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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Advanced Laboratory and Field Arrays: Evaluating Sampling Techniques for MHK Biological Monitoring (Task 6)

The overall goal of the task was to identify cost effective biological sampling techniques for MHK environmental monitoring. Protected, demersal, and pelagic fish and selected nektonic invertebrates were surveyed using capture and remote sensing techniques at the PacWave sites. The performance of capture and remote sensing monitoring techniques were evaluated and generic nekton monitoring indices were developed for MHK technologies and sites. In parallel to data collections at the PacWave site, the ability of regression models to characterize, detect, and predict change in acoustic data was evaluated using acoustic data collected in Admiralty Inlet, WA, during a biological monitoring study of the proposed SnoPud tidal turbine project site. Expected outcomes of these efforts included an evaluation of instrumentation and techniques used to monitor biological variability; identification of data streams that can be used to detect and quantify change; and sampling requirements to ensure detection of change in monitored variables.

13 HYDRO ENERGY↗
DOE OSTI2021

Iterative self-organizing SCEne-LEvel sampling (ISOSCELES) for large-scale building extraction

Convolutional neural networks (CNN) provide state-of-the-art performance in many computer vision tasks, including those related to remote-sensing image analysis. Successfully training a CNN to generalize well to unseen data, however, requires training on samples that represent the full distribution of variation of both the target classes and their surrounding contexts. With remote sensing data, acquiring a sufficiently representative training set is a challenge due to both the inherent multi-modal variability of satellite or aerial imagery and the general high cost of labeling data. To address this challenge, we have developed ISOSCELES, an Iterative Self-Organizing SCEne LEvel Sampling method for hierarchical sampling of large image sets. Using affinity propagation, ISOSCELES automates the selection of highly representative training images. Compared to random sampling or using available reference data, the distribution of the training is principally data driven, reducing the chance of oversampling uninformative areas or undersampling informative ones. In comparison to manual sample selection by an analyst, ISOSCELES exploits descriptive features, spectral and/or textural, and eliminates human bias in sample selection. Using a hierarchical sampling approach, ISOSCELES can obtain a training set that reflects both between-scene variability, such as in viewing angle and time of day, and within-scene variability at the level of individual training samples. We verify the method by demonstrating its superiority to stratified random sampling in the challenging task of adapting a pre-trained model to a new image and spatial domain for country-scale building extraction. Using a pair of hand-labeled training sets comprising 1,987 sample image chips, a total of 496,000,000 individually labeled pixels, we show, across three distinct model architectures, an increase in accuracy, as measured by F1-score, of 2.2–4.2%.

42 ENGINEERING↗
DOE OSTI2026

Automation of Laser Plasma Focused Ion Beam Microscopy for Next-Gen Energy Materials

Automation can revolutionize the use of ultrafast laser ablation and plasma-focused ion beam (PFIB) techniques for high-throughput, reproducible cross-sectioning and various sample preparation in materials characterization. As these methods become essential for analyzing complex energy materials and next-generation devices, efficient, standardized workflows are needed to minimize variability and enhance precision. This work highlights our advancements in developing automated processes for sample preparation that integrates machine learning, workflow optimization, and large-scale data acquisition to improve efficiency and scalability in applications such as electrolyzers, photovoltaic cells, and microelectronics. To streamline cross-sectioning and lamella fabrication, we have implemented fully automated workflows that standardize laser ablation and PFIB milling sequences. These workflows incorporate pre-programmed protocols for material removal, alignment, and thinning, reducing user intervention and ensuring consistency across different sample types. Machine learning algorithms further enhance automation by predicting optimal milling strategies and adapting parameters based on material properties and sectioning requirements. This approach significantly improves throughput while maintaining the structural integrity of prepared samples for high-resolution imaging and analysis, including transmission electron microscopy. Beyond sample preparation, our automation platform enables the acquisition of large, high-resolution datasets through serial sectioning, image alignment, and 3D reconstruction. These automated routines facilitate multi-scale characterization, capturing structural and compositional details from the nanoscale to the device level. By reducing variability and increasing efficiency, our automated approach enhances defect analysis, failure diagnostics, and process optimization, accelerating advancements in materials research and device engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Quasar classification using color and variability

