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This project utilized a 10-meter Fast Transfer System (called RABITTS) and Decay Station. FPYs are measured using neutron activation of U-235 and Pu-239 followed by gamma ray spectroscopy. We irradiated targets with mono-energetic neutrons produced at the TUNL tandem accelerator laboratory. The gamma spectra collected in these target irradiations are being analyzed to determine FPY values.
The objective of this work was to develop a machine learning ensemble that could assist pebble bed reactor verification by evaluating whether a given pebble circulating through a PBR was normal or anomalous using gamma spectroscopy measurements from a notional PBR burnup measurement system. Using a PBR reference design, data sets of synthetic gamma spectra representative of BUMS measurements of normal and anomalous pebbles that may be used to produce special fissile material were generated to train and test an ML anomaly detection ensemble on two reference scenarios – substitution of normal pebbles with target pebbles for production of Pu or 233 U. The ML ensemble correctly identified all anomalous pebbles in the testing data set, and while perfect ensemble performance is normally indicative of overfitting, it was concluded that significantly lower photon intensity of target pebbles produced distinctly less intense photon spectra to where perfect ensemble performance was expected.
This report provides a performance summary of the “Isotopics by Nuclides” tool in InterSpec. The primary objective of the NA-241 FY25 project was the detection and characterization of non-homogeneous uranium samples. However, the tool also demonstrates effectiveness in determining the enrichment of homogeneous uranium or plutonium from single gamma spectra. This paper presents a subset of evaluated data to avoid distribution limitations while offering potential users’ insight into the tool's performance.
New reactor designs, such as pebble-bed reactors, present challenges for the safeguarding of fissile material. Due to the multi-pass fuel circulation design and the non-uniform path a pebble may traverse through a pebble-bed reactor, there will be variations in the irradiation history of spent fuel pebbles. The standard approach of estimating actinide quantities based on fission gamma spectra or neutron emission paired with depletion modeling may yield uncertainties too large for safeguards and material accountancy. This project investigated, through modeling and experimentation, the potential of neutron self-interrogation of spent fuel pebbles as an innovative method to implement materials accountability. As an example, our feasibility studies indicate that the mass of U-235, U-238, Pu-239 and Pu-241 can be predicted to 4.1, 0.86, 13 and 13 % accuracy, respectively, when measuring 100 closely packed end-of-life spent fuel pebbles over approximately 12 days using a 4π counting geometry.
Some Radioisotope Identification Devices (RIIDs) have a low efficiency neutron detector that can provide a neutron singles counting rate along with the primary gamma spectra that can be used to identify a radioisotope. When we know absolute efficiency, other characteristics of a radioisotope can be estimated such as mass or source strength when accompanied by the identity of the isotope and other observable variables. This study focuses on characterizing and comparing the absolute neutron efficiencies of some commonly used RIIDs: the ORTEC Detective X, ORTEC RADEAGLET-R, and FLIR IDentifinder 2.
SAND2024-01293O The Code for BALDR Study 07.05 software reproduces results from the BALDR study concerning "A Semi-Supervised Learning Method to Produce Explainable Radioisotope Proportion Estimates for NaI-based Synthetic and Measured Gamma Spectra." The code for BALDR Study 07.05 can reproduce a scientific study following the step numbers within the file names. Using synthetic and measured data to find the best model for the radioisotope proportion estimation task of interest, the study generated results for inclusion in a paper. The high-level methods involved are neural networks, semi-supervised learning, and out-of-distribution detection. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
Heating rate measurements made in a mock-up of a BeO heat shield for a gas core nuclear rocket engine yields results nominally a factor of two greater than calculated by two different methods. The disparity is thought to be caused by errors in neutron capture cross sections and gamma spectra from the low cross-section elements, D, O, and Be.
The composition of a sample of lunar surface material returned by the Luna 16 automatic station from the Sea of Fertility was studied, using nondestructive activation analysis. The structure of the returned surface material is inhomogeneous; the surficial material is thin, quite homogeneous, and the granularity increases with depth. Based on grain size, the sample was separated into five zones. The activation analysis was conducted on a sample taken from the friable surficial layer, zone A. The content of Al, Mn, Na, Cr, Co, Fe, and Sc was determined by nondestructive activation analysis of the sample. In determining Cr, Co, Fe, and Sc, the sample was irradiated for 24 hours and cooled for 10 days. Gamma spectra of the samples were recorded with a semiconductor Ge(Li)-detector and a multichannel analyzer, and measurement data were processed with an electronic computer.
