2023

Jump to: 2022, 2021

19 pages, 8642 KiB

Open AccessArticle

A Portable Three-Layer Compton Camera for Wide-Energy-Range Gamma-ray Imaging: Design, Simulation and Preliminary Testing

by Jipeng Zhang, Xiong Xiao, Ye Chen, Bin Zhang, Xinhua Ma, Xianyun Ai and Jinglun Li

Sensors 2023, 23(21), 8951; https://doi.org/10.3390/s23218951 - 03 Nov 2023

Cited by 1 | Viewed by 836

Abstract

(1) Background: The imaging energy range of a typical Compton camera is limited due to the fact that scattered gamma photons are seldom fully absorbed when the incident energies are above 3 MeV. Further improving the upper energy limit of gamma-ray imaging has [...] Read more.

(1) Background: The imaging energy range of a typical Compton camera is limited due to the fact that scattered gamma photons are seldom fully absorbed when the incident energies are above 3 MeV. Further improving the upper energy limit of gamma-ray imaging has important application significance in the active interrogation of special nuclear materials and chemical warfare agents, as well as range verification of proton therapy. (2) Methods: To realize gamma-ray imaging in a wide energy range of 0.3~7 MeV, a principle prototype, named a portable three-layer Compton camera, is developed using the scintillation detector that consists of an silicon photomultiplier array coupled with a Gd₃Al₂Ga₃O₁₂:Ce pixelated scintillator array. Implemented in a list-mode maximum likelihood expectation maximization algorithm, a far-field energy-domain imaging method based on the two interaction events is applied to estimate the initial energy and spatial distribution of gamma-ray sources. The simulation model of the detectors is established based on the Monte Carlo simulation toolkit Geant4. The reconstructed images of a ¹³³Ba, a ¹³⁷Cs and a ⁶⁰Co point-like sources have been successfully obtained with our prototype in laboratory tests and compared with simulation studies. (3) Results: The proportion of effective imaging events accounts for about 2%, which allows our prototype to realize the reconstruction of the distribution of a 0.05 μSv/h ¹³⁷Cs source in 10 s. The angular resolution for resolving two ¹³⁷Cs point-like sources is 15°. Additional simulated imaging of the 6.13 MeV gamma-rays from 14.1 MeV neutron scattering with water preliminarily demonstrates the imaging capability for high incident energy. (4) Conclusions: We conclude that the prototype has a good imaging performance in a wide energy range (0.3~7 MeV), which shows potential in several MeV gamma-ray imaging applications. Full article

► Show Figures

Figure 1

20 pages, 5774 KiB

Open AccessArticle

Compact Back-End Electronics with Temperature Compensation and Efficient Data Management for In Situ SiPM-Based Radiation Detection

by Nile E. J. Dixon, Stephen D. Monk, James Graham and David Cheneler

Sensors 2023, 23(8), 4053; https://doi.org/10.3390/s23084053 - 17 Apr 2023

Cited by 1 | Viewed by 1741

Abstract

A compact back-end interface for silicon photomultipliers (SiPMs) implementing Zener diode-based temperature compensation has been developed for the remote detection of beta and gamma radiation. Remote detection is facilitated by the development of an efficient data management system utilising MySQL database storage for [...] Read more.

A compact back-end interface for silicon photomultipliers (SiPMs) implementing Zener diode-based temperature compensation has been developed for the remote detection of beta and gamma radiation. Remote detection is facilitated by the development of an efficient data management system utilising MySQL database storage for recording periodic spectra data for wireless access over a private Wi-Fi network. A trapezoidal peak shaping algorithm has been implemented on an FPGA for the continuous conversation of pulses from the SiPM, signifying the detection of a radiological particle, into spectra. This system has been designed to fit within a 46 mm cylindrical diameter for in situ characterization, and can be attached to one or more SiPMs used in conjunction with a range of scintillators. LED blink tests have been used to optimise the trapezoidal shaper coefficients to maximise the resolution of the recorded spectra. Experiments with an array of SiPMs integrated with a NaI(Tl) scintillator exposed to sealed sources of Co-60, Cs-137, Na-22 and Am-241 have shown that the detector achieves a peak efficiency of 27.09 ± 0.13% for a gamma peak at 59.54 keV produced by Am-241, and a minimum energy resolution (Delta E/E) of 4.27 ± 1.16% for the 1332.5 keV gamma peak from Co-60. Full article

► Show Figures

Figure 1

13 pages, 2095 KiB

Open AccessArticle

Emergency Management in the Event of Radiological Dispersion in an Urban Environment

by Edoardo Cavalieri d’Oro and Andrea Malizia

Sensors 2023, 23(4), 2029; https://doi.org/10.3390/s23042029 - 10 Feb 2023

Cited by 3 | Viewed by 1582

Abstract

Dispersion of a radiological source is a complex scenario in terms of first response, especially when it occurs in an urban environment. The authors in this paper designed, simulated, and analyzed the data from two different scenarios with the two perspectives of an [...] Read more.

