Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “forensics”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 307 records · Page 17

Chemometrics and visible diffuse reflectance spectroscopy to classify plutonium dioxide

Diffuse reflectance (DR) spectra in the Vis-NIR (∼380–1050 nm) region were acquired for a series of PuO 2 samples with a spot size of about 10 × 10 μm. Two batches of six PuO 2 samples, synthesized approximately 7.5 months apart, were prepared using both Pu(III) and Pu(IV) oxalate precursors at three distinct calcination temperatures (450, 650, and 950 °C). This yielded a total of 12 PuO 2 samples and 433 DR spectra. The DR spectrum of PuO 2 contained numerous peaks in the visible region, and characteristic features were identified with respect to calcination temperature and chemistry. A distinct peak multiplet near 615 nm was observed for samples prepared at low calcination temperatures, and a peak near 660 nm was observed for higher calcination temperatures. A multivariate classification strategy based on principal component analysis (PCA) was developed to distinguish PuO 2 calcination temperatures of 450, 650, and 950 °C with 100 % accuracy. Classification results also indicate the potential to distinguish chemical processing history (i.e., Pu(III) or Pu(IV)) based on the spectra with 72 % accuracy based on k-nearest neighbors applied to the PCA scores. Partial least squares discriminant analysis was used to identify variation among batches with 88 % accuracy and found that peaks near 669, 681, 811, and 970 nm were the most useful for predicting the batch identity. Here, this work demonstrates how micro-diffuse reflectance spectroscopy and chemometrics can be used to classify PuO 2 processing history based on Vis-NIR spectral features. Combining the chemometric approach with mapping sequences could provide a rapid, nondestructive approach to classify Pu oxide materials for environmental, forensics, and nonproliferation applications.

Actinide↗

147 Nd Quantification Using HSCCC-Purified Samples

Quantifying the fission product 147 Nd in nuclear debris samples is an important component of post-detonation nuclear forensics. The most accurate quantifications are obtained when Nd is purified from all other fission products, actinides, activation products, and environmental matrix contained within the debris. In this study, a recently developed method for Nd purification was tested, purifying 147 Nd from solutions of mixed fission products using high-speed counter-current chromatography (HSCCC). Importantly, the new method allowed for faster elution of Nd from the column as compared with established high performance liquid chromatography (HPLC) methods, and resulted in accurate/precise 147 Nd quantification by gamma-ray spectrometry. While the up-front equipment costs associated with HSCCC may be higher, its operational costs are on par with those of HPLC (solvents, extractants, power). Gas-flow proportional beta decay counting revealed contamination from the nearest neighbor lanthanide 143 Pr (a gamma-silent radioisotope) in the HSCCC-purified samples, but the activity contribution from 147 Nd could still be quantified. Remarkably consistent elution profiles were observed for the HSCCC method, spanning rare earth element (REE) loadings of more than 10 orders of magnitude (tracer to mmol quantities). In conclusion, the reliability and speed of the new method suggest utility for the rapid separation and quantification of 147 Nd in unknown samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantitative Encapsulation and Homogeneity Assessment of Sol–Gel Based Nuclear Explosive Debris Simulants

Nuclear explosive debris simulants are an important material in training and validating aspects of post-detonation nuclear forensic processes. Realistic simulants should replicate several aspects of nuclear explosive debris such as the size, shape, color, density, and chemical and radiological properties. Silica particles produced via sol-gel synthesis have recently been found to successfully reproduce many of these parameters including the controllable incorporation of radionuclide content. However, to be useful as a benchmarking material for validation and verification of laboratory methodologies, radionuclide content from batch-to-batch must be reproducible. Here, in this work, we explore the variance in radionuclide distribution incorporated into sol-gel benchmarking materials with respect to sample subdivision. Results will help inform the sample sizes required to minimize variance between samples.

36 - MATERIALS SCIENCE↗

Machine Learning–Augmented Laser-Induced Breakdown Spectroscopy for Spectral Discrimination of Iron Oxalates