We conduct a pilot investigation to determine the optimal combination of color and variability information to identify quasars in current and future multi-epoch optical surveys. We use a Bayesian quasar selection algorithm to identify 35,820 type 1 quasar candidates in a 239 deg{sup 2} field of the Sloan Digital Sky Survey (SDSS) Stripe 82, using a combination of optical photometry and variability. Color analysis is performed on 5-band single- and multi-epoch SDSS optical photometry to a depth of r∼22.4. From these data, variability parameters are calculated by fitting the structure function of each object in each band with a power-law model using 10 to >100 observations over timescales from ∼1 day to ∼8 years. Selection was based on a training sample of 13,221 spectroscopically confirmed type-1 quasars, largely from the SDSS. Using variability alone, colors alone, and combining variability and colors we achieve 91%, 93%, and 97% quasar completeness and 98%, 98%, and 97% efficiency, respectively, with particular improvement in the selection of quasars at 2.7<z<3.5 where quasars and stars have similar optical colors. The 22,867 quasar candidates that are not spectroscopically confirmed reach a depth of i∼22.0; 21,876 (95.7%) are dimmer than coadded i-band magnitude of 19.9, the cutoff for spectroscopic follow-up for SDSS on Stripe 82. Brighter than 19.9, we find 5.7% more quasar candidates without confirming spectra in sky regions otherwise considered complete. The resulting quasar sample has sufficient purity (and statistically correctable incompleteness) to produce a luminosity function comparable to those determined by spectroscopic investigations. We discuss improvements that can be made to the process in preparation for performing similar photometric selection and science on data from post-SDSS sky surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1981

Sampling problems

Precipitation estimates from satellites are subject to a number of uncertainties involving design characteristics, satellite positioning, natural variability of precipitation, and the noncontinuous acquisition of data. The sources and sizes of these uncertainties are in need of proper evaluation and estimation. The present sampling and estima-theory seems to be adequate for some measurement problems (e.g., determining precipitation at a point), while others require further theoretical work (e.g., determining the time history of precipitation over large areas).

Flueck, J. A.↗
DOE OSTI2017

Mapping snow depth within a tundra ecosystem using multiscale observations and Bayesian methods

Abstract. This paper compares and integrates different strategies to characterize the variability of end-of-winter snow depth and its relationship to topography in ice-wedge polygon tundra of Arctic Alaska. Snow depth was measured using in situ snow depth probes and estimated using ground-penetrating radar (GPR) surveys and the photogrammetric detection and ranging (phodar) technique with an unmanned aerial system (UAS). We found that GPR data provided high-precision estimates of snow depth (RMSE = 2.9 cm), with a spatial sampling of 10 cm along transects. Phodar-based approaches provided snow depth estimates in a less laborious manner compared to GPR and probing, while yielding a high precision (RMSE = 6.0 cm) and a fine spatial sampling (4 cm × 4 cm). We then investigated the spatial variability of snow depth and its correlation to micro- and macrotopography using the snow-free lidar digital elevation map (DEM) and the wavelet approach. We found that the end-of-winter snow depth was highly variable over short (several meter) distances, and the variability was correlated with microtopography. Microtopographic lows (i.e., troughs and centers of low-centered polygons) were filled in with snow, which resulted in a smooth and even snow surface following macrotopography. We developed and implemented a Bayesian approach to integrate the snow-free lidar DEM and multiscale measurements (probe and GPR) as well as the topographic correlation for estimating snow depth over the landscape. Our approach led to high-precision estimates of snow depth (RMSE = 6.0 cm), at 0.5 m resolution and over the lidar domain (750 m × 700 m).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1975