The primary goals of this project are development of the technology for HgI2 photodetectors (PD's), development of a HgI2/scintillator gamma detector, development of electronics, and development of a prototype gamma spectrometer. Work on the HgI2 PD's involved HgI2 purification and crystal growth, detector surface and electrical contact studies, PD structure optimization, encapsulation and packaging, and testing. Work on the HgI2/scintillator gamma detector involved a study of the optical - mechanical coupling for the optimization of CsI(Tl)/HgI2 gamma ray detectors and determination of the relationship between resolution versus scintillator type and size. The development of the electronics focused on low noise amplification circuits using different preamp input FET's and the use of a coincidence technique to maximize the signal, minimize the noise contribution in the gamma spectra, and improve the overall system resolution.
Over the past decade, considerable resources have been applied to investigate verification of used nuclear fuel assemblies for international safeguards. The opportunity to expand the available data used to validate these verification techniques was presented in 2016 by the High Burnup Spent Fuel Data Project, which made 25 high-burnup pressurized water reactor used fuel rods available for measurement in the Irradiated Fuels Examination Laboratory at Oak Ridge National Laboratory. With the support of the National Nuclear Security Administration Office of Nonproliferation and Arms Control, a 2017 campaign measured the 25 used fuel rods with a high-resolution gamma spectrometer. A planar high-purity germanium detector was used to provide high-efficiency across an energy range from 60 keV to 3 MeV. Gamma spectra of individual fuel rods were collected in 4.5 mm steps along the entire length of each rod. In addition, spectra were collected on select rods in rotational increments of 30 degrees to provide data on the distribution of fission products along the rod perimeter. The spectra are stored on a controlled-access website for use by others. This paper describes the measurement geometry, used fuel rod characteristics, example spectra, and preliminary analyses performed during the measurement campaign.
Classifiers for dissolution events at a radiochemical processing facility are studied using gamma spectra measurements of effluents collected by a high purity germanium detector located at its off-gas stack. Data sets collected at the Oak Ridge National Laboratory’s Radiochemical Engineering Development Center under a Pu dissolution campaign spanning a three months period are utilized. Features corresponding to the activity levels of 15 radionuclides, including isotopes of iodine, krypton, and xenon, that are indicated by the target decay chains, are computed from the spectra at 1 hour intervals. A conceptualization diagram is developed to reflect the steps from the source to measurement to feature computation that depend on fission products indicated by decay chains, chemical processing, and effluents transport to the off-gas stack. A diverse set of eight classifiers based on different design principles are trained using the ground truth data for this campaign, and the outputs of top three classifiers, namely, classification trees, Ensemble of Trees (EOT), and k-nearest neighbor, are combined using EOT classifier-fuser. Our results show that for 5-fold cross validation, features associated with isotopes of xenon provide the lowest classification error among the different elements across the classifiers; the classification error is furthered improved when all 15 isotope features are used by each classifier, and it is again improved by the fusion of three classifiers. Further reduction in classification error is achieved by using a measurement window of 1-2 days which is identified based on half-life time estimates of the isotopes; it is long enough for the stabilization of feature estimates while being short enough not to be affected by the follow on dissolution events. As a net result of feature and classifier fusion, combined with the incorporation of decay chain and isotope half-life information, this approach achieves 98% detection rate while maintaining a false alarm rate under 2% for this data set.
Three types of information fusion strategies are studied to assess the performance of classifiers for detecting low-level U-235 radiation sources, using features obtained from gamma spectra of NaI detectors. These three strategies are based on using two spectral region features, fusing eight classifiers of diverse designs, and fusing multiple detectors located at different positions around the source. The inner, middle and outer groups of detectors, within a formation of two concentric circles and a spiral of 21 detectors, are identified based on their distance to the source, which is located at the center. This study provides two main qualitative insights into this classification task. First,the fusion of detectors leads to an overall improved classification performance, least in the inner group, most in the outer group, and in between for the middle group. Second, several classifiers and fusers achieve lower training error which does not translate to lower generalization error, indicating their over-fitting to training data.
