FIELDABLE NUCLEAR MATERIAL IDENTIFICATION SYSTEM
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A comparison of the characteristics of the Nuclear Materials Identification System (NMIS) and its more fieldable version that was developed for future treaty applications, the Fieldable Nuclear Materials Identification System (FNMIS), is presented. Both systems were developed for the US Department of Energy (DOE) Office of Nuclear Verification (ONV). Under the Warhead Safety and Security Exchange Agreement, NMIS was also jointly developed with the Russian Federation. The configuration of the systems and their characteristics are described. In addition, the capabilities, advantages and disadvantages, and a comparison fast-neutron transmission imaging measurement is presented. The comparison measurements gave essentially the same results because the software and imaging apparatus have the same capabilities, with the FNMIS completing the measurements slightly faster. NMIS is an open system that is more easily modified for research applications and is not suitable for the ONV mission, and FNMIS is compatible with an information barrier, which is more useful for ONV applications.
Nuclear material identification and isotopic composition analysis are important capabilities for safeguards and the verification of nuclear arms control and nonproliferation treaties. Epithermal neutron resonance imaging has been proposed for spent fuel assay measurements, and the development of a mobile neutron imaging system could provide such a tool for on-site applications. This technique is highly sensitive to isotopes of interest for safeguards applications (e.g. 235,238 U, 238,239,240 Pu) and yields unique transmission spectra for a target containing actinides and some mid- and high-Z elements. Paired with a position-sensitive neutron detector, such a system could provide spatial information of the target isotopic composition. Recent progress in the development of high intensity neutron sources could make mobile epithermal neutron imaging designs increasingly feasible to serve as a tool for nuclear inspectors. In this work, Monte Carlo (MC) simulations were performed to further optimize a previous design for an epithermal neutron resonance-based analysis apparatus using a D-T portable neutron generator. Additionally, experimental work is being performed to test the feasibility of this method. The MC simulations of moderation time distributions for different moderator compositions and thicknesses were measured to provide a multi-group correction for neutron time-of-flight energy reconstruction.
This work demonstrates the potential of silicon pillars filled with boron-10 as a sensor technology for a compact and portable neutron multiplicity system. Solid-state, semiconductor based neutron detectors may enable completely new detector form factors, offer an alternate approach to helium-3 based systems, and reduce detector weight and volume requirements. Thirty-two pillar-structured neutron detectors were assembled into a system with an active area of over 20 cm 2 and were used in this work to demonstrate the feasibility of this sensor technology as a potential replacement for helium-3 based gas detectors. Multiplicity measurements were successfully carried out using a californium-252 neutron source, in which the source mass, system efficiency, and die-away time were determined. As a result, this demonstration shows that these solid-state detectors could allow for a more compact and portable system that could be used for special nuclear material identification in the field.
Nuclear forensics is the collection and analysis of nuclear or radiological material to support investigations into the diversion, trafficking, or illicit activities involving materials. The goal is to link nuclear or radioactive material to people, processes, events and/or locations.
Nuclear forensics is the collection and analysis of nuclear or radiological material to support investigations into the diversion, trafficking, or illicit activities involving materials. The goal is to link nuclear or radioactive material to people, processes, events and/or locations.
Identifying threat nuclear materials is a critical for the prevention of acts of nuclear terrorism on the homeland. For this purpose, many radionuclide identification devices are deployed in the field. However, these will not necessarily be in the hands of non-experts, therefore these devices need to provide ready-made answers for the personnel in the field. This is where advanced algorithms are employed to both interpret the data and provide the identification of the nuclear material being interrogated. We took a machine learning approach to identification, by using training and validation data sets to create and optimize classifiers which determine which radionuclide is consistent with the data. The classifiers investigated were the Random Forest, Decision Tree, Support Vector Machine, and XG Boost and their performance was judged using the F1 Score for both hyperparameter tuning and comparison. In the end, we found out that the Random Forest Classifier worked the best based off the F1 Score they got which was 0.98.
