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DOE OSTI2025

Monte Carlo N-Particle Transport Performance of Predicting Digital Radiographic IQI Inspection

The identification of porosity, geometric noncompliance, and other defect types are critical to the qualification of materials and components. X-ray radiographic nondestructive testing is a common industrial inspection method for process quality control and component qualification and certification. Digital radiography provides a quick and efficient alternative when compared to traditional film-based inspection. The quality of radiographic inspection is dependent on equipment specifications, such as the source spot size and detector pixel size, and the specific parameters selected for use for the radiographic technique. To evaluate if an x-ray system and technique is sufficient for a given requirement, a radiographic image quality indicator (IQI) can be used. Radiographic IQIs in hard to machine materials or hard to manufacture defects can be time consuming and expensive to manufacture. This study was conducted to evaluate current Savannah River National Laboratory (SRNL) x-ray imaging systems with a custom tantalum IQI and using Monte Carlo simulations to predict the performance of future systems. The tantalum IQI was tested using a Siefert Isovolt 420 keV x-ray tube with a Perkin Elmer XRD 1611 flat panel with 100-micron pixels. Using the Monte Carlo N-Particle transport software, the radiographic tally was used to simulate the photon flux through an identical tantalum IQI. These simulations provided a benchmark as to the best theoretical identification on a given system using our tantalum IQI. The simulations were refined to match SRNL’s current systems’ noise levels, leading to confidence in their ability to predict the performance of other systems that may be purchased and deployed in the future at the Savannah River Site. Future studies will be conducted to prove this research can be extended to artificially evaluate the ability for systems to identify critical defect sizes through x-ray radiographic inspection, drastically reducing the cost and time burdens of producing high-fidelity radiographic test articles.

digital X-ray radiography↗

NASA NTRS1994

MME-based attitude dynamics identification and estimation for SAMPEX

A method is described for obtaining optimal attitude estimation algorithms for spacecraft lacking attitude rate measurement devices (rate gyros), and then demonstrated using actual flight data from the Solar, Anomalous, and Magnetospheric Particle Explorer (SAMPEX) spacecraft. SAMPEX does not have on-board rate sensing, and relies on sun sensors and a three-axis magnetometer for attitude determination. Problems arise since typical attitude estimation is accomplished by filtering measurements of both attitude and attitude rates. Rates are nearly always sampled much more densely than are attitudes. Thus, the absence/loss of rate data normally reduces both the total amount of data available and the sampling density (in time) by a substantial fraction. As a result, the sensitivity of the estimates to model uncertainty and to measurement noise increases. In order to maintain accuracy in the attitude estimates, there is increased need for accurate models of the rotational dynamics. The proposed approach is based on the minimum model error (MME) optimal estimation strategy, which has been successfully applied to estimation of poorly modeled dynamic systems which are relatively sparsely and/or noisily measured. The MME estimates may be used to construct accurate models of the system dynamics (i.e. perform system model identification). Thus, an MME-based approach directly addresses the problems created by absence of attitude rate measurements.

Depena, Juan↗

NASA NTRS1995

Clouds and the Earth's Radiant Energy System (CERES) Algorithm Theoretical Basis Document: Cloud Analyses and Determination of Improved Top of Atmosphere Fluxes (Subsystem 4) - Volume 3

The theoretical bases for the Release 1 algorithms that will be used to process satellite data for investigation of the Clouds and Earth's Radiant Energy System (CERES) are described. The architecture for software implementation of the methodologies is outlined. Volume 3 details the advanced CERES methods for performing scene identification and inverting each CERES scanner radiance to a top-of-the-atmosphere (TOA) flux. CERES determines cloud fraction, height, phase, effective particle size, layering, and thickness from high-resolution, multispectral imager data. CERES derives cloud properties for each pixel of the Tropical Rainfall Measuring Mission (TRMM) visible and infrared scanner and the Earth Observing System (EOS) moderate-resolution imaging spectroradiometer. Cloud properties for each imager pixel are convolved with the CERES footprint point spread function to produce average cloud properties for each CERES scanner radiance. The mean cloud properties are used to determine an angular distribution model (ADM) to convert each CERES radiance to a TOA flux. The TOA fluxes are used in simple parameterization to derive surface radiative fluxes. This state-of-the-art cloud-radiation product will be used to substantially improve our understanding of the complex relationship between clouds and the radiation budget of the Earth-atmosphere system.