Solid-propellant rocket motor ballistic performance variation analyses

Results are presented of research aimed at improving the assessment of off-nominal internal ballistic performance including tailoff and thrust imbalance of two large solid-rocket motors (SRMs) firing in parallel. Previous analyses using the Monte Carlo technique were refined to permit evaluation of the effects of radial and circumferential propellant temperature gradients. Sample evaluations of the effect of the temperature gradients are presented. A separate theoretical investigation of the effect of strain rate on the burning rate of propellant indicates that the thermoelastic coupling may cause substantial variations in burning rate during highly transient operating conditions. The Monte Carlo approach was also modified to permit the effects on performance of variation in the characteristics between lots of propellants and other materials to be evaluated. This permits the variabilities for the total SRM population to be determined. A sample case shows, however, that the effect of these between-lot variations on thrust imbalances within pairs of SRMs is minor in compariosn to the effect of the within-lot variations. The revised Monte Carlo and design analysis computer programs along with instructions including format requirements for preparation of input data and illustrative examples are presented.

Sforzini, R. H.↗
NASA NTRS2017

Pulsed-Laser Irradiation Space Weathering Of A Carbonaceous Chondrite

Grains on the surfaces of airless bodies experience irradiation from solar energetic particles and melting, vaporization and recondensation processes associated with micrometeorite impacts. Collectively, these processes are known as space weathering and they affect the spectral properties, composition, and microstructure of material on the surfaces of airless bodies, e.g. Recent efforts have focused on space weathering of carbonaceous materials which will be critical for interpreting results from the OSIRIS-REx and Hayabusa2 missions targeting primitive, organic-rich asteroids. In addition to returned sample analyses, space weathering processes are quantified through laboratory experiments. For example, the short-duration thermal pulse from hypervelocity micrometeorite impacts have been simulated using pulsed-laser irradiation of target material e.g. Recent work however, has shown that pulsed-laser irradiation has variable effects on the spectral properties and microstructure of carbonaceous chondrite samples. Here we investigate the spectral characteristics of pulsed-laser irradiated CM2 carbonaceous chondrite, Murchison, including the vaporized component. We also report the chemical and structural characteristics of specific mineral phases within the meteorite as a result of pulsed-laser irradiation.

Thompson, M. S.↗
DOE OSTI2015

Control of the external photoluminescent quantum yield of emitters coupled to nanoantenna phased arrays

Optical losses in metals represent the largest limitation to the external quantum yield of emitters coupled to plasmonic antennas. These losses can be at the emission wavelength, but they can be more important at shorter wavelengths, i.e., at the excitation wavelength of the emitters, where the conductivity of metals is usually lower. We present accurate measurements of the absolute external photoluminescent quantum yield of a thin layer of emitting material deposited over a periodic nanoantenna phased array. Emission and absorptance measurements of the sample are performed using a custom-made setup including an integrating sphere and variable angle excitation. The measurements reveal a strong dependence of the external quantum yield on the angle at which the optical field excites the sample. Such behavior is attributed to the coupling between far-field illumination and near-field excitation mediated by the collective resonances supported by the array. Numerical simulations confirm that the inherent losses associated with the metal can be greatly reduced by selecting an optimum angle of illumination, which boosts the light conversion efficiency in the emitting layer. This combined experimental and numerical characterization of the emission from plasmonic arrays reveals the need to carefully design the illumination to achieve the maximum external quantum yield.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1983

Interannual variability and predictability of 500 mb geopotential heights over the Northern Hemisphere

The interannual variability of monthly mean 500 mb heights in a 15-year sample of observed data is compared to the variance expected from sampling errors associated with high-frequency fluctuations using the analysis of variance approach. The monthly mean 'signal' stands out significantly from the 'noise' over a substantial fraction of the Northern Hemisphere during the winter. The expected spectrum of variance at very low frequencies is assumed to be white at frequencies lower than per (30 days) rather than the per (96 days) cutoff used by Madden. This difference is justified by observing that the effective time between independent samples T(0) is relatively insensitive to changes in the maximum lag over which the local autocorrelation is integrated to calculate T(0). Further non-randomness in the variance of 500 mb heights is evidenced by the correlation between monthly mean height and contemporaneous daily variability.