For the characterization of spent fuel and for the safe direct disposal of SNF we present: a) a method of numerical assessment of their radionuclides inventory that is derived from the initial fuel characteristics and individual burn-up / cooling time history of that particular fuel assembly, and b) how the numerical information can be experimentally assessed using muon tomography as a nondestructive assay of large and heterogeneous SNF casks. We combine both complementary methods, i.e. numerical assessment and muon tomography (MT) experimental assay, to provide a powerful tool for verifying the nuclear inventory without compromising the casks or radioactive material containers. Here, we shall present the numerical assessment technique and preliminary but very promising experimental results, and explain the scope of a versatile and mobile MT-detection system for the identification of nuclear material inside large casks containing spent fuel assemblies and/or other large volume heterogeneous material containers for which the European Commission has recently granted R and D funding within the CHANCE project to be developed. (authors)
Neutron measurement technology is critical to the detection and identification of nuclear materials and sources. Portable neutron detectors that enable thermal neutron and fast neutron measurements with a single system are still an experimental area. The ability to employ three signatures (photons, thermal neutrons, and fast neutrons) simultaneously for identification provides an extra element of certainty in results. The energy of fast neutrons can also provide a unique spectral signature for source quantification. A phoswich detector is based on the use of two dissimilar scintillators with a single photomultiplier tube (PMT) for the purpose of radiation detection. Past development was focused primarily on the application of the multi-scintillator design to gamma-ray, alpha- and beta-particle measurements. To this end, the work presented here has focused on the development of a phosphor sandwich ('phoswich') detector capable of differentiating between photons, thermal neutrons, and fast neutrons. The portable phoswich neutron detector was designed using two solid-sate scintillators: the {sup 6}Li-loaded glass and the EJ-299-33A plastic. Experiments showed that detector provides simultaneously count rates of photons, thermal neutrons, and fast neutrons with the energy spectroscopy option. (authors)
In this article, we propose the conceptual design, with supporting beam dynamics results, of a normal conducting, separated-sector cyclotron with a strong-focusing field gradient designed to accelerate light ions with a charge-to-mass ratio of 1/2 up to 15–20 MeV/u. The design can support a host of applications for therapy, radiobiology, material science, and instrumentation development. The light-ion species, which can include a mixed ion beam, can be dynamically chosen to provide a range of characteristic signals appropriate for specific material identification such as special nuclear materials. A conservative baseline concept is presented which has been optimized for radioisotope production of alpha emitters and theranostic radiopharmaceuticals. The modular design is also demonstrated to be scalable in gross physical parameters by a factor of 2–3, thereby reducing the size, weight, and power requirements (SWaP) and enabling near-term security applications.
The detection and accurate identification of nuclear material is critical to the advancement of national security, medical technology, and environmental prosperity. The gold standard solid-state detector HPGe, suffers from high manufacturing costs and the need to operate at cryogenic temperatures to ensure reliable energy resolution. The other most common solid-state detector, cadmium zinc telluride (CZT), has the ability to operate at room temperature, but the grow process results in impurities decreasing performance. In this paper we have developed a continuous flow synthesis able to mass produce targeted size cadmium selenide quantum dots. The implementation of these QDs in QD/MEH-PPV composites has the ability to rival HPGe energy resolution at room temperature.
Presentation describes development of a portable short pulse neutron source with the ability to detect concealed special nuclear material using a stimulating radiation source.
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Detection and identification of special nuclear materials (SNMs) are an essential part of the US nonproliferation effort. Modern cutting-edge SNM detection methodologies rely more and more on modeling and simulation techniques. Experiments with radiological samples in realistic configurations, is the ultimate tool that establishes the minimum detection limits of SNMs in a host of different geometries. Modern modeling and simulation approaches have the potential to significantly reduce the number of experiments with radioactive sources needed to determine these detection limits and reduce the financial barrier to SNM detection. Unreliable nuclear data is one of the principal causes of uncertainty in modeling and simulating nuclear systems. In particular, nuclear cross sections introduce a significant uncertainty in the nuclear data. The goal of this research is to develop a methodology that will autonomously extract the correct nuclear resonance characteristics of experimental data in a reliable way, a task previously left to expert judgement. Accurate nuclear data will in turn allow contemporary modeling and simulation to become far more reliable, de-escalating the extent of experimental testing. Modeling and simulation techniques reduce the use and distribution of radiological sources, while at the same time increase the reliability of the currently used methods for the detection and identification of SNMs.
Radionuclide identification through gamma-ray spectroscopy is an indispensable tool in combatting the illicit smuggling of nuclear material. The radionuclide identification devices used in the field need to provide ready-made answers to non-experts, and therefore require sophisticated algorithms that can interpret the underlying data. We investigated the Random Forest classifier as a tool for identifying the radionuclide that is consistent with the data. We were provided with training and validations data sets and used them to optimize the two hyperparameters of the classifiers: maximum features required, and minimum samples used to split each node. The F1 score, a harmonic mean of precision and recall, was used to evaluate the performance of each built classifier. We found the optimal performance with minimum samples of 5 and maximum features of 50, with the F1 score of 0.95.
The thorium fuel cycle is an alternative to the uranium fuel cycle in that when 232Th is irradiated with neutrons it is converted to 233U, another fissile isotope. There are several chemical forms of thorium which are used in the Th fuel cycle. Recently, Raman spectroscopy has become a very portable and facile analytical technique useful for many applications, including e.g. determining the chemical composition of different materials such as for thorium compounds. The technique continues to improve with the development of ever-more sensitive instrumentation and better software. Using a laboratory Fourier-transform (FT)-Raman spectrometer with a 785 nm wavelength laser, we were able to obtain Raman spectra from a series of thorium-bearing compounds of unknown origin. These spectra were compared to the spectra of in-stock-laboratory thorium compounds including ThO2, ThF4, Th(CO3)2 and Th(C2O4)2. The unknown spectra showed very good agreement to the known standards, demonstrating the applicability of Raman spectroscopy for detection and identification of these nuclear materials.
The detection, identification, and localization of illicit nuclear materials in urban environments is of utmost importance for national security. Most often, the process of performing these operations consists of a team of trained individuals equipped with radiation detection devices that have built-in algorithms to alert the user to the presence nuclear material and, if possible, to identify the type of nuclear material present. To encourage the development of new detection, radioisotope identification, and source localization algorithms, a dataset consisting of realistic Monte Carlo-simulated radiation detection data from a 2 in. × 4 in. × 16 in. NaI(Tl) scintillation detector moving through a simulated urban environment based on Knoxville, Tennessee, was developed and made public in the form of a Topcoder competition. The methodology used to create this dataset has been verified using experimental data collected at the Fort Indiantown Gap National Guard facility. Realistic signals from special nuclear material and industrial and medical sources are included in the data for developing and testing algorithms in a dynamic real-world background.
Under a 2006 agreement between the Department of Energy (DOE) of the United States of America and the Institut de Radioprotection et de Sûreté Nucléaire (IRSN) of France, the National Nuclear Security Administration (NNSA) within DOE and IRSN initiated a collaboration to improve isotopic identification and analysis of nuclear material [i.e., plutonium (Pu) and uranium (U)]. The specific aim of the collaborative project was to develop new versions of two types of isotopic identification and analysis software: (1) the fixed-energy response-function analysis for multiple energies (FRAM) codes and (2) multi-group analysis (MGA) codes. The project is entitled Action Sheet 4 – Cooperation on Improved Isotopic Identification and Analysis Software for Portable, Electrically Cooled, High-Resolution Gamma Spectrometry Systems (Action Sheet 4). FRAM and MGA/U235HI are software codes used to analyze isotopic ratios of U and Pu. FRAM is an application that uses parameter sets for the analysis of U or Pu. MGA and U235HI are two separate applications that analyze Pu or U, respectively. They have traditionally been used by safeguards practitioners to analyze gamma spectra acquired with high-resolution gamma spectrometry (HRGS) systems that are cooled by liquid nitrogen. However, it was discovered that these analysis programs were not as accurate when used on spectra acquired with a newer generation of more portable, electrically cooled HRGS (ECHRGS) systems. In response to this need, DOE/NNSA and IRSN collaborated to update the FRAM and U235HI codes to improve their performance with newer ECHRGS systems. Lawrence Livermore National Laboratory (LLNL) and Los Alamos National Laboratory (LANL) performed this work for DOE/NNSA.