Enhanced characterization and phase identification of post-PUREX Pu Oxalates (PuOXA) are pivotal for nonproliferation and pre-detonation nuclear forensics. Despite significant advances in the characterization of PuO 2 samples, little is known about the impact of both the chemical structure and oxidation states of PuOXA (i.e., Pu(III) and Pu(IV)) have on optical emission signatures. Here, we demonstrate the analytical capabilities of laser-induced breakdown spectroscopy (LIBS) applied to Fe(II) and Fe(III) oxalate samples as surrogates for PuOXA, highlighting the discriminating features in the LIBS emission spectra arising from differences in the oxidation states within mixed FeOXA samples. We report the enhancement of spectral feature selection using Principal Component Analysis (PCA), which enables the analytical superiority of machine learning algorithms such as Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), and Random Forest Regression (RFR) over conventional univariate techniques for phase discrimination and chemometric analysis. Cluster analysis revealed how both matrix effects and laser ablation influence cluster separability by introducing spectral artifacts that misdirect the maximization of variance. PCA-selected emission lines were used in the regression models, demonstrating that both univariate and multivariate linear regression models (i.e., PLSR and SVR) can achieve acceptable performance, with machine learning models outperforming conventional calibration regressions. Furthermore, the application of non-linearly activated PCA-selected emission lines illustrates how simplifying the data while retaining captured variance enables the use of less complex and more computationally efficient models. Furthermore, this is particularly evident in the underperformance of RFR, which suffers from increased computational costs and overfitting owing to its high complexity.

Oxalates↗

Elephant range and population, strontium isotopes, and genetics combine to give local-scale specificity to ivory hotspot tracking

We use Sr isotopes to increase the precision of DNA-based origin estimates of wildlife products. Population information is used to develop Sr isotope Elephant Polygons that are overlaid onto the region of origin identified by DNA assignment to determine the sources of seized ivory samples. Our approach is cognizant of isotope mixing due to isotope turnover within animals and also of the large home range of elephants or other mobile species. Genetic information from 3 different law enforcement ivory seizures suggests a region of origin confined to Kenya and Tanzania in eastern Africa. We determine characteristic 87 Sr/ 86 Sr ratios for each of 25 different Elephant Polygons within this region using analyses of more the 600 known-origin reference samples. Using both the 87 Sr/ 86 Sr ratios of the seized ivory samples and elephant population estimates from individual Elephant Polygons we find that at least 75 % of the samples likely came from a single Elephant Polygon which includes the Tsavo National Parks in Kenya and the Mkomazi National Park in Tanzania. A few samples may have come from other regions, most likely from Tanzania. This study illustrates the value of combining genetics, isotope geochemistry, and population surveys in wildlife forensics studies.

Africa↗

Rapid Characterization and Statistical Analysis of High-Volume Field-Harvested Photovoltaic Connectors

Photovoltaic (PV) installations heavily depend on connectors for efficient module and string interconnections without requiring skilled labor. Yet this seemingly innocuous component of PV systems is a leading cause of module failures, multiple high-profile fires, and lawsuits in the PV industry. This work aims to answer critical questions regarding why connectors fail and the contributing factors to their failure. The study involves collecting and analyzing more than 17,000 field-harvested connectors from various solar installations across the United States. The vast dataset, which includes connector metadata, visual inspections, and resistance measurements, provides unprecedented insight into the state of health of PV connectors across the US, including the geographic locations, connector types, and installation practices most prone to failures. The work presented here describes a novel rapid characterization method for processing large numbers of connectors and is supported by parallel forensic analysis to discern the root causes of failures as well as a levelized cost of lifetime model to determine the economic ramifications of connector failure. Ultimately, the findings may inform PV developers about the best practices to extend connector longevity and lead to more resilient and reliable PV systems.

connectors↗

A Framework for Inverse Prediction Using Functional Response Data

Inverse prediction models have commonly been developed to handle scalar data from physical experiments. However, it is not uncommon for data to be collected in functional form. When data are collected in functional form, it must be aggregated to fit the form of traditional methods, which often results in a loss of information. For expensive experiments, this loss of information can be costly. In this study, we introduce the functional inverse prediction (FIP) framework, a general approach which uses the full information in functional response data to provide inverse predictions with probabilistic prediction uncertainties obtained with the bootstrap. The FIP framework is a general methodology that can be modified by practitioners to accommodate many different applications and types of data. We demonstrate the framework, highlighting points of flexibility, with a simulation example and applications to weather data and to nuclear forensics. Results show how functional models can improve the accuracy and precision of predictions.

42 ENGINEERING↗

Laser-Induced Plasmas of Plutonium Dioxide in a Double-Walled Cell

Plutonium research has been stifled by the significant number of administrative controls and safety procedures, space and instrumentation limitations in radiological gloveboxes, and the potential for personnel and equipment contamination. To address the limited number of spectroscopic studies in Pu-bearing compounds in the current scientific literature, this work presents the use of double-walled cells (DWCs) in “clean” buildings/laboratories as an alternative to research in radiological gloveboxes. This study reports the first laser-induced breakdown spectroscopy (LIBS) experiments of a PuO 2 pellet contained within a DWC, where the formation of elemental (atomic and ionic) species as well as the evolution from elemental to molecular products (Pu x O y ) was measured. Raman spectroscopy was also used to characterize the surface of the ablated pellet and the particulates deposited on the window of the inner cell. The full width half-maximum of the T 2g band enabled us to obtain an estimate of the temperature at the pellet surface after the ablation pulse and the particulates based on the crystal lattice disorder. Particulates deposited on the window of the DWC during laser ablation were characterized using scanning electron microscopy, where molten irregular particulates and spheroids were observed. This exciting research conducted in a DWC describes our initial attempts to incorporate LIBS in the arsenal of spectroscopic tools for nuclear forensics applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Multivariate regression modelling for gender prediction using volatile organic compounds from hand odor profiles via HS-SPME-GC-MS

The efficacy of using human volatile organic compounds (VOCs) as a form of forensic evidence has been well demonstrated with canines for crime scene response, suspect identification, and location checking. Although the use of human scent evidence in the field is well established, the laboratory evaluation of human VOC profiles has been limited. This study used Headspace-Solid Phase Microextraction-Gas Chromatography-Mass Spectrometry (HS-SPME-GC-MS) to analyze human hand odor samples collected from 60 individuals (30 Females and 30 Males). The human volatiles collected from the palm surfaces of each subject were interpreted for classification and prediction of gender. The volatile organic compound (VOC) signatures from subjects’ hand odor profiles were evaluated with supervised dimensional reduction techniques: Partial Least Squares-Discriminant Analysis (PLS-DA), Orthogonal-Projections to Latent Structures Discriminant Analysis (OPLS-DA), and Linear Discriminant Analysis (LDA). The PLS-DA 2D model demonstrated clustering amongst male and female subjects. The addition of a third component to the PLS-DA model revealed clustering and minimal separation of male and female subjects in the 3D PLS-DA model. The OPLS-DA model displayed discrimination and clustering amongst gender groups with leave one out cross validation (LOOCV) and 95% confidence regions surrounding clustered groups without overlap. The LDA had a 96.67% accuracy rate for female and male subjects. The culminating knowledge establishes a working model for the prediction of donor class characteristics using human scent hand odor profiles.

59 BASIC BIOLOGICAL SCIENCES↗

Challenges in correlating oxygen stable isotope ratios of hydrates on uranium ore concentrates to process waters

Exchange of oxygen stable isotopes (δ 18 O values) between precipitation waters and uranium oxides is governed by thermodynamics or kinetics. It has been assumed that meteoric waters can be related to precipitation waters in uranium ore concentrates and their calcination and reduced uranium oxide products. With this assumption, the δ 18 O values of uranium materials could provide forensic signatures that identify the production history and geolocation of nuclear materials. To further exploit the potential of δ 18 O values in nuclear material analysis, this study examines the oxygen stable isotope exchange in two UOCs, magnesium diuranate (MDU) and sodium diuranate (SDU). MDU and SDU were synthesized from solutions of uranyl nitrate hexahydrate using precipitation waters with unique oxygen isotope compositions. The structures of the MDU and SDU were analyzed using powder X-ray diffraction (p-XRD) and thermal mass loss curves, while the δ 18 O values of waters generated during thermal decomposition were analyzed using a thermogravimetric analyzer coupled to an isotope ratio infrared spectrometer (TGA-IRIS). By p-XRD, the MDU was uniform and amorphous across all syntheses with residual crystalline material incorporated as a minor component. Combined with the TGA results, all of the MDU is likely amorphous MgU 2 O 7 ·3H 2 O with MgO impurities present throughout. In contrast, the SDU synthesis resulted in multiple phases with many samples exhibiting crystalline phases including a combination of Na(UO 2 ) 4 O 2 (OH) 5 ·5H 2 O and Na 2 (UO2) 6 O 4 (OH) 6 ·8H 2 O with a Na 2 U 2 O 7 minor phase. A small fraction of the SDU samples were amorphous with no crystalline XRD peaks observed. Mass loss curves of the SDU samples revealed that the amorphous samples contained inclusions of similar crystalline phases compared to the crystalline materials. The uniformity of the MDU samples enabled highly reproducible measurements of δ 18 O values of the water vapor yielded for two dehydration events at 170 °C and 500 °C. In contrast, the multiphase composition of the SDU samples resulted in poor reproducibility in δ 18 O values. In conclusion, neither system revealed any correlation between the δ 18 O values of precipitation water, and the waters released during dehydration of the UOCs.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Characterization of Uranium Foil Irradiations at the WSU TRIGA Reactor Using a New Reactor Model in Scale

A new reactor model of the Washington State University TRIGA was developed in the SCALE neutron transport code, and its fidelity was verified by comparison to MCNP and available data for several reactor parameters. The model was used to characterize irradiations designed to produce the short-lived actinides 237 U and 239 U, two key isotopes for nuclear forensics. These short-lived actinides, their decay daughters 237Np and 239Pu, and total fissions (via 99 Mo) were measured in irradiated foils at Los Alamos National Laboratory and other labs with good agreement among parent/daughter pairs and among labs. The laboratory-measured isotope ratios were used as a benchmark for the model determination of reaction rates. The flux distribution in the foils was also determined. Finally, using the continuous energy TSUNAMI-3D module of SCALE, a sensitivity/uncertainty analysis was performed to determine the effects on foil reactions caused by other system-wide reactions and by uncertainties in the known cross-sections.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NREL’s Cyber-Energy Emulation Platform for Research and System Visualization

This paper presents NREL’s Cyber Energy Emulation (CEE) Platform. This is a novel emulation platform for achieving real-time visualization of large-scale environments involving cyber-physical devices. It allows for the environment to include real, physical hardware, along with emulated devices communicating with each other as part of the same system. The CEE Platform is also capable of streaming, collecting, storing, transporting, and visualizing all data within the emulated environment. By providing this capability, it enables high-fidelity visual analysis of events to be performed in real time as well as the use of historical data for forensic analysis. This paper presents the design of the CEE Platform as well as several potential use cases and applications. It also aims to highlight why this type of visualization tool has potential for research and education about cyber-physical systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Improving robustness for model discerning synthesis process of uranium oxide with unsupervised domain adaptation

The quantitative characterization of surface structures captured in scanning electron microscopy (SEM) images has proven to be effective for discerning provenance of an unknown nuclear material. Recently, many works have taken advantage of the powerful performance of convolutional neural networks (CNNs) to provide faster and more consistent characterization of surface structures. However, one inherent limitation of CNNs is their degradation in performance when encountering discrepancy between training and test datasets, which limits their use widely. The common discrepancy in an SEM image dataset occurs at low-level image information due to user-bias in selecting acquisition parameters and microscopes from different manufacturers. Therefore, in this study, we present a domain adaptation framework to improve robustness of CNNs against the discrepancy in low-level image information. Furthermore, our proposed approach makes use of only unlabeled test samples to adapt a pretrained model, which is more suitable for nuclear forensics application for which obtaining both training and test datasets simultaneously is a challenge due to data sensitivity. Through extensive experiments, we demonstrate that our proposed approach effectively improves the performance of a model by at least 18% when encountering domain discrepancy, and can be deployed in many CNN architectures.

scanning electron microscopy↗

Crime scene investigations using portable, non-destructive space exploration technology

The National Institute of Justice (NIJ) and the National Aeronautics and Space Administration's (NASAs) Goddard Space Flight Center (GSFC) have teamed up to explore the use of NASA developed technologies to help criminal justice agencies and professionals solve crimes. The objective of the program is to produce instruments and communication networks that have application within both NASA's space program and NIJ programs with state and local forensic laboratories. A working group of NASA scientists and law enforcement professionals has been established to develop and implement a feasibility demonstration program. Specifically, the group has focused its efforts on identifying gunpowder and primer residue, blood, and semen at crime scenes. Non-destructive elemental composition identification methods are carried out using portable X-ray fluorescence (XRF) systems. These systems are similar to those being developed for planetary exploration programs. A breadboard model of a portable XRF system has been constructed for these tests using room temperature silicon and cadmium-zinc telluride (CZT) detectors. Preliminary tests have been completed with gunshot residue (GSR), blood-spatter and semen samples. Many of the element composition lines have been identified. Studies to determine the minimum detectable limits needed for the analyses of GSR, blood and semen in the crime scene environment have been initiated and preliminary results obtained. Furthermore, a database made up of the inorganic composition of GSR is being developed. Using data obtained from the open literature of the elemental composition of barium (Ba) and antimony (Sb) in handswipes of GSR, we believe that there may be a unique GSR signature based on the Sb to Ba ratio.

Firearms↗

Ambient Mass Spectrometry Rapid Analysis Methods for Trace Inorganics

The ability to rapidly detect and characterize the chemistry of trace quantities of inorganic species has multiple potential applications, including nuclear safeguards, nuclear forensics, and environmental monitoring. Some mass spectrometric methods currently exist, but they are costly and time-intensive, often destroying chemical information in the process of ionization. Ambient mass spectrometry is a relatively new analytical method in which samples are introduced to the mass spectrometer from atmospheric pressure, rather than from high vacuum. Ambient MS can operate with gentler ionization methods such as electrospray ionization (ESI) and paper-spray ionization (PSI), reducing fragmentation and preserving the chemical information of the analyte. This may be useful for determining the intended purpose of material in a sample. Strontium, part of nuclear fallout, is analyzed here to test these new analytical methods for viability. Electrospray ionization mass spectrometry functions by spraying the sample as a solution through a needle charged to a few kV. A nebulizing gas flows out along with the sample to create the spray before droplets enter a drying chamber with heated drying gas to remove the solvent molecules. From there bare analyte ions enter the mass spectrometer. This method has the advantage of relatively fast sample preparation and stable ionization. More stable ionization produces higher-quality data. Paper-spray ionization mass spectrometry operates by applying sample to a paper triangle. The paper triangle is then electrified in a metal clamp to a few kV before spray solvent is applied. The spray solvent transports analyte in the sample to the tip, where it is ionized and enters the mass spectrometer. One advantage of this method is reduced sample preparation - an analyst can even swipe a surface and cut a triangle directly from the swipe. The data analysis serves to rapidly process tens of samples all at once. The mass spectrometer outputs a file containing a few hundred spectra for each sample. The pipeline processes each one to identify peaks of interest. A full palette of data analysis metrics are generated, including plots of the raw data and plots of calculated values such as isotopic ratios. The pipeline filters the raw data to remove noise and background peaks, as well as peaks representing detector saturation. A heat map is generated to show the overall spectrum in mass-time- intensity space. Post-processing, we obtained the desired calibration curves, demonstrating that both ESI-MS and PSI-MS are viable methods for quantifying trace amounts of inorganics while retaining their chemical speciation information. ESI-MS demonstrated a linear response region of 100 ppb to 20 ppm, with a limit-of-detection of around 100 ppb. At top left is an example spectrum with the {sup 88}SrNO{sub 3} peak identified to show the retention of chemical speciation. PSI-MS showed a linear response region of around 1 ppb to 1 ppm, with a limit-of-detection of near 1 ppb. PSI-MS produced more erratic results than ESI-MS, likely due to the variability in ionization resulting from manual positioning of the paper triangle near the MS inlet. Future efforts will focus on improving the repeatability of PSI-MS as well as analyzing other species of interest such as cerium and uranium. Improvements will also be made to create more reliable data extraction and intelligent data filtering.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Direct Alpha Spectrometry of Nuclear Fallout

Advanced instruments and methods are under development to allow direct alpha spectrometry of nuclear fallout debris near the point of collection, to support nuclear forensics (NF). New approaches are needed to support NF in order to accelerate the process for data generation and reduce the overall timeline for decision making. Fallout debris at short time periods following detonation can be difficult to work with for alpha spectrometry, due to the presence of intense beta radiation originating from significant quantities of high-activity fission products. Intense beta radiation can challenge traditional silicon-based high-resolution alpha spectrometers. Addressing this, single-crystal (sc) chemical vapor deposition (CVD) produced diamond semiconductors have been studied for use for alpha spectrometry for assaying nuclear fallout debris. Tests have been performed using scCVD sensors to assay a variety of actinide-bearing samples. Sample preparation, when done, has been limited to pulverization using a mechanical ball mill. To reduce measurement times, multi-chip arrays of scCVD diamond semiconductor have been developed in form factors suitable for field deployment in support of NF objectives. These arrays have been tested using high-beta-activity sol gel surrogate nuclear explosive debris (SNED) containing varying concentrations of uranium and plutonium. Results from the use of scCVD detectors with sol gel SNED will be presented.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Visualizing the Nanoscale Oxygen and Cation Transport Mechanisms during the Early Stages of Oxidation of Fe–Cr–Ni Alloy Using In Situ Atom Probe Tomography

Abstract Understanding the early stages of interactions between oxygen and material surfaces—especially at very high spatial resolutions—is highly beneficial for fields ranging from materials degradation, corrosion, geological sciences, forensics, and catalysis. The ability of in situ atom probe tomography (APT) is demonstrated to track the diffusion of oxygen and metal ions at nanoscale spatial resolution during the early stages of oxidation of a model Fe–Cr–Ni alloy. Using 18 O isotope tracers in these in situ APT experiments and complementary ex situ multimodal microscopy, spectroscopy, and computational simulations allows to precisely analyze the kinetics of oxidation and determine that outward cation diffusion to oxide/air interface is the primary mechanism for intragranular oxide growth in this alloy at 300 °C. This unique in situ isotopic tracer APT approach and the insights gained can be highly beneficial for studying early stages of gas–surface reactions in a broad array of materials.

36 MATERIALS SCIENCE↗