Detection Of Special Nuclear Material Research Articles

Artificial Intelligence Detection System of Radioactive Nanocomposites in Liquid-Filled Containers for Nuclear Security

Nuclear terrorism resulting from the illicit trafficking of nuclear and radioactive materials consists of a serious threat against the security of countries. Hence, the transportation of hidden nuclear materials in large-scale cargos has emerged as an important public issue that requires immediate attention. The security architecture should merge the nuclear security systems and execute a procedure for the detection of nuclear and radioactive materials. In this regard, the detection of special nuclear materials (SNMs) in liquid-filled cargo containers is an essential matter of homeland security because of the difficulties imposed by liquids in performing efficient manual inspection. This paper presents a new artificial intelligence (AI) system implemented with fuzzy logic tools for detecting composite materials, including Pb-Th, Pb-U, and Pb-Co, in containers filled with water by utilizing optical signature information obtained with COMSOL. The developed AI system and its underlying method are validated for a scenario of detecting Pb-Th, Pb-U, and Pb-Co in water-filled containers.

9 MV LINAC Photoneutron Interrogation of Uranium With Advanced Acoustically Tensioned Metastable Fluid Detectors

Abstract Active special nuclear material (SNM) photoneutron interrogation research with acoustically tensioned metastable fluid detector (ATMFD) sensor technology is discussed, which provides evidence for enabling real-time detection of SNM even when deployed under extreme 15,000 R h−1 (9 MeV endpoint) X-ray beams. Experiments to detect 3.2 kg depleted uranium (DU) are described with the use of two designs of the economical acoustically tensioned metastable fluid detector (E-ATMFD), viz., E-ATMFD.Ver.0 and E-ATMFD.Ver.1, respectively, at standoffs ranging from 0.1 m to 10 m—including with the E-ATMFD directly within the interrogating beam. Under similar conditions and with 100% photon rejection (i.e., 0 cpm with beam on, and without SNM), the E-ATMFD.Ver.1 design operating at ∼0.9 W of drive power was shown capable of ∼6× (600%) higher gain over E-ATMFD.Ver.0 operating at ∼7 W (with beam on and with SNM). The sensitivity gain rises to ∼27× (i.e., 2700%) with the E-ATMFD.Ver.1 operating at 0.99 W and a background count rate of ∼1 cpm. The E-ATMFD.Ver.1 demonstrated 100% photon blindness (0 cpm) while operating at ∼0.56 W drive power and placed directly within the beam under 15,000 R/h; including the SNM target led to a count rate of up to 50 cpm—revealing the E-ATMFD.Ver.1 is potential field capable of detecting U-based SNMs within seconds from photofission neutron signals, even when deployed directly within the intense (15,000 R/h) high energy (9 MeV endpoint X-Ray) interrogating photon beam.

SNM Radiation Signature Classification Using Different Semi-Supervised Machine Learning Models

The timely detection of special nuclear material (SNM) transfers between nuclear facilities is an important monitoring objective in nuclear nonproliferation. Persistent monitoring enabled by successful detection and characterization of radiological material movements could greatly enhance the nuclear nonproliferation mission in a range of applications. Supervised machine learning can be used to signal detections when material is present if a model is trained on sufficient volumes of labeled measurements. However, the nuclear monitoring data needed to train robust machine learning models can be costly to label since radiation spectra may require strict scrutiny for characterization. Therefore, this work investigates the application of semi-supervised learning to utilize both labeled and unlabeled data. As a demonstration experiment, radiation measurements from sodium iodide (NaI) detectors are provided by the Multi-Informatics for Nuclear Operating Scenarios (MINOS) venture at Oak Ridge National Laboratory (ORNL) as sample data. Anomalous measurements are identified using a method of statistical hypothesis testing. After background estimation, an energy-dependent spectroscopic analysis is used to characterize an anomaly based on its radiation signatures. In the absence of ground-truth information, a labeling heuristic provides data necessary for training and testing machine learning models. Supervised logistic regression serves as a baseline to compare three semi-supervised machine learning models: co-training, label propagation, and a convolutional neural network (CNN). In each case, the semi-supervised models outperform logistic regression, suggesting that unlabeled data can be valuable when training and demonstrating value in semi-supervised nonproliferation implementations.