The machine learning methods for classifiers to detect low level radiation sources are of interest when suitable training data sets are available. Their application and performance assessment, however, involves the aspects of over-fitting and training data selection that are somewhat uncommon in other existing methods for this task.We study U-235 gamma signatures using data sets collected by 21 NaI detectors under controlled conditions. The gamma spectra are collected by the detectors located at different distances from the source, and we study their choice as training sets for classifiers to detect a source. The detectors form the near, middle and outer groups based on the distance to source. The classifiers based on the outer group are susceptible to over-fitting, that is, they achieve low training error but incur much higher testing error in independent tests. The other two groups achieve lower training error and comparable testing error, and the near group achieves the overall lowest error. In detecting a source at an unknown distance, the farther detectors in the middle group achieve the overall lowest testing error with limited over-fitting, thereby indicating the complex dependencies between the training and classifier performance.
Experimental measurement of gaseous fission product release with respect to temperature and burnup is a critical aspect of understanding nuclear fuel performance, validating predictive models, and qualifying new fuels. To measure this phenomenon in real-time, Oak Ridge National Laboratory has developed an instrument for measuring in situ fission gas release from small-scale fuel samples irradiated in the High Flux Isotope Reactor (HFIR). The instrument uses a continuous flow of Heover the fuel samples to sweep gaseous fission products from a sealed capsule in the HFIR Be reflector to an instrument station adjacent to the reactor. The instrument station houses two high-purity germanium (HPGe) detectors that measure decay gamma rays from fission products passing through a room temperature dwell chamber placed over the detector crystal. The sealed capsules in the reactor are designed to modulate fuel sample temperatures between 700 and 1,100°C by changing the Ar/He gas mixture surrounding the capsules during irradiation. N-type thermocouples are incorporated into the capsule housing to record real-time fuel temperatures. The capsules are heated primarily by prompt gamma rays emitted from the HFIR core with minimal heat contributions from fission in the fuel samples to minimize temperature gradients in the specimens for separate-effects characterization of the material. This paper describes modeling of time-dependent nuclear heating and fission product formation in fuel samples, thermal characteristics of the in-core capsules, and expected gaseous fission product gamma spectra at the HPGe instrument station.
We introduce a non-resonant acceleration mechanism arising from the second adiabatic invariant in magnetic turbulence and apply it to study the prompt emission spectra of gamma-ray bursts (GRBs). The mechanism contains both the first- and second-order Fermi acceleration, originating from the interacting turbulent reconnection and dynamo processes. It leads to a hard electron energy distribution up to a cutoff energy at the balance between the acceleration and synchrotron cooling. The sufficient acceleration rate ensures a rapid hardening of any initial energy distribution to a power-law distribution with the index p∼1, which naturally produces a low-energy photon index α∼−1 via the synchrotron radiation. For typical GRB parameters, the synchrotron emission can extend to a characteristic photon energy on the order of ∼100 keV.
If cyclotron scattering, rather than absorption, is responsible for the line features observed recently in two gamma-ray burst spectra (Murakami et al., 1988), then the second and higher harmonics are due to resonant scattering events that excite the electron to Landau levels above the ground state. Here, relativistic Compton scattering cross sections are used to estimate the expected ratio of third to second harmonics in the presence of Doppler broadening. At the field strength (1.7 TG) required to give first and second harmonics at 19 keV and 38 keV, there should be no detectable third harmonic in the spectrum.
Detailed differential energy spectra from gamma ray bursts obtained by IMP-6 are presented. Observations cover times of occurance, photon flux, and temporal and spectral characteristics.
The splitting of photons into two photons becomes both possible and significant in magnetic fields in excess of 10(exp 12) Gauss. Below the threshold energy, 2m sub e c(exp 2) for single photon pair production, splitting can be an astronomically observable phenomenon evident in gamma ray burst spectra. In such circumstances, it was found that magnetic photon splitting reprocesses the gamma ray burst continuum by degrading the photon energy, with a net effect that is quite similar to pair cascade reprocessing of the spectrum. Results are presented for the spectral modifications due to splitting, taking into account the different probabilities for splitting for different polarization modes. Unpolarized and polarized pair cascade photon spectra form the input spectra for the model, which calculates the resulting splitting reprocessed spectra numerically by solving the photon kinetic equations for each polarization mode. This inclusion of photon polarizations is found to not alter previous predictions that splitting produce a significant flattening of the hard X ray continuum and a bump at MeV energies below a pair production turnover. The spectrum near the bump is always strongly polarized.