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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.

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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Review of the High Performance Antiproton Trap (HiPAT) Experiment at the Marshall Space Flight Center

The significant energy density of matter-antimatter annihilation is attractive to the designers of future space propulsion systems, with the potential to offer a highly compact source of power. Many propulsion concepts exist that could take advantage of matter-antimatter reactions, and current antiproton production rates are sufficient to support basic proof-of-principle evaluation of technology associated with antimatter- derived propulsion. One enabling technology for such experiments is portable storage of low energy antiprotons, allowing antiprotons to be trapped, stored, and transported for use at an experimental facility. To address this need, the Marshall Space Flight Center's Propulsion Research Center is developing a storage system referred to as the High Performance Antiproton Trap (HiPAT) with a design goal of containing 10(exp 12) particles for up to 18 days. The HiPAT makes use of an electromagnetic system (Penning- Malmberg design) consisting of a 4 Telsa superconductor, high voltage electrode structure, radio frequency (RF) network, and ultra high vacuum system. To evaluate the system normal matter sources (both electron guns and ion sources) are used to generate charged particles. The electron beams ionize gas within the trapping region producing ions in situ, whereas the ion sources produce the particles external to the trapping region and required dynamic capture. A wide range of experiments has been performed examining factors such as ion storage lifetimes, effect of RF energy on storage lifetime, and ability to routinely perform dynamic ion capture. Current efforts have been focused on improving the FW rotating wall system to permit longer storage times and non-destructive diagnostics of stored ions. Typical particle detection is performed by extracting trapped ions from HiPAT and destructively colliding them with a micro-channel plate detector (providing number and energy information). This improved RF system has been used to detect various plasma modes for both electron and ion plasmas in the two traps at MSFC, including axial, cyclotron, and diocotron modes. New diagnostics are also being added to HiPAT to measure the axial density distribution of the trapped cloud to match measured RF plasma modes to plasma conditions.

Pearson, J. B.↗
DOE OSTI2026

Using 2.5D super-resolution to improve flaw detection in metal additive manufacturing parts

Industrial X-ray computed tomography (XCT) enables non-destructive inspection of additively manufactured (AM) parts, but high-resolution scanning requires long acquisition times and significant computational resources, limiting throughput in production environments. Super-resolution techniques can recover high-resolution information from low-resolution scans, but existing methods face a trade-off between 2D approaches that ignore inter-slice information and 3D methods that are computationally prohibitive for practical deployment. To address this trade-off, we propose a 2.5D deep learning-based super-resolution approach that uses seven neighbouring low-resolution slices to super-resolve the centre slice. This work evaluates the method on real XCT scans of steel AM parts, comparing reconstruction quality and flaw detection performance of 2D, 2.5D, and 3D ESRGAN-based super-resolution methods. Results demonstrate that 2.5D super-resolution significantly improves detection of small, process-induced flaws (e.g. porosity) compared to 2D methods, while avoiding the prohibitive computational burden of full 3D approaches. These findings provide initial evidence of 2.5D super-resolution as a practical, deployable solution for improving flaw detection in high-throughput industrial XCT inspection.

X-ray CT↗
NASA NTRS2007

Contribution of Chlorophyll Fluorescence to the Apparent Reflectance of Vegetation

Current strategies for monitoring the physiologic status of terrestrial vegetation rely on remote sensing reflectance (R) measurements, whi ch provide estimates of relative vegetation vigor based primarily on chlorophyll content. Vegetation chlorophyll fluorescence (CF) offers a non-destructive alternative and a more direct approach for diagnosis of vegetation stress before a significant reduction in chlorophyll content has occurred. Thus, monitoring of vegetation vigor based on CF may allow earlier stress detection and more accurate carbon sequestra tion estimates, than is possible using R data alone. However, the observed apparent vegetation reflectance (Ra) in reality includes contrib utions from both the reflected and fluoresced radiation. The aim of t his study is to determine the relative R and CF fractions contributing to Ra from the vegetation in the red to near-infrared region of the spectrum. The practical objectives of the study are to: 1) evaluate t he relationship between CF and R at the foliar level for corn, soybean, maple; and 2) for corn, determine if the relationship established f or healthy (optimal N) vegetation changes under N defiiency. To obtai n generally applicable results, experimental measurements were conducted on unrelated crop and tree species (maple, soybean and corn), unde r controlled conditions and a gradient of inorganic N fertilization l evels. Optical R spectra and actively induced CF emissions were obtained on the same foliar samples, in conjunction with measurements of p hotosynthetic function, pigment levels, and C and N content. The comm on spectral trends or similarities were examined. On average, 10-20% of apparent R at 685 nm was actually due to CF. The spectral trends in steady and maximum F varied significantly, with Fs (especially red) showing higher ability for species and treatment separation. The relative contribution of ChF to R varied significantly among species, with maple emitting much higher F amounts, as compared to corn and soybea n. Fs individual red and far-red bands and their ratio exhibited consistent species separations. For corn, the relative CF fraction increased in concert with the nutrient stress levels from <2% for non-stressed foliage to >7% for severely nutrient deficient plants. F685s provide d optimal treatment separation. This study confirms the trends in F68 5sE740s associated with N deficiency and vegetation stress, established usmg single narrow band excitation.