Dispersion of a radiological source is a complex scenario in terms of first response, especially when it occurs in an urban environment. The authors in this paper designed, simulated, and analyzed the data from two different scenarios with the two perspectives of an unintentional fire event and a Radiological Dispersal Device (RDD) intentional explosion. The data of the simulated urban scenario are taken from a real case of orphan sources abandoned in a garage in the center of the city of Milan (Italy) in 2012. The dispersion and dose levels are simulated using Parallel Micro Swift Spray (PMSS) software, which takes into account the topographic and meteorological information of the reference scenarios. Apart from some differences in the response system of the two scenarios analyzed, the information provided by the modeling technique used, compared to other models not able to capture the actual urban and meteorological contexts, make it possible to modulate a response system that adheres to the real impact of the scenario. The authors, based on the model results and on the evidence provided by the case study, determine the various countermeasures to adopt to mitigate the impact for the population and to reduce the risk factors for the first responders. Full article

► Show Figures

Figure 1

10 pages, 499 KiB

Open AccessPerspective

Sievert or Gray: Dose Quantities and Protection Levels in Emergency Exposure

by Chiara Ferrari, Guglielmo Manenti and Andrea Malizia

Sensors 2023, 23(4), 1918; https://doi.org/10.3390/s23041918 - 08 Feb 2023

Cited by 2 | Viewed by 1818

Abstract

Mitigation or even elimination of adverse effects caused by ionizing radiation is the main scope of the radiation protection discipline. The interaction of radiation with living matter is quantified and correlated with biological effects by dose. The Sievert is the most well-known quantity, [...] Read more.

Mitigation or even elimination of adverse effects caused by ionizing radiation is the main scope of the radiation protection discipline. The interaction of radiation with living matter is quantified and correlated with biological effects by dose. The Sievert is the most well-known quantity, and it is used with the equivalent and effective dose to minimize stochastic effects. However, Gray is the reference quantity for sizing tissue reactions that could occur under high-exposure conditions such as in a radiation emergency. The topics addressed in this review are the choice to move from Sievert to Gray, how the operational quantities for environmental and individual monitoring of the detectors should consider such a change of units, and why reference levels substitute dose levels in emergency exposure. Full article

► Show Figures

Figure 1

2022

Jump to: 2023, 2021

33 pages, 14005 KiB

Open AccessArticle

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

by Luís Marques, Luís Félix, Gonçalo Cruz, Vasco Coelho, João Caetano, Alberto Vale, Carlos Cruz, Luís Alves and Pedro Vaz

Sensors 2023, 23(1), 329; https://doi.org/10.3390/s23010329 - 28 Dec 2022

Cited by 3 | Viewed by 3245

Abstract

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 [...] Read more.

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. Full article

► Show Figures

Figure 1

11 pages, 3825 KiB

Open AccessCommunication

Real-Time Monitoring Method for Radioactive Substances Using Monolithic Active Pixel Sensors (MAPS)

by Yongchao Han, Shoulong Xu and Youjun Huang

Sensors 2022, 22(10), 3919; https://doi.org/10.3390/s22103919 - 22 May 2022

Cited by 1 | Viewed by 1805

Abstract

This study presents a real-time monitoring technique for radioactive substances that meets safety management needs. We studied the accumulation characteristics of radiation response signals of monolithic active pixel sensors (MAPSs) based on their response and discrimination ability to gamma (γ) photon or neutron [...] Read more.

This study presents a real-time monitoring technique for radioactive substances that meets safety management needs. We studied the accumulation characteristics of radiation response signals of monolithic active pixel sensors (MAPSs) based on their response and discrimination ability to gamma (γ) photon or neutron radiation. The radiation status of the radioactive substances was determined by monitoring the accumulation data of radiation responses. As per the results, Am-Be and ²⁵²Cf radiation response signals are primarily concentrated in the range of 0–70 pixels. Response signals of ⁶⁰Co and ¹³⁷Cs γ-ray were concentrated in two regions; there was a peak in the region with a pixel value of less than 50, and a plateau in the region with a pixel value of more than 75. Therefore, the results are able to discriminate between spectra. Furthermore, we designed a radioactivity monitoring system that is able to examine multiple radioactive materials. Its working principle is that a change in the accumulation of radioactivity monitoring data indicates a radiation change during the last accumulation cycle. This study provides vital technical support for the long-term supervision of radioactive substances. Full article

► Show Figures

Figure 1

17 pages, 3196 KiB

Open AccessArticle

GEANT4 Simulation for Radioactive Particle Tracking (RPT) Technique

by Ahmed A. Alghamdi, Thaar M. Aljuwaya, Abdullah S. Alomari and Muthanna H. Al-Dahhan

Sensors 2022, 22(3), 1223; https://doi.org/10.3390/s22031223 - 05 Feb 2022

Cited by 3 | Viewed by 3653

Abstract

In the past two decades, the radioactive particle tracking (RPT) measurement technique has been proven to visualize flow fields of most multiphase flow systems of industrial interest. The accuracy of RPT, and hence the data obtained, depend largely on the calibration process, which [...] Read more.

In the past two decades, the radioactive particle tracking (RPT) measurement technique has been proven to visualize flow fields of most multiphase flow systems of industrial interest. The accuracy of RPT, and hence the data obtained, depend largely on the calibration process, which stands here as a basis for two subsequent processes: tracking and reconstruction. However, limitations in the RPT calibration process can be found in different experimental constrains and in assumptions made in the classical Monte Carlo approach used to simulate number of counts received by the detectors. Therefore, in this work, we applied a GEANT4-based Monte Carlo code to simulate the RPT calibration process for an investigated multiphase flow system (i.e., gas–liquid bubble column). The GEANT4 code was performed to simulate the number of counts received by 28 scintillation detectors for 931 known tracer positions while capturing all the types of photon interaction and overcoming solids’ angle limitations in classical approaches. The results of the simulation were validated against experimental data obtained using an automated RPT calibration device. The results showed a good agreement between the simulated and experimental counts, where the maximum absolute average relative deviation detected was about 5%. The GEANT4 model typically predicted the number of counts received by all the detectors; however, it over-estimated the counts when the number of primary events applied in the model was not the optimal. Full article

► Show Figures

Figure 1

18 pages, 4500 KiB

Open AccessArticle

A High-Performance Gamma Spectrometer for Unmanned Systems Based on Off-the-Shelf Components

by Andrea Chierici, Andrea Malizia, Daniele Di Giovanni, Riccardo Ciolini and Francesco d’Errico

Sensors 2022, 22(3), 1078; https://doi.org/10.3390/s22031078 - 29 Jan 2022

Cited by 9 | Viewed by 3680

Abstract

Since the Fukushima Daiichi Nuclear Power Plant accident in March 2011, the technology available for unmanned aerial vehicles (UAVs) for radiation monitoring has improved greatly. Remote access to radiation-contaminated areas not only eliminates unnecessary exposure of civilians or military personnel, but also allows [...] Read more.

Since the Fukushima Daiichi Nuclear Power Plant accident in March 2011, the technology available for unmanned aerial vehicles (UAVs) for radiation monitoring has improved greatly. Remote access to radiation-contaminated areas not only eliminates unnecessary exposure of civilians or military personnel, but also allows workers to explore inaccessible places. Hazardous levels of radioactive contamination can be expected as a result of accidents in the nuclear power industry or as a result of the intentional release of radioactive materials for terrorist purposes (dirty bombs, building contamination, etc.). The possibility to detect, identify, and characterize radiation and nuclear material using mobile and remote sensing platforms is a common requirement in the radiation sensing community. The technology has applications in homeland security and law enforcement, customs and border protection, nuclear power plant safety and security, nuclear waste monitoring, environmental recovery, and the military. In this work, the authors have developed, implemented, and characterized a gamma-ray detection and spectroscopy system capable of operating on a UAV. The system was mainly developed using open-source software and affordable hardware components to reduce development and maintenance costs and provide satisfactory performance as a detection instrument. The designed platform can be used to perform mapping or localization tasks to improve the risk assessment process for first responders during the management of radiological and nuclear incidents. First, the design process of the system is described; the result of the characterization of the platform is then presented together with the use of the prototype installed on a UAV in an exercise simulating a radiological and nuclear contamination scenario. Full article

► Show Figures

Figure 1

15 pages, 2832 KiB

Open AccessArticle

Novel Algorithm for Radon Real-Time Measurements with a Pixelated Detector

by Alessandro Rizzo, Francesco Cardellini, Claudio Poggi, Enrico Borra, Luca Ciciani, Livio Narici, Luciano Sperandio and Ignazio Vilardi

Sensors 2022, 22(2), 516; https://doi.org/10.3390/s22020516 - 10 Jan 2022

Cited by 1 | Viewed by 2552

Abstract

Nowadays, radon gas exposure is considered one of the main health concerns for the population because, by carrying about half the total dose due to environmental radioactivity, it is the second cause of lung cancer after smoking. Due to a relatively long half-life [...] Read more.

Nowadays, radon gas exposure is considered one of the main health concerns for the population because, by carrying about half the total dose due to environmental radioactivity, it is the second cause of lung cancer after smoking. Due to a relatively long half-life of 3.82 days, the chemical inertia and since its parent Ra-226 is largely diffuse on the earth’s crust and especially in the building materials, radon can diffuse and potentially saturate human habitats, with a concentration that can suddenly change during the 24 h day depending on temperature, pressure, and relative humidity. For such reasons, ‘real-time’ measurements performed by an active detector, possibly of small dimensions and a handy configuration, can play an important role in evaluating the risk and taking the appropriate countermeasures to mitigate it. In this work, a novel algorithm for pattern recognition was developed to exploit the potentialities of silicon active detectors with a pixel matrix structure to measure radon through the α emission, in a simple measurement configuration, where the device is placed directly in air with no holder, no collection filter or electrostatic field to drift the radon progenies towards the detector active area. This particular measurement configuration (dubbed as bare) requires an α/β-discrimination method that is not based on spectroscopic analysis: as the gas surrounds the detector the α particles are emitted at different distances from it, so they lose variable energy amount in air depending on the traveled path-length which implies a variable deposited energy in the active area. The pixels matrix structure allows overcoming this issue because the interaction of α, β and γ particles generate in the active area of the detector clusters (group of pixels where a signal is read) of different shape and energy dispersion. The novel algorithm that exploits such a phenomenon was developed using a pixelated silicon detector of the TimePix family with a compact design. An α (Am-241) and a β (Sr-90) source were used to calibrate the algorithm and to evaluate its performances in terms of β rejection capability and α recognition efficiency. Successively, the detector was exposed to different radon concentrations at the ENEA-INMRI radon facility in ‘bare’ configuration, in order to check the linearity of the device response over a radon concentration range. The results for this technique are presented and discussed, highlighting the potential applications especially the possibility to exploit small and handy detectors to perform radon active measurements in the simplest configuration. Full article

► Show Figures

Figure 1

2021

Jump to: 2023, 2022

23 pages, 2067 KiB

Open AccessReview

Application and Development of Noncontact Detection Method of α-Particles Based on Radioluminescence

by Zeqian Wu, Jinxing Cheng, Mei Xu, Qingbo Wang, Ai Yu, Yue Zhang, Weiwei Wen, Youpeng Wu and Zhongfeng Tang

Sensors 2022, 22(1), 202; https://doi.org/10.3390/s22010202 - 28 Dec 2021

Cited by 2 | Viewed by 1966

Abstract

The detection of α particles is of great significance in military and civil nuclear facility management. At present, the contact method is mainly used to detect α particles, but its shortcomings limit the broad application of this method. In recent years, preliminary research [...] Read more.

The detection of α particles is of great significance in military and civil nuclear facility management. At present, the contact method is mainly used to detect α particles, but its shortcomings limit the broad application of this method. In recent years, preliminary research on noncontact α-particle detection methods has been carried out. In this paper, the theory of noncontact α-particles detection methods is introduced and studied. We also review the direct detection and imaging methods of α particles based on the different wavelengths of fluorescence photons, and analyze the application and development of this method, providing an important reference for researchers to carry out related work. Full article

► Show Figures

Figure 1

14 pages, 5949 KiB

Open AccessArticle

Discrete Convolution-Based Energy Spectrum Configuring Method for the Analysis of the Intrinsic Radiation of ¹⁷⁶Lu

by Kilyoung Ko, Hyunwoong Choi, Yongsun Yi, Wonku Kim, Junhyeok Kim, Jisung Hwang, Eunbie Ko and Gyuseong Cho

Sensors 2021, 21(21), 7040; https://doi.org/10.3390/s21217040 - 23 Oct 2021

Cited by 3 | Viewed by 2300

Abstract

There has been considerable interest in inorganic scintillators based on lutetium due to their favorable physical properties. Despite their advantages, lutetium-based scintillators could face issues because of the natural occurring radioisotope of ¹⁷⁶Lu that is contained in natural lutetium. In order to [...] Read more.

There has been considerable interest in inorganic scintillators based on lutetium due to their favorable physical properties. Despite their advantages, lutetium-based scintillators could face issues because of the natural occurring radioisotope of ¹⁷⁶Lu that is contained in natural lutetium. In order to mitigate its potential shortcomings, previous works have studied to understand the energy spectrum of the intrinsic radiation of ¹⁷⁶Lu (IRL). However, few studies have focused on the various principal types of photon interactions with matter; in other words, only the full-energy peak according to the photoelectric effect or internal conversion have been considered for understanding the energy spectrum of IRL. Thus, the approach we have used in this study considers other principal types of photon interactions by convoluting each energy spectrum with combinations for generating the spectrum of the intrinsic radiation of ¹⁷⁶Lu. From the results, we confirm that the method provides good agreement with the experiment. A significant contribution of this study is the provision of a new approach to process energy spectra induced by mutually independent radiation interactions as a single spectrum. Full article

► Show Figures

Figure 1

13 pages, 940 KiB

Open AccessArticle

Convolutional Neural Networks for Challenges in Automated Nuclide Identification

by Anthony N. Turner, Carl Wheldon, Tzany Kokalova Wheldon, Mark R. Gilbert, Lee W. Packer, Jonathan Burns and Martin Freer

Sensors 2021, 21(15), 5238; https://doi.org/10.3390/s21155238 - 03 Aug 2021

Cited by 8 | Viewed by 2937

Abstract

Improvements in Radio-Isotope IDentification (RIID) algorithms have seen a resurgence in interest with the increased accessibility of machine learning models. Convolutional Neural Network (CNN)-based models have been developed to identify arbitrary mixtures of unstable nuclides from gamma spectra. In service of this, methods [...] Read more.

Improvements in Radio-Isotope IDentification (RIID) algorithms have seen a resurgence in interest with the increased accessibility of machine learning models. Convolutional Neural Network (CNN)-based models have been developed to identify arbitrary mixtures of unstable nuclides from gamma spectra. In service of this, methods for the simulation and pre-processing of training data were also developed. The implementation of 1D multi-class, multi-label CNNs demonstrated good generalisation to real spectra with poor statistics and significant gain shifts. It is also shown that even basic CNN architectures prove reliable for RIID under the challenging conditions of heavy shielding and close source geometries, and may be extended to generalised solutions for pragmatic RIID. Full article

► Show Figures

Figure 1

20 pages, 7695 KiB

Open AccessArticle

Pseudo-Gamma Spectroscopy Based on Plastic Scintillation Detectors Using Multitask Learning

by Byoungil Jeon, Junha Kim, Eunjoong Lee, Myungkook Moon and Gyuseong Cho

Sensors 2021, 21(3), 684; https://doi.org/10.3390/s21030684 - 20 Jan 2021

Cited by 11 | Viewed by 3041

Abstract

Although plastic scintillation detectors possess poor spectroscopic characteristics, they are extensively used in various fields for radiation measurement. Several methods have been proposed to facilitate their application of plastic scintillation detectors for spectroscopic measurement. However, most of these detectors can only be used [...] Read more.

Although plastic scintillation detectors possess poor spectroscopic characteristics, they are extensively used in various fields for radiation measurement. Several methods have been proposed to facilitate their application of plastic scintillation detectors for spectroscopic measurement. However, most of these detectors can only be used for identifying radioisotopes. In this study, we present a multitask model for pseudo-gamma spectroscopy based on a plastic scintillation detector. A deep- learning model is implemented using multitask learning and trained through supervised learning. Eight gamma-ray sources are used for dataset generation. Spectra are simulated using a Monte Carlo N-Particle code (MCNP 6.2) and measured using a polyvinyl toluene detector for dataset generation based on gamma-ray source information. The spectra of single and multiple gamma-ray sources are generated using the random sampling technique and employed as the training dataset for the proposed model. The hyperparameters of the model are tuned using the Bayesian optimization method with the generated dataset. To improve the performance of the deep learning model, a deep learning module with weighted multi-head self-attention is proposed and used in the pseudo-gamma spectroscopy model. The performance of this model is verified using the measured plastic gamma spectra. Furthermore, a performance indicator, namely the minimum required count for single isotopes, is defined using the mean absolute percentage error with a criterion of 1% as the metric to verify the pseudo-gamma spectroscopy performance. The obtained results confirm that the proposed model successfully unfolds the full-energy peaks and predicts the relative radioactivity, even in spectra with statistical uncertainties. Full article

► Show Figures

Figure 1

Journal Menu

Journal Browser

Measurements, Instrumentation, Sensing and Simulation Techniques for the Detection of Radiation

Share This Topical Collection

Editors

Topical Collection Information

Keywords

Published Papers (13 papers)

2023

Jump to: 2022, 2021

2022

Jump to: 2023, 2021

2021

Jump to: 2023, 2022

Further Information

Guidelines

MDPI Initiatives

Follow MDPI