Source record↗

DOE OSTI2024

Deriving the Infrared Complex Refractive Indices of Organic Powders for Optical Modeling: Comparison of Methods

Identification of solids via infrared reflection spectroscopy requires a spectral library of all solids likely to be encountered. A confounding factor in populating such a spectral library is that the reflectance spectra of solids vary with their form, including particle size, film thickness, and substrate. To reduce the efforts of experimentally constructing such a library, an alternate strategy is to use the wavelength-dependent optical constants, n and k, of a solid to calculate a series of reflectance spectra corresponding to each scenario or morphology. Because most n/k measurements are best performed on mm-sized crystals, however, the challenge of determining the optical constants increases when a solid is only readily available as a powder, as is often the case. Some organic solids, such as caffeine, are both unavailable in large crystals and difficult to press into pellets. In this study, the infrared optical constants, or complex refractive indices, of caffeine were determined using three different methods: single-angle reflectance, infrared spectroscopic ellipsometry, and quantitative absorbance measurements of KBr pellets. The n and k values derived through each method were used to model the hyperspectral imaging reflectance spectrum of a caffeine film on a steel planchet. Over 1,110 – 870 cm-1, the single-angle reflectance-derived n and k had the best correlation with the experimental spectrum. These results suggest different organic solids may require different methods to determine the most accurate infrared complex refractive indices for synthetic spectral libraries.

FTIR, hyperspectral imaging, infrared, infrared (I↗

NASA NTRS1995

Use of nonlinear identification in robust attitude and attitude rate estimation for SAMPEX

A method is described for obtaining optimal attitude estimation/identification algorithms for spacecraft lacking attitude rate measurement devices (rate gyros), and then demonstrated using actual flight data from the Solar, Anomalous, and Magnetospheric Particle Explorer (SAMPEX) spacecraft. SAMPEX does not have on-board rate sensing, and relies on sun sensors and a three-axis magnetometer for attitude determination. The absence of rate data normally reduces both the total amount of data available and the sampling density (in time) by a substantial fraction. In addition, attitude data is occasionally unavailable (for example, during sun occultation). As a result, the sensitivity of the estimates to model uncertainty and to measurement noise increases. In order to maintain accuracy in the attitude estimates, there is an increased need for accurate models of the rotational dynamics. The Minimum Model Error(MME)/Least Square Correlation(LSC) algorithm accurately identifies an improved model for SAMPEX to be used during periods of complete data loss or extreme noise. The model correction is determined by estimating only one orbit(the identification pass) just prior to the assumed data loss(the prediction pass). The MME estimator correctly predicted the states during the identification phase, but more importantly determines the necessary model correction trajectory, d(t). The LSC algorithm is then used to find this trajectory's functional form, H(x(t)). The results show significant improvement of the new corrected model's attitude estimates as compared to the original uncorrected model's estimates. The possible functional form of the correction term is limited at this point in the study to functions strictly of the estimated states. The results, however, strongly suggest that functions based on the relative position of the satellite may also be possible candidates for future consideration.

Mook, D. Joseph↗

NASA NTRS2018

Advanced Curation Development of Tools and Methods for Microparticle Curation

The Astromaterials Acquisition and Curation Office at NASA Johnson Space Center is currently developing new tools and methods for the collection, storage, handling and characterization of particles less than 100 microns in diameter, or microparticles. Astromaterials Curation currently maintains four microparticle collections: Cosmic Dust that has been collected in Earth’s stratosphere by ER2 and WB-57 aircraft, Comet 81P/Wild 2 dust returned by NASA’s Stardust spacecraft, interstellar dust that was returned by Stardust, and asteroid Itokawa particles that were returned by the JAXA (Japan Aerospace Exploration Agency)’s Hayabusa spacecraft. NASA Curation is currently preparing for the anticipated return of two new astromaterials collections – asteroid Ryugu regolith to be collected by Hayabusa II spacecraft in 2021 (samples will be provided by JAXA as part of an international agreement), and asteroid Bennu regolith to be collected by the OSIRIS-REx (Origins Spectral Interpretation Resource Identification Security - Regolith Explorer) spacecraft in 2023. In order to maximize the scientific yield from these valuable acquisitions, it will be necessary to develop methods that extend our current microsample handling capabilities. Here we describe recent progress in the development of sample handling techniques that will enhance our microparticle curation capabilities. Further described are: Six-Axis Robot Arms for Particle Manipulation, and Charge-Dissipative Substrates.

Snead, Christopher↗

DOE OSTI2025

Summer 2025 SULI: Nucleus ID, TinyTPC, and Scientific Communication

This paper summarizes my work during the Summer 2025 SULI internship, which focused on two main projects and broader scientific development. The first project involved improving the particle identification (PID) of protons, deuterons, and tritons using PIDA distributions and template fitting, with the goal of modeling nuclear final-state interactions (FSI) and testing the robustness of the method against systematic uncertainties. These techniques pave the way for future application to LArTPC data from the ICARUS detector. The second project centered on the optimization and data-taking of the TinyTPC detector, a compact LArTPC used for high-resolution low-energy measurements. I adjusted gain and threshold parameters, performed hardware validation tests, and developed analysis strategies to extract meaningful physics from collected data. Throughout the summer, I also enhanced my scientific communication and mentorship skills through presentations, collaborative analysis, and peer guidance.

McCright, Hannah [Maryland U.]↗

NASA NTRS1975

Air pollution source identification

The techniques available for source identification are reviewed: remote sensing, injected tracers, and pollutants themselves as tracers. The use of the large number of trace elements in the ambient airborne particulate matter as a practical means of identifying sources is discussed. Trace constituents are determined by sensitive, inexpensive, nondestructive, multielement analytical methods such as instrumental neutron activation and charged particle X-ray fluorescence. The application to a large data set of pairwise correlation, the more advanced pattern recognition-cluster analysis approach with and without training sets, enrichment factors, and pollutant concentration rose displays for each element is described. It is shown that elemental constituents are related to specific source types: earth crustal, automotive, metallurgical, and more specific industries. A field-ready source identification system based on time and wind direction resolved sampling is described.

Fordyce, J. S.↗

DOE OSTI2025

Identification of $^{3}$He–$^{3}$H clusters in the $^{6}$Li+$^{89}$Y experiment using particle-$\gamma$ coincidence measurement

The 6 Li+ 89 Y experiment was performed to explore the reaction mechanism induced by a weakly bound nucleus 6 Li and its cluster configuration. Here, the particle-$\gamma$ coincidence method was used to identify the different reaction channels. The $\gamma$-rays coincident with 3 He/ 3 H indicate that the 3 H/ 3 He stripping reaction plays a significant role in the formation of Zr/Nb isotopes. The obtained results support the existence of a 3 He- 3 H cluster in 6 Li. Direct and sequential transfer reactions are adequately discussed, and the FRESCO code is used to perform precise finite-range cyclic redundancy check calculations. In the microscopic calculation, direct cluster transfer is more predominant than sequential transfer in 3 H transfer. However, the direct cluster transfer is of comparable magnitude to the sequential transfer in the 3 He transfer.

CRC calculations↗

NASA NTRS2024

Harnessing Collaborative Learning Automata to Guide Multi-objective Optimization based Inverse Analysis for Structural Damage Identification

Structural damage identification based on physical models is often transformed into an optimization problem that minimizes the difference between measurement information of structure being monitored and the model prediction in the parametric space. However, the objective function in this context often exhibits multimodality, involving high-dimensional variables due to the reliance on finite element models for damage identification. These features pose challenges to optimization algorithms, where entrapment in local solutions can lead to false positives and false negatives in damage identification. In this research, we propose a reinforcement learning based multi-swarm optimizer to tackle such challenges in pursuit of a small yet diverse solution set that can capture the true damage scenario as one of the solutions. The proposed method leverages the flexibility of the particle swarm optimizer and incorporates novel strategies of metaheuristics to realize targeted improvement. To enable the particle swarm to adaptively select the appropriate search strategy based on the current environment, we adopt the learning automata technique, which sidesteps the need for reward strategy selection that is usually ad hoc at each step of the search. The integration harnesses the automatic learning and self-adaptation capabilities of learning automata, enabling the particles to navigate based on environmental signals. This leads to accumulated probabilities tied to advantageous movements, fostering an adaptive exploration of particles in the search space. The proposed approach is first validated through implementing into benchmark test cases with comparisons. It is then applied to structural damage identification with piezoelectric admittance experimental signals. `The results highlight the capability of the algorithm to identify a small solution set with high accuracy to match the actual damage scenario.