Detecting and characterizing special nuclear material for nuclear nonproliferation applications

There is an urgent need for new, better instrumentation and techniques for detecting and characterizing special nuclear material (SNM), i.e., highly enriched uranium and plutonium. The development of improved instruments and techniques requires experiments performed with the SNM itself, which is of limited availability. This paper describes the findings of experiments performed at the National Criticality Experiments Research Center conducted using new instruments and techniques on unclassified, kg-quantity SNM objects. These experiments, performed in the framework of the Department of Energy, National Nuclear Security Administration Consortium for Monitoring, Technology, and Verification, focused on detecting, characterizing, and localizing SNM samples with masses ranging from 3.3 to 13.8 kg, including plutonium and highly enriched uranium using prototype detectors and techniques. The work demonstrates SNM detection and characterization using recently-developed prototype detection systems. Specifically, we present new results in passive detection and imaging of plutonium and uranium objects using gamma-ray and dual particle (fast neutron and gamma-ray) imaging. We also present a new analysis of the delayed neutron emissions during active interrogation of uranium using a neutron generator.

Comparative study of the pulse shape discrimination (PSD) performance of pixelated stilbene and plastic scintillator (EJ-276) arrays for a coded-aperture-based hand-held dual-particle imager

As the demand for the detection of special nuclear materials (SNMs) increases, the use of imaging instruments that can sensitively image both gamma-ray and neutron signatures has become necessary. This study compared the pulse shape discrimination (PSD) performance of gamma/neutron events when employing either a pixelated stilbene or a plastic (EJ-276) scintillator array coupled to a silicon photomultiplier (SiPM) array in a dual-particle imager. The stilbene array allowed a lower energy threshold above which neutron and gamma-ray events can be clearly distinguished. A greater number of events can, therefore, be used when forming both gamma-ray and neutron images, which shortens the time required to acquire the images by nearly seven times.

Reconstruction of fast neutron direction in segmented organic detectors using deep learning

A method for reconstructing the direction of a fast neutron source using a segmented organic scintillator-based detector and deep learning model is proposed and analyzed. The model is based on recurrent neural network, which can be trained by a sequence of data obtained from an event recorded in the detector and suitably pre-processed. The performance of deep learning-based model is compared with the conventional double-scatter detection algorithm in reconstructing the direction of a fast neutron source. With the deep learning model, the uncertainty in source direction of 0.301 rad is achieved with 100 neutron detection events in a segmented cubic organic scintillator detector with a side length of 46 mm. To reconstruct the source direction with the same angular resolution as the double-scatter algorithm, the deep learning method requires 75% fewer events. Application of this method could augment the operation of segmented detectors operated in the neutron scatter camera configuration for applications such as special nuclear material detection.

Evaluation of a positron-emission-tomography-based SiPM readout for compact segmented neutron imagers

Gamma-ray emission from special nuclear material (SNM) is relatively easy to shield from detection using modest amounts of high-Z material. In contrast, fast-neutrons are much more penetrating and can escape relatively thick high-Z shielding without losing significant energy. Furthermore, fast neutrons provide a clear and unambiguous signature of the presence of SNM with few competing natural background sources. The challenge of detecting fast neutrons is twofold. First, the neutron flux from SNM are only a fraction of the corresponding gamma-ray flux. Second, fast neutrons can be difficult to differentiate from gamma rays. The ability to discriminate gamma rays from neutrons, combined with a neutron imaging capability, can in some situations enable the localization of SNM neutron sources distinct from background. With the developments of pulse-shape-sensitive plastic scintillators that offer excellent gamma-ray/neutron discrimination, and arrays of silicon photomultipliers combined with highly scalable and fast positron-emission-tomography (PET) multi-channel readout systems, field-deployable neutron imagers suitable for SNM detection might now be within reach. In this paper, we present a characterization of the performance of a recently available commercial PET-scanner readout, including its sensitivity to pulse-shape differences between fast neutrons and gamma rays, energy and timing resolution. We find that, while the pulse-shape discrimination is achievable with stilbene, further improvement of the readout is required to achieve it with the PSD-capable available plastic scintillators.