Campbell, P. K. Entcheva↗
DOE OSTI2024

Mixture-of-Experts for Multi-Domain Defect Identification in Non-Destructive Inspection

Composite materials are widely used in aircraft structures because of their superior mechanical properties. However, their complex failure modes require sophisticated inspection methods to ensure structural integrity. Ultrasonic testing (UT) is a common non-destructive inspection (NDI) technique for aircraft composites that can detect internal and external defects with high resolution and accuracy. Despite their effectiveness, traditional UT methods rely on the manual interpretation of ultrasonic signals, which is time-consuming, labor-intensive, and subjective. Furthermore, processing such large-scale data, particularly across materials of varying thicknesses, significantly increases the computational demands of deep learning model optimization. To overcome these challenges, we propose an efficient sparse mixture-of-experts (MoE) model with a multi-level loss function and introduce four novel training objectives to improve computational efficiency and accuracy in identifying surface defects in composite aircraft materials. Here, we evaluated our approach on material with multiple thicknesses or domains comprising various defects. Our experimental results demonstrate higher accuracy and F1-Score, with only 10% training epochs compared to baseline MoE.

composite materials↗
DOE OSTI2026

Model-based, in-situ, non-destructive qualification and certification of parts made by autonomous additive manufacturing

To address the significant productivity challenges associated with the qualification and certification (Q&C) tasks of additively manufactured (AM) parts, which have traditionally relied on rigorous post‐build inspection and testing, we propose an integrated framework that combines model‐based qualification and certification (MBQ&C) with autonomous additive manufacturing (AAM). MBQ&C employs high‐fidelity predictive models, developed within the Integrated Computational Materials Engineering (ICME) paradigm, to simulate process–structure–property–performance relationships for assessing a part’s fitness for use. Since predictive models are commonly machine learning (ML)-based or reduced-order surrogates of validated physics models, they run efficiently, enabling timely inference. In parallel, the self-driving AAM utilises ML-based adaptive, closed‐loop control strategies to avoid, mitigate, or repair defects and anomalies during fabrication, thereby increasing the likelihood of producing acceptable parts. A key feature of the combined AAM-MBQ&C framework is that predictive models explicitly incorporate defects or anomalies that persist after the build, using instance-specific data captured via in-situ sensing. This customisation enables a build‐specific assessment of fitness for use, rather than relying on nominal or generic parameters. Such individualised evaluation provides a robust basis for Q&C-related acceptance decisions relating to each build. Additionally, the rapid solution capabilities of ML or reduced-order models enable the determination of a part’s suitability for service shortly after build completion. As the framework matures, it has the potential to substantially reduce reliance on conventional point‐design approaches—such as time‐consuming post‐build computed tomography scanning and costly destructive testing. Thus, the AAM-MBQ&C framework represents a transformative, scalable strategy for quality assurance of AM components, as parts produced within a stable, validated, and certified envelope can be certified with reduced testing. Key benefits include: (1) significant gains in Q&C productivity through efficient, model-centric assessment; (2) performance-based classification of defects into critical and non-critical categories; (3) the ability to predict potential deviations in the performance of parts affected by real-time, adaptive process control interventions relative to those produced under a certified process, and (4) the enabling of virtual Q&C for service environments that are difficult, hazardous, or impractical to access or reproduce experimentally. Collectively, these capabilities strengthen the business case for AM, particularly for high‐consequence and mission‐critical applications. Finally, although this work focuses on powder-based AM, the proposed techniques could be extended to AM processes employing alternative feedstock forms.

Gunasegaram, Dayalan↗
DOE OSTI2025

Evaluation of Properties for Microsample Identification

A study was conducted to determine if individual particle characteristics could be used to identify particles of interest, sub-samples, from bulk post-detonation debris. Three archived post-detonation debris samples were used for this effort. Particles from these samples were identified as active (produced fission tracks), and inactive (did not produce fission tracks), as the first defining characteristic. Morphology was the secondary characteristic to select particles for further study, i.e. spherical/non-spherical. Once particles were identified and isolated, they were characterized by optical microscopy for size in µm, number of fission tracks, morphology, transmitted light color, and reflected light color. Particles were then analyzed by scanning electron microscopy for morphology, elemental content, and compound identification. Raman spectroscopy was attempted on five particles with indeterminate results due to environmental mixing (heterogeneity) during the events of particle formation. Once all non-destructive analyses were completed all particles were analyzed by thermal ionization mass spectrometry to determine isotopic atom percents of plutonium and uranium, and an estimate of atoms of plutonium and uranium in each particle. An estimate of the ratio of uranium to plutonium was also obtained (U/Pu). Data analytics of the data from the particles showed that combining characteristics of the particles have a high probability of identifying particles of interest from bulk post-detonation debris samples. Please note that this version of the report is an abridged version of the full report (Wagnon et al. 2025) that has been edited to be appropriate for public release.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
NASA NTRS2010

X-Ray Computed Tomography Inspection of the Stardust Heat Shield

The "Stardust" heat shield, composed of a PICA (Phenolic Impregnated Carbon Ablator) Thermal Protection System (TPS), bonded to a composite aeroshell, contains important features which chronicle its time in space as well as re-entry. To guide the further study of the Stardust heat shield, NASA reviewed a number of techniques for inspection of the article. The goals of the inspection were: 1) to establish the material characteristics of the shield and shield components, 2) record the dimensions of shield components and assembly as compared with the pre-flight condition, 3) provide flight infonnation for validation and verification of the FIAT ablation code and PICA material property model and 4) through the evaluation of the shield material provide input to future missions which employ similar materials. Industrial X-Ray Computed Tomography (CT) is a 3D inspection technology which can provide infonnation on material integrity, material properties (density) and dimensional measurements of the heat shield components. Computed tomographic volumetric inspections can generate a dimensionally correct, quantitatively accurate volume of the shield assembly. Because of the capabilities offered by X-ray CT, NASA chose to use this method to evaluate the Stardust heat shield. Personnel at NASA Johnson Space Center (JSC) and Lawrence Livermore National Labs (LLNL) recently performed a full scan of the Stardust heat shield using a newly installed X-ray CT system at JSC. This paper briefly discusses the technology used and then presents the following results: 1. CT scans derived dimensions and their comparisons with as-built dimensions anchored with data obtained from samples cut from the heat shield; 2. Measured density variation, char layer thickness, recession and bond line (the adhesive layer between the PICA and the aeroshell) integrity; 3. FIAT predicted recession, density and char layer profiles as well as bondline temperatures Finally suggestions are made as to future uses of this technology as a tool for non-destructively inspecting and verifying both pre and post flight heat shields.

McNamara, Karen M.↗
NASA NTRS2005

Lunar and Planetary Science XXXVI, Part 13

Contents include the following: A Fast, Non-Destructive Method for Classifying Ordinary Chondrite Falls Using Density and Magnetic Susceptibility. An Update on Results from the Magnetic Properties Experiments on the Mars Exploration Rovers, Spirit and Opportunity. Measurement Protocols for In Situ Analysis of Organic Compounds at Mars and Comets. Piping Structures on Earth and Possibly Mars: Astrobiological Implications. Uranium and Lead in the Early Planetary Core Formation: New Insights Given by High Pressure and Temperature Experiments. The Mast Cameras and Mars Descent Imager (MARDI) for the 2009 Mars Science Laboratory. MGS MOC: First Views of Mars at Sub-Meter Resolution from Orbit. Analysis of Candor Chasma Interior Layered Deposits from OMEGA/MEX Spectra. Analysis of Valley Networks on Valles Marineris Plateau Using HRSC/MEX Data. Solar Abundance of Elements from Neutron-Capture Cross Sections. Preliminary Evaluation of the Secondary Ion/Accelerator Mass Spectrometer, MegaSIMS. Equilibrium Landforms in the Dry Valleys of Antarctica: Implications for Landscape Evolution and Climate Change on Mars. Continued Study of Ba Isotopic Compositions of Presolar Silicon Carbide Grains from Supernovae. Paleoenviromental Evolution of the Holden-Uzboi Area. Stability of Magnesium Sulfate Minerals in Martian Environments. Tungsten Isotopic Constraints on the Formation and Evolution of Iron Meteorite Parent Bodies. Migration of Dust Particles and Volatiles Delivery to the Inner Planets. On the Sitting of Trapped Noble Gases in Insoluble Organic Matter of Primitive Meteorites. Trapping of Xenon Upon Evaporation-Condensation of Organic Matter Under UV Irradiation: Isotopic Fractionation and Electron Paramagnetic Resonance Analysis. Stability of Water on Mars. A Didactic Activity. Analysis of Coronae in the Parga Chasma Region, Venus. Photometric and Compositional Surface Properties of the Gusev Crater Region, Mars, as Derived from Multi-Angle, Multi-Spectral Investigation of Mars Express HRSC Data. Mapping Compositional Diversity on Mars: Spatial Distribution and Geological Implications. A New Simulation Chamber for Studying Planetary Environments. Folded Structure in Terra Sirenum. Mars. Nitrogen-Noble Gas Static Mass Spectrometry of Genesis Collector Materials. Neon Isotope Heterogeneity in the Terrestrial Mantle: Implication for the Acquisition of Volatile Elements in Terrestrial Planets. The Cosmic Clock, the Cycle of Terrestrial Mass Extinctions.

Source record↗
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↗
DOE OSTI2026

Self-supervised and multi-fidelity learning for extended predictive soil spectroscopy

Infrared spectroscopy is a cost-effective, non-destructive, and environmentally benign technology that is increasingly recognized as an important solution for meeting the global demand for soil data. While both near-infrared (NIR) and mid-infrared (MIR) diffuse reflectance spectroscopy enable rapid estimation of soil properties, they present a significant trade-off: NIR offers superior scalability and lower operational costs, whereas MIR provides higher analytical fidelity by capturing fundamental molecular vibrations. In this study, we propose a self-supervised, multi-fidelity learning framework designed to bridge this gap. Our approach leverages large-scale MIR spectral libraries to learn a compact, transferable latent representation, into which NIR spectra are subsequently aligned for downstream prediction. The workflow consists of pretraining a latent model on a large MIR library, adapting the representation using a smaller paired NIR–MIR dataset, and evaluating generalization on an independent external test set. Across a range of chemical and physical soil properties, we found that MIR-derived embeddings improved prediction accuracy relative to baseline models that used raw MIR inputs. Predictions derived from the spectrum conversion (NIR to MIR) task did not match the performance of the original MIR spectra but were similar or superior to predictive performance of NIR-only models, suggesting the unified spectral latent space can effectively leverage the larger and more diverse MIR dataset for prediction of soil properties not well represented in current NIR libraries.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Characterizing leaf-scale fluorescence with spectral invariants

Sun-induced chlorophyll fluorescence (SIF) is increasingly recognized as a non-destructive probe for tracking terrestrial photosynthesis. Emerging developments in spectral invariants theory provide an innovative and efficient approach for representing SIF radiative transfer processes at the canopy scale. However, modeling leaf-scale fluorescence based on the spectral invariants properties (SIP) remains underexplored. In this study, the spectral invariants theory is employed for the first time to model the leaf-scale total, backward and forward fluorescence (leaf-SIP SIF). The leaf-SIP SIF model separates the leaf-scale radiative transfer process into two distinct components: the wavelength-dependent one associated with leaf biochemical properties, and the wavelength-independent component linked to leaf structural characteristics. The leaf structure-related effects are characterized by two spectrally invariant parameters: the photon recollision probability (p) and the scattering asymmetry parameter (q), which are parameterized using the directly measurable leaf dry matter. Evaluation against field measurements shows that the proposed leaf-SIP SIF model has a good performance, with coefficient of determination (R 2 ) of 0.89, 0.89, 0.90 and root mean squared errors (RMSE) of 1.28, 0.69, 0.74 Wm -2 µm -1 sr -1 , respectively for the total, backward, and forward fluorescence (660–800 nm). The leaf-SIP SIF model with a more concise formulation demonstrates comparable performance with the widely used Fluspect model. Further, the leaf-SIP SIF model provides a simple and efficient approach for simulating leaf-scale fluorescence, with the potential to be integrated into a unified SIP-based model framework for simulating the radiative transfer processes across the soil-leaf-canopy-atmosphere continuum.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2010

NASA MUST Paper: Infrared Thermography of Graphite/Epoxy

The focus of this project is to use Infrared Thermography, a non-destructive test, to detect detrimental cracks and voids beneath the surface of materials used in the space program. This project will consist of developing a simulation model of the Infrared Thermography inspection of the Graphite/Epoxy specimen. The simulation entails finding the correct physical properties for this specimen as well as programming the model for thick voids or flat bottom holes. After the simulation is completed, an Infrared Thermography inspection of the actual specimen will be made. Upon acquiring the experimental test data, an analysis of the data for the actual experiment will occur, which includes analyzing images, graphical analysis, and analyzing numerical data received from the infrared camera. The simulation will then be corrected for any discrepancies between it and the actual experiment. The optimized simulation material property inputs can then be used for new simulation for thin voids. The comparison of the two simulations, the simulation for the thick void and the simulation for the thin void, provides a correlation between the peak contrast ratio and peak time ratio. This correlation is used in the evaluation of flash thermography data during the evaluation of delaminations.

Comeaux, Kayla↗
NASA NTRS1990

Use of high-dimensional spectral data to evaluate organic matter, reflectance relationships in soils

Recent breakthroughs in remote sensing technology have led to the development of a spaceborne high spectral resolution imaging sensor, HIRIS, to be launched in the mid-1990s for observation of earth surface features. The effects of organic carbon content on soil reflectance over the spectral range of HIRIS, and to examine the contributions of humic and fulvic acid fractions to soil reflectance was evaluated. Organic matter from four Indiana agricultural soils was extracted, fractionated, and purified, and six individual components of each soil were isolated and prepared for spectral analysis. The four soils, ranging in organic carbon content from 0.99 percent, represented various combinations of genetic parameters such as parent material, age, drainage, and native vegetation. An experimental procedure was developed to measure reflectance of very small soil and organic component samples in the laboratory, simulating the spectral coverage and resolution of the HIRIS sensor. Reflectance in 210 narrow (10 nm) bands was measured using the CARY 17D spectrophotometer over the 400 to 2500 nm wavelength range. Reflectance data were analyzed statistically to determine the regions of the reflective spectrum which provided useful information about soil organic matter content and composition. Wavebands providing significant information about soil organic carbon content were located in all three major regions of the reflective spectrum: visible, near infrared, and middle infrared. The purified humic acid fractions of the four soils were separable in six bands in the 1600 to 2400 nm range, suggesting that longwave middle infrared reflectance may be useful as a non-destructive laboratory technique for humic acid characterization.

Henderson, T. L.↗
NASA NTRS2010

Measurement of Insulation Compaction in the Cryogenic Fuel Tanks at Kennedy Space Center by Fast/Thermal Neutron Techniques

The liquid hydrogen and oxygen cryogenic storage tanks at John F. Kennedy Space Center (KSC) use expanded perlite as thermal insulation. Th ere is evidence that some of the perlite has compacted over time, com promising the thermal performance and possibly also structural integr ity of the tanks. Therefore an Non-destructive Testing (NDT) method for measuring the perlite density or void fraction is urgently needed. Methods based on neutrons are good candidates because they can readil y penetrate through the 1.75 cm outer steel shell and through the ent ire 120 cm thickness of the perlite zone. Neutrons interact with the nuclei of materials to produce characteristic gamma rays which are the n detected. The gamma ray signal strength is proportional to the atom ic number density. Consequently, if the perlite is compacted then the count rates in the individual peaks in the gamma ray spectrum will i ncrease. Perlite is a feldspathic volcanic rock made up of the major elements Si, AI, Na, K and 0 along with some water. With commercially available portable neutron generators it is possible to produce simul taneously fluxes of neutrons in two energy ranges: fast (14 MeV) and thermal (25 meV). Fast neutrons produce gamma rays by inelastic scatt ering which is sensitive to Fe and O. Thermal neutrons produce gamma rays by radiative capture in prompt gamma neutron activation (PGNA) and this is sensitive to Si, AI, Na, Kand H. Thus the two energy ranges produce complementary information. The R&D program has three phases: numerical simulations of neutron and gamma ray transport with MCNP s oftware, evaluation of the system in the laboratory on test articles and finally mapping of the perlite density in the cryogenic tanks at KSC. The preliminary MCNP calculations have shown that the fast/therma l neutron NDT method is capable of distinguishing between expanded an d compacted perlite with excellent statistics.