Yang Zhang↗

NASA NTRS1973

Identification of comet nucleus from comet coma.

The study of comets is of important scientific value as part of the exploration of the solar system. This paper proposes a method, called 'stationary target identification,' to detect the nucleus within the coma. The method makes use of the fact that the coma is ever expanding about the nucleus. Therefore, when a radar beam is used for detection, the coma particles will produce a return signal that is Doppler shifted. The effects of the spatial extent of the coma and Doppler bandwidth of the coma returns upon the required data processing are considered. Also different methods of implementation are considered.-

Brock, H. I.↗

NASA NTRS1974

X-ray diffraction identification of minerals in lunar regolith returned by Luna 16 automatic station

The methods of powder and monocrystal X-ray diffraction served in identifying the mineral composition of gross samples of regolith from different levels of the drill core and about 80 individual regolith particles returned by the Luna 16 station. It was established that the Sea of Fertility regolith includes pyroxenes of the augite-pigeonite series, anorthites, ilmenite, olivines, spinels, alpha cristobalite, iron particles, glass, and several as yet unidentified particles. Crystallographic and roentgenometric data are given for all the lunar minerals found.

Makarov, Y. S.↗

NASA NTRS2005

Lunar and Planetary Science XXXVI, Part 7

Topics discussed include: Lunar Geologic Mapping: Preliminary Mapping of Copernicus Quad High-Resolution Topography of Layers in the Valles Marineris Via Thermoclinometry ; The Critical Importance of Data Reduction Calibrations in the Interpretability of S-type Asteroid Spectra; (sup 238)U-(sup 206)Pb Age and Uranium-Lead Isotope Systematics of Mare Basalt 10017; Morphological Investigations of Martian Spherules, Comparisons to Collected Terrestrial Counterparts; The Vapor Pressure of Palladium at Temperatures up to 1973K; Areas of Favorable Illumination at the Lunar Poles Calculated from Topography; An Indigenous Origin for the South Pole-Aitken Basin Thorium Anomaly; Ar-Ar Ages of Nakhlites Y000593, NWA998, and Nakhla and CRE Ages of NWA998; Experiments on the Acoustic Properties of Titan-like Atmospheres; Analysis of Downstream Transitions in Morphology and Structure of Lava Channels on Mars; Structure and Bonding of Carbon in Clays from CI Carbonaceous Chondrites; Comparison of Three Hydrogen Distributions at the Equator of Mars; An Impact Origin for the Foliation of Ordinary Chondrites; A New Micrometeorite Collection from Antarctica and Its Preliminary Characterization by Microobservation, Microanalysis and Magnetic Methods; Volcanic Plumes and Plume Deposits on Io; Results of the Alpha-Particle-X-Ray Spectrometer on Board of the Mars Exploration Rovers; Effects of Oceans on Atmospheric Loss During the Stage of Giant Impacts; and Identification of Predominant Ferric Signatures in Association to the Martian Sulfate Deposits

Source record↗

NASA NTRS1976

A thermoluminescent method for aerosol characterization

A thermoluminescent method has been used to study the interactions of aerosols with ozone. The preliminary results show that ozone reacts with many compounds found in aerosols, and that the thermoluminescence curves obtained from ozonated aerosols are characteristic of the aerosol. The results suggest several important applications of the thermoluminescent method: development of a detector for identification of effluent sources; a sensitive experimental tool for study of heterogeneous chemistry; evaluation of importance of aerosols in atmospheric chemistry; and study of formation of toxic, electronically excited species in airborne particles.