Modeling and Simulation of Radioactive Nanomaterials of Pb-U, Pb-Th, and Pb-Co in Water-Filled Containers for Nuclear Security Applications

In this paper, the optical properties of lead-thorium (Pb-Th), lead-uranium (Pb-U), and lead-cobalt (Pb-Co) nuclear nanoparticles in a container filled with water are simulated and modeled employing finite element analysis (FEA) for diverse particle sizes. The simulated absorption maxima of electronic excitations of nuclear nanoparticles such as Pb-U are red-shifted from 375 to 380 nm for the first peak, from 595 to 600 nm for the second peak, and from 730 to 740 nm for the third peak with increasing particle sizes from core U: 7 nm and shell Pb: 2 nm to core U: 9 nm and shell Pb: 2 nm. Moreover, the absorption peak of the Pb-Th and Pb-Co nanoparticles is red-shifted by increasing the particle size. The FEA-simulated optical band gap energies of Pb-Th, Pb-U, and Pb-Co nanoparticles were also obtained, and the data decreased with increasing the particle size. FEA-based simulations have disclosed restrictions intended for Pb-Th and Pb-Co nanoparticles size greater than 9 nm and for Pb-U nanoparticles size larger than 11 nm. The simulation method in this research enables the prediction of optical properties and contributes to the understanding and design of Pb-Th, Pb-U, and Pb-Co nanoparticles in the water container before manufacturing and functionalizing them. The work here is of particular interest in the nuclear security domain and in the nondestructive, remote detection of special nuclear materials (SNM) in water-filled cargo containers, whose manual inspection imposes physical and financial challenges.

Compact lightweight imager of both gamma rays and neutrons based on a pixelated stilbene scintillator coupled to a silicon photomultiplier array

Dual particle imaging, in which both neutrons and gamma-rays in the environment can be individually characterized, is particularly attractive for monitoring mixed radiation emitters such as special nuclear materials (SNM). Effective SNM localization and detection benefits from high instrument sensitivity so that real-time imaging or imaging with a limited number of acquired events is enabled. For portable applications, one also desires a dual particle imager (DPI) that is readily deployable. We have developed a hand-held type DPI equipped with a pixelated stilbene-silicon photomultiplier (SiPM) array module and low sampling-rate analog-to-digital converters (ADCs) processed via a multiplexed readout. The stilbene-SiPM array (12 × 12 pixels) is capable of effectively performing pulse shape discrimination (PSD) between gamma-ray and neutron events and neutron/gamma-ray source localization on the imaging plane, as demonstrated with 252Cf neutron/gamma and 137Cs gamma-ray sources. The low sampling rate ADCs connected to the stilbene-SiPM array module result in a compact instrument with high sensitivity that provides a gamma-ray image of a 137Cs source, producing 6.4 μR/h at 1 m, in less than 69 s. A neutron image for a 3.5 × 105 n/s 252Cf source can also be obtained in less than 6 min at 1 m from the center of the system. The instrument images successfully with field of view of 50° and provides angular resolution of 6.8°.

Deployment of a double scatter system for directional detection of background neutron radiation

The detection of special nuclear materials (SNM) requires the understanding of nuclear signatures that allow the discrimination against background. In particular, understanding neutron background characteristics such as count rates and energies and their correlations with environmental conditions and surroundings of measurement locations is important in enhancing SNM detection capabilities. The Mobile Imager of Neutrons for Emergency Responders (MINER) was deployed for 8 weeks in downtown San Francisco (CA) to study such neutron background characteristics in an urban environment. Of specific interest was the investigation of the impact of surrounding buildings on the neutron background count rates and to answer the question whether buildings act as absorber of neutrons or as sources via the so-called ship effect. MINER consists of 16 liquid scintillator detector elements and can be operated as a neutron spectrometer, as a neutron imager, or simply as a counter of fast neutrons. As expected, the neutron background rate was found to be inversely proportional to the atmospheric pressure. In the energy range where MINER is most sensitive, approximately 1–10 MeV, it was found that the shape of the detected background spectrum is similar to that of a detected fission spectrum, indicating the limited discrimination power of the neutron energy. The similarities between the detected background neutron spectrum and fission sources makes it difficult to discriminate SNM from background based solely on the energies observed. The images produced using maximum likelihood expectation maximization revealed that neutrons preferentially are coming from areas in the environment that have open sky, indicating that the surrounding buildings act as absorbers of neutrons rather than sources as expected by the ship effect. The inherent properties of a neutron scatter camera limit the achievable image quality and the effective deployment to systematically map neutron background signatures due to the low count rate.

Investigation of the use of Coincidences Between Fast Neutrons and Gamma Rays for the Detection of Special Nuclear Materials

The emergence of new methodologies with promising applications that could impact nuclear security and emergency preparedness detection systems in the near future motivate the development of computational tools that allow the theoretical investigation of the relevant design parameters for such detection systems. Here, we present Monte Carlo simulations using the MCNP6 code to investigate the use of fast neutron-neutron and gamma-neutron coincidences in addition to conventional methods for detection of special nuclear materials (SNM) using inorganic scintillator detectors. The results show fair agreement between MCNP6 and MCNP-PoliMi simulations for neutron-neutron coincidences and that coincident detection of gamma rays and fast neutrons has a potential for enhancing the sensitivity for detection of SNM compared with conventional gamma-ray, single-neutron, and fast neutron-neutron coincidence detection schemes.

Assessing the suitability of three proxy sources for the development of detectors of special nuclear materials

Numerous techniques and equipment have been developed to provide a capability for the detection of special nuclear materials (SNM), but due to the necessary security measures surrounding these materials alternate, or proxy, neutron sources are often utilised in their stead. In this paper we report the neutron and gamma pulse shape discrimination response of plastic scintillator to mixed neutron/gamma beams produced from two radionuclide neutron sources, and also from an SNM source of weapons-grade plutonium. We discuss the suitability of using radionuclide sources, with appropriate shielding configurations as proxy sources for SNM.A 3σnth-γ discrimination level has been achieved for an SNM source at a low-level energy threshold of ∼220 keVee when a shielding configuration of 5 cm of lead was implemented. Varying amounts of lead and high-density polyethylene (HDPE) shielding were also investigated with the 3σ limit being reached by ∼240 keVee.This work shows that an AmBe neutron source serves as an appropriate SNM proxy achieving a comparable value for figure of merit above ∼1 MeVee. For energies below 1 MeVee down to ∼100 keVee a closer approximation of the expected FoM for SNM can be attained when using 252Cf as a proxy source or by utilising an ‘enhanced’ AmBe source with the addition of a further low energy γ ray source.

12C(p,p′)12CReaction (Ep=19.5–30MeV) for Active Interrogation of Special Nuclear Material

Passive detection of special nuclear material (SNM) is challenging due to its inherently low rate of spontaneous emission of penetrating radiation, the relative ease of shielding, and the fluctuating and frequently overwhelming background. Active interrogation (AI), the use of external radiation to increase the emission rate of characteristic radiation from SNM, has long been considered to be a promising method to overcome those challenges. Current AI systems that incorporate radiography tend to use bremsstrahlung beams, which can deliver high radiation doses. Low-energy ion-driven nuclear reactions that produce multiple monoenergetic photons may be used as an alternative. The $^{12}$C(p,p')$^{12}$C is one such reaction that could produce large gamma-ray yields of highly penetrating 4.4- and 15.1-MeV gamma rays. This reaction does not directly produce neutrons below the $\sim$19.7-MeV threshold, and the 15.1-MeV gamma-ray line is well matched to the photofission cross-section of $^{235}$U and $^{238}$U. We report the measurements of thick-target gamma-ray yields at 4.4 and 15.1 MeV from the $^{12}$C(p,p')$^{12}$C at proton energies of 19.5, 25, and 30 MeV. Measurements were made with two 3'' EJ309 cylindrical liquid scintillation detectors and thermoluminescent dosimeters placed at 0 and 90 degrees. We estimate the highest yields of the 4.4- and 15.1-MeV gamma rays of 1.65$\times10^{10}$ sr$^{-1}\mu$ C$^{-1}$ and 4.47$\times10^8$ sr$^{-1}\mu$ C$^{-1}$ at a proton energy of 30 MeV, respectively. The yield of 4.4 and 15.1 MeV gamma rays in all experimental configurations is greater than a comparable deuteron-driven reaction that produces the same gamma-ray energies- $^{11}$B(d,n$\gamma$)$^{12}$C. However, a two orders of magnitude increase of the neutron radiation dose is observed when the proton energy increases from 19.5 to 30 MeV.

Detection of special nuclear materials (SNM) using passive and pulsed neutron source based active coincidence methods

Detection of fissile and fertile materials and their accountability is important for nuclear safeguards. This paper reports detection of 238U and 235U in the same experimental setup using passive and pulsed neutron source based active coincidence methods respectively. The coincidence analysis has been carried out using a time stamp data acquisition system. Furthermore, the paper reports the fast ever detection of 235U using D-T pulsed neutron source based active coincidence method along with time stamp data acquisition system. In this study, 142.86 gm 238U and 1 gm 235U have been detected successfully using passive and pulsed neutron source based active coincidence methods with 6000 s and 400 s time stamp data respectively acquired using only eight 3He detectors of 45 cm active length. Furthermore, the present research methodology can be extended for the detection of Plutonium. This work will also be of importance towards detection of small quantity of SNM in cellulose waste from nuclear material processing facilities.

Isotopic analysis of uranium by laser induced breakdown spectroscopy

There are several advantages of using laser ablation (LA) for nuclear material detection, which includes minimal sample preparation, near-instantaneous detection, and isotope detection. The well-known laser ablation method commonly called Laser Induced Breakdown Spectroscopy (LIBS) has one of the main advantages of optical emission spectroscopy (OES): is noninvasive and near-instantaneous detection and identification of elements in the sample. The detection of special nuclear materials (SNMs), such as uranium and thorium, is of particular interest to many agencies around the world, i.e., International Atomic Energy Agency (IAEA). Chemometrics analysis coupled with LIBS is a suitable combination for the determination of isotope ratios in the air at atmospheric pressure using poorly resolved lines. Typically, the precision will be in the range from 4 to 10% depending on the enrichment level, which is compatible with the use of an alarm instrument in complementary access inspection.

New Compact Neutron Generator System for Multiple Applications

Compact neutron generators can provide a high flux of neutrons with energies ranging from thermal (0.025 eV) to 14 MeV. The application of the deuterium-deuterium, D-10B, and D-7Li nuclear reactions and new advancements in high-flux neutron generator technology along with the commercial availability of high-voltage direct current power supplies enables the production of high-flux 2.45-, 6-, 10-, and 13-MeV neutrons. The high-energy neutrons or the moderated epithermal neutrons from the new compact neutron generator can greatly advance cancer therapy, radioisotope production, neutron yield measurement, special nuclear materials detection, and neutron transmutation doping of silicon.

New solid-state organic scintillators for fast and thermal neutron detection

Detection of special nuclear materials (SNM) requires instruments that can detect and characterize uranium and plutonium isotopes, having at the same time the ability to discriminate among different types of radiation. For many decades, neutron detection has been based on 3He proportional counters sensitive primarily to thermal neutrons. The most common methods for detection of fast neutrons have been based on liquid scintillators with pulse shape discrimination (PSD). The shortage of 3He and handling issues with liquid scintillators stimulated a search for efficient solid-state PSD materials. Recent studies conducted at LLNL led to development of new materials, among which are organic crystals with excellent PSD and first PSD plastics for fast neutron detection. More advantages are introduced by plastics doped with neutron capture agents, such as 10B and 6Li, that can be used without moderation for combined detection of both thermal and fast neutrons, offering, in addition, a unique “triple” PSD for signal separation between fast neutrons, thermal neutrons, and gamma-rays. More recent studies have been focused on development of deuterated scintillators that can be used for neutron spectroscopy without time-of-flight (ToF). Among commercially produced materials are large-scale (>10 cm) stilbene crystals grown by the inexpensive solution technique, and different types of PSD plastics that, due to the deployment advantages and ease of fabrication, create a basis for the widespread use of solid-state scintillators as large-volume and low-cost neutron detectors.

Simulation of delayed gamma rays from neutron-induced fissions using MCNP 6.1

As part of its R&xD activities in the fields of radioactivewaste drum storage and homeland security, the NuclearMeasurement Laboratory of CEA Cadarache has started studiesrelated to the detection of induced delayed fission gamma rays asa signature of U/Pu presence either in radioactive wastes or incargo containers and luggage. The study described in the presentpaper explores the feasibility of detecting fission delayed gammarays of nuclear materials interrogated by a pulsed neutrongenerator. For this purpose, Monte Carlo simulations have beenperformed with ACT, the MNCP6 Activation Control Card.Simulated results have been compared with experimental data tovalidate the numerical model. Samples of uranium andplutonium have been irradiated for 2 hours with a pulsed D-Tneutron generator delivering 14 MeV neutrons with an averageemission of 8.107n/s, which are thermalised in a graphite cellcalled REGAIN. At the end of irradiation, activated nuclearmaterials were placed in a low-background, high-resolutiongamma spectroscopy station in order to detect delayed gammarays emitted by fission products. Anomalies have been observedin the calculated time decay curve of fission delayed gamma rayswith MCNP6 ACT card, but the time behavior is correct for non-fission activated materials like aluminum or copper. On the otherhand, the number of counts recorded in the main simulatedgamma ray lines from activated nuclear material fission productsis consistent with the experimental results, thus validating thesimulation scheme in view of further studies on thecharacterization of radioactive waste drums or special nuclearmaterial detection in cargo containers.

MACHINE-LEARNING ALGORITHM FOR SHIELDED SPECIAL NUCLEAR MATERIALS DETECTION

A machine-learning algorithm has been implemented by use of a neural network as a preliminary study on the applicability of this method to special nuclear materials detection. The algorithm predicts the presence of the 238U isotope when learning from a gamma spectrum data measured with a high-purity germanium detector from a sample of depleted uranium. In this work, both a fully connected neural network and a convolutional neural network have been implemented, and the performance of different configurations of the network has been studied. The use of convolutional network showed better performance over the fully connected network, with cost function and success rate values supporting a better prediction while avoiding overfitting. Furthermore, implemented network features such as filtering, max-pooling, dropout regularization, and momentum optimization also showed improved prediction performance.

Enhancing neutron detection capabilities of a water Cherenkov detector

In this work we show the neutron detection capabilities of a water Cherenkov detector (WCD) using pure water, as well as an aqueous solution of sodium chloride as the detection volume. The experiments were performed using a WCD with a single photomultiplier tube (PMT), and a 252Cf neutron source. We show that fast neutrons from a 252Cf source directly impinging the detector can be clearly detected and identified over the natural radiation background. We also present results from numerical simulations that describe the response of the WCD to neutrons of different energies. To do this, a detailed model for the WCD and of the neutron source spectra have been implemented. The implemented simulation code takes into account the interaction processes involved in the detection of neutrons using WCD, and support the experimental evidence introduced in this work. Being both the active volumes analyzed in this work (pure water) and the additive (sodium chloride), cheap, non-toxic and easily accessible materials, the results obtained are of interest for the development of large neutron detectors for different applications. Of particular importance are the detection of special nuclear materials, as well as those applications related with space weather phenomena. We conclude that WCD used as neutron detectors could be a replace or a complementary tool for standard neutron monitors based on 3He.