Livingston, R. A.↗
DOE OSTI2026

A Bayesian inferencing framework for ultrasound wave speed measurements in metal additive manufacturing

Process-related changes during metal additive manufacturing introduce microstructural variability in the material properties of printed parts, directly affecting component reliability. Accurate estimation of these property variations with part performance are essential for quality assurance. Ultrasound testing offers a non-destructive means to estimate mechanical properties and detect defects; however, conventional analysis methods often neglect the influence of microstructural variability, limiting their effectiveness. Here, this research presents a Bayesian inference technique for quantifying wave speed uncertainty from ultrasound measurements of metal additive manufactured parts. By integrating prior ultrasound data with a Bayesian model, the proposed approach generates posterior density estimates of wave speed that systematically account for manufacturing-induced variability and uncertainty. The novelty of this research lies in applying a Bayesian framework to analyze experimental ultrasound measurements within the context of metal additive manufacturing variability. The method enhances the accuracy of wave speed estimation by 64%, defect position by 50% and increases confidence associated with wave speed variance by 30% across different porosity levels, thereby providing a robust foundation for improved decision-making and increased reliability in additively manufactured components.

Additive manufacturing↗
DOE OSTI2025

Variance Preserving Spectral Subsampling

Generating statistically faithful short-duration gamma-ray spectra from a single long measurement is essential in nuclear safeguards, supporting tasks such as algorithm development and machine-learning applications, especially when list-mode data are unavailable. Existing subsampling methods often distort the statistical characteristics of genuine short-duration measurements, leading to biased or unreliable analytical outcomes and thereby undermining downstream tasks. In this work, we compare five subsampling approaches using a benchmark set of 156 genuine replicate spectra collected with a high-purity germanium detector. We evaluate each method with respect to run-to-run variance, channel-to-channel variance, and preservation of total counts (losslessness). Across a wide range of subsampling ratios, only binomial subsampling without replacement consistently reproduces the statistical properties of genuine short-duration spectra, maintaining proper dispersion even in sparse spectral regions and perfectly preserving total counts. These results provide a mathematically principled and practically validated framework for generating synthetically shortened spectra when true short-duration measurements are unavailable.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
NASA NTRS1991

Quantitative nondestructive evaluation of materials and structures

An experimental investigation was undertaken to quantify damage tolerance and resistance in composite materials impacted using the drop-weight method. Tests were conducted on laminates of several different carbon-fiber composite systems, such as epoxies, modified epoxies, and amorphous and semicrystalline thermoplastics. Impacted composite specimens were examined using destructive and non-destructive techniques to establish the characteristic damage states. Specifically, optical microscopy, ultrasonic, and scanning electron microscopy techniques were used to identify impact induced damage mechanisms. Damage propagation during post impact compression was also studied.

Smith, Barry T.↗
NASA NTRS1994

Root growth and development in response to CO2 enrichment

A non-destructive technique (minirhizotron observation tubes) was used to assess the effects of CO2 enrichment on root growth and development in experimental plots in a scrub oak-palmetto community at the Kennedy Space Center. Potential effects of CO2 enrichment on plants have a global significance in light of concerns over increasing CO2 concentrations in the Earth's atmosphere. The study at Kennedy Space Center focused on aboveground physiological responses (photosynthetic efficiency and water use efficiency), effects on process rates (litter decomposition and nutrient turnover), and belowground responses of the plants. Belowground dynamics are an exceptionally important component of total plant response but are frequently ignored due to methodological difficulties. Most methods used to examine root growth and development are destructive and, therefore, severely compromise results. Minirhizotrons allow nondestructive observation and quantification of the same soil volume and roots through time. Root length density and root phenology were evaluated for CO2 effects with this nondestructive technique.

Day, Frank P., Jr.↗