Long, E. R., Jr.↗

DOE OSTI2026

Dual particle imaging using time-of-flight neutron classification

Fast-neutron imaging technology is well-suited for passive nuclear material monitoring, secondary inspection of flagged cargo, and wide-area search for lost neutron sources. However, imaging systems that use pulse shape discrimination for event classification require complex pulse waveform analysis. In this work, we evaluate time-of-flight (TOF) based particle classification as an alternative solution for fast-neutron imaging by classifying all events with a TOF above a maximum threshold as neutrons. We measured a Cf-252 source next to Cs-137 using a 12-bar organic-glass scintillator array. By varying the TOF thresholds for neutron identification, we demonstrate a clear trade-off between event yield and backprojection image fidelity, with stricter thresholds improving precision at the cost of statistics, TOF thresholded data generated an image that predicted the neutron source direction with 20% reduced mean central angle prediction error compared to a traditional pulse shape discrimination (PSD) method with comparable event count. Time-of-flight particle classification shows promise as an alternative to pulse shape discrimination systems for fast neutron imaging systems looking to minimize costs and size of electronics with comparable imaging quality. The sources used demonstrate that the method is effective in classifying measured neutrons in a measurement environment with 150 μCi Cs-137 and 1.6 × 10 6 n/s Cf-252 sources positioned at distances of 66 cm and 81 cm from the detector. Additionally, the method classifies low-energy neutron events that pulse shape discrimination removes, so a combination of both methods would result in a higher overall neutron event efficiency.

Heriot, William [Univ. of Michigan, Ann Arbor, MI ↗

NASA NTRS1983

Extraction of cloud cover parameters from multispectral satellite measurements

An approach to the extraction of cloud cover parameters from multispectral satellite measurements is proposed which combines the best features of the threshold method and of the cluster approach. The approach proposed here utilizes radiative transfer equations, as in the threshold method, along with the identification of clusters in the two-dimensional histogram formed by the visible and 11-micron infrared channels. Information from a third channel, at 3.7 microns, is used to determine the microphysical model of the cloud particles. Examples of applications of the proposed approach are presented.

Arking, A.↗

DOE OSTI2024

Identifying Neutrino Final States and Energies in MicroBooNE with New Deep-Learning Based LArTPC Reconstruction Frameworks

MicroBooNE, a Liquid Argon Time Projection Chamber (LArTPC) located in the $\nu_{\mu}$-dominated Booster Neutrino Beam at Fermilab, has been studying $\nu_{e}$ charged-current (CC) interaction rates to shed light on the MiniBooNE low energy excess. The LArTPC technology employed by MicroBooNE provides the capability to image neutrino interactions with mm-scale precision. Computer vision and other machine learning techniques are promising tools for image processing that could boost efficiencies for selecting $\nu_{e}$-CC and other rare signals, reduce cosmic and beam-induced backgrounds, and improve the reconstruction of neutrino energies. The MicroBooNE experiment has been at the forefront of developing and testing such techniques for use in physics analyses. In this poster we overview deep-learning based reconstruction methods. We will showcase the use of a recurrent neural network to estimate neutrino energies and present a new reconstruction framework that uses convolutional neural networks to locate neutrino interaction vertices, tag pixels with track and shower labels, and perform particle identification on reconstructed clusters. We will present studies characterizing the performance of these new tools and demonstrate their effectiveness through their use in an inclusive $\nu_{e}$-CC event selection.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1975

Contamination Control in Hybrid Microelectronic Modules. Part 1: Identification of Critical Process and Contaminants

Various hybrid processing steps, handling procedures, and materials are examined in an attempt to identify sources of contamination and to propose methods for the control of these contaminants. It is found that package sealing, assembly, and rework are especially susceptible to contamination. Moisture and loose particles are identified as the worst contaminants. The points at which contaminants are most likely to enter the hybrid package are also identified, and both general and specific methods for their detection and control are developed. In general, the most effective controls for contaminants are: clean working areas, visual inspection at each step of the process, and effective cleaning at critical process steps. Specific methods suggested include the detection of loose particles by a precap visual inspection, by preseal and post-seal electrical testing, and by a particle impact noise test. Moisture is best controlled by sealing all packages in a clean, dry, inert atmosphere after a thorough bake-out of all parts.

Himmel, R. P.↗