing 30 mol% SiO
2
have been examined using Phy-X software. The mass attenuation coefficient (MAC) results demonstrated that the tetsed glasses are good attenuator against the low energy radiation, and their attenuation performance diminishes as the energy of the radiation increases. The MAC increases with the addition of PbF
2
, and the difference in MAC between the glasses with different PbF
2
contents is significantly high at lower energy region. At high energy, the difference in MAC between the glasses is small which suggested that as the energy of the photons increases, the MAC for these glasses tend to converge. The linear attenuation coefficient (LAC) for the glasses is investigated and we found that the LAC for the glass with 49 mol% of PbF
2
is 58% bigger than that of the glass with 21 mol%. We investigated the average half value layer (
HVL
¯
) for the tested glasses when exposed to
137
Cs and
60
Co and the results showed that the values of
HVL
¯
for
60
Co are about double those for
137
Cs for all glasses, which suggests that the energies emitted by
60
Co in general penetrate the glass sample more deeply in comparison with the photons emitted by
137
Cs. The mean free path (MFP) of the glasses against the density shows the desirable properties of PbF
2
, as the MFP values decrease when the density increases.
Journal Article
Radioactive source search problem and optimisation model based on meta-heuristic algorithm
In the process of rational development and utilisation of nuclear energy, people often face nuclear accidents such as lost and stolen radioactive sources; so, the means of searching for these sources quickly in highly radioactive environments is an important security challenge. In the past, these jobs were limited to workers specialising in nuclear technology. They used gamma-ray detection equipment to search for radioactive sources, but the search efficiency was low. The main purpose of this article is to design a meta-heuristic algorithm based on imitating professional technicians to locate radioactive sources in a computer-aided manner. At the same time, due to the complexity that may characterise the actual search, the search strategy must be optimised. The article established an intelligent random search model with human thinking. Finally, it was proved based on the mathematical theory that the complexity of the model search algorithm is linear, and the simulation experiment results show that the optimisation algorithm has good efficiency and fault tolerance.
Journal Article