Shukla, J.↗
DOE OSTI2018

Oxaliplatin and irinotecan induce heterogenous changes in the EMT markers of metastasizing colorectal carcinoma cells

Highlights: • Significant variability and lower expression uniformity in lymph node metastatic cells. • Heterogeneity of cell response partially determined by cancer cell microenvironment. • Metastatic cells proved to be less sensitive to chemotherapy treatment compared to primary site cancer cells. • Irinotecan and oxaliplatin affected EMT markers in primary cell lines. In patients with advanced colorectal cancer (CRC), surgery is complemented with systemic therapy – chemotherapy and radiochemotherapy. Although the patients’ overall survival has been significantly improved, tumor resistance is still a frequent cause of chemotherapy failure. Several factors contribute to chemoresistance of tumor cells including changes related with epithelial-mesenchymal transition (EMT). The present study was designed to verify the presence of EMT markers in paired CRC primary cell lines obtained from primary tumor sites and lymph node metastases of three patients and to investigate the effect of irinotecan and oxaliplatin treatment on these markers as well. The samples of the higher stage of CRC and positive for angioinvasion were selected and qPCR, western blot analysis, migration assay, cytotoxicity testing was performed. Results confirmed the increased expression of several markers characteristic of EMT and invasiveness in lymph node metastatic cells, with a significant variability between individual samples. Irinotecan and oxaliplatin decreased migration activity of the cells and to the varying degree affected the expression of EMT and invasiveness markers. In conclusion, in CRC EMT is present in metastatic cells over a phenotypic continuum whose expression is altered heterogeneously upon irinotecan and oxaliplatin treatment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Imprecise global sensitivity analysis using bayesian multimodel inference and importance sampling

Global Sensitivity Analysis (GSA) aims to understand the relative importance of uncertain input variables to model response. Conventional GSA involves calculating sensitivity (Sobol’) indices for a model with known model parameter distributions. However, model parameters are affected by aleatory and epistemic uncertainty, with the latter often caused by lack of data. In this paper, we propose a new framework to quantify uncertainty in probability model-form and model parameters resulting from small datasets and integrate these uncertainties into Sobol’ index estimates. First, the process establishes, through Bayesian multimodel inference, a set of candidate probability models and their associated probabilities. Imprecise Sobol’ indices are calculated from these probability models using an importance sampling reweighting approach. This results in probabilistic Sobol’ indices, whose distribution characterizes uncertainty in the sensitivity resulting from small dataset size. The imprecise Sobol’ indices thus provide a measure of confidence in the sensitivity estimate and, moreover, can be used to inform data collection efforts targeted to minimize the impact of uncertainties. Through an example studying the parameters of a Timoshenko beam, we show that these probabilistic Sobol’ indices converge to the true/deterministic Sobol’ indices as the dataset size increases and hence, distribution-form uncertainty reduces. The approach is then applied to assess the sensitivity of the out-of-plane properties of an E-glass fiber composite material to its constituent properties. This second example illustrates the approach for an important class of materials with wide-ranging applications when data may be lacking for some input parameters.

42 ENGINEERING↗
DOE OSTI2016

Alpha1 LASSO data bundles Lamont, OK

A data bundle is a unified package consisting of LASSO LES input and output, observations, evaluation diagnostics, and model skill scores. LES input includes model configuration information and forcing data. LES output includes profile statistics and full domain fields of cloud and environmental variables. Model evaluation data consists of LES output and ARM observations co-registered on the same grid and sampling frequency. Model performance is quantified by skill scores and diagnostics in terms of cloud and environmental variables.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

LASSO Data Bundles

The Alpha 2 release is the second release from the LASSO Pilot Phase that builds upon the Alpha 1 release. Alpha 2 contains additional diagnostics in the data bundles and focuses on cases from spring-summer 2016. A data bundle is a unified package consisting of LASSO LES input and output, observations, evaluation diagnostics, and model skill scores. LES input include model configuration information and forcing data. LES output includes profile statistics and full domain fields of cloud and environmental variables. Model evaluation data consists of LES output and ARM observations co-registered on the same grid and sampling frequency. Model performance is quantified by skill scores and diagnostics in terms of cloud and environmental variables.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Empirically assessing the potential release of rare earth elements from black shale under simulated hydraulic fracturing conditions

Rare earth elements (REEs) are economically important to modern society and the rapid growth of technologies dependent on REEs has placed considerable economic pressure on their sourcing. This study addresses whether REEs could be released as a byproduct of natural gas extraction from a series of experiments that were designed to simulate hydraulic fracturing of black shale under various pressure (25 and 27.5 MPa) and temperature (50, 90, 130 °C) conditions. The dissolved REEs in the reacted fluids displayed no propensity for the REEs to be released from black shale under high pressure and temperature conditions, a result that is consistent across the different types of fluids investigated. Overall, there was a net loss of REEs from the fluid. These changes in dissolved REEs were greatest at the moment the fluids first contacted the shale and before the high temperature and high pressure conditions were imposed, although the magnitude of these changes (10 -4 μg/g) were small compared to the magnitude of the total REE content present in the solid shale samples (10 2 μg/g). These results highlight the variability and complexity of hydraulic fracturing systems and indicate that REE may not serve as robust tracers for fracturing fluid-shale reactions. Additionally, the results suggest that significant quantities of REEs may not be byproducts of hydraulically fractured shales.

03 NATURAL GAS↗
DOE OSTI2015

Study of interface correlation in W/C multilayer structure by specular and non-specular grazing incidence X-ray reflectivity measurements

W/C/W tri-layer thin film samples have been deposited on c-Si substrates in a home-built Ion Beam Sputtering system at 1.5 × 10{sup −3} Torr Ar working pressure and 10 mA grid current. The tri-layer samples have been deposited at different Ar{sup +} ion energies between 0.6 and 1.2 keV for W layer deposition and the samples have been characterized by specular and non-specular grazing incidence X-ray reflectivity (GIXR) measurements. By analyzing the GIXR spectra, various interface parameters have been obtained for both W-on-C and C-on-W interfaces and optimum Ar{sup +} ion energy for obtaining interfaces with low imperfections has been found. Subsequently, multilayer W/C samples with 5-layer, 7-layer, 9-layer, and 13-layer have been deposited at this optimum Ar{sup +} ion energy. By fitting the specular and diffused GIXR data of the multilayer samples with the parameters of each interface as fitting variables, different interface parameters, viz., interface width, in-plane correlation length, interface roughness, and interface diffusion have been estimated for each interface and their variation across the depth of the multilayers have been obtained. The information would be useful in realizing W/C multilayers for soft X-ray mirror application in the <100 Å wavelength regime. The applicability of the “restart of the growth at the interface” model in the case of these ion beam sputter deposited W/C multilayers has also been investigated in the course of this study.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Phase transformations in oxides above 2000°C: experimental technique development

Here, the oxidation of boride and carbide-based ultra-high-temperature ceramics is the primary limiting factor for their use as aerodynamic surfaces. Understanding the behaviour of the oxides that can result from oxidation of metal borides and carbides at very high temperatures is essential to optimise and tailor the performance of these materials; yet experimental thermodynamic and structural data for refractory oxides above 2000°C are mostly absent. The following techniques that can be applied to fill this gap are discussed: (i) commercial ultra-high-temperature differential thermal analysis for investigation of phase transformations and melting in inert environments to 2500°C, (ii) a combination of laser heating with a splittable nozzle aerodynamic levitator for splat quenching and drop calorimetry from temperatures limited only by sample evaporation, (iii) synchrotron X-ray and neutron diffraction on laser-heated aerodynamically levitated oxide samples for in situ observation of phase transformations in variable atmospheres, refinement of high-temperature structures and thermal expansion. Recent experimental findings include anomalous thermal expansion of the defect fluorite phase of YSZ, thermodynamics of pyrochlore–fluorite transformation from high-temperature structure refinements, and measurement of thermal expansion to the melting temperatures and fusion enthalpies of Zr, Hf, La, Yb and Lu oxides. These methods provide temperatures, enthalpies and volume change for phase transformations above 2000°C, which are required for thermodynamic assessments and calculation of phase diagrams of multicomponent systems.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Deciphering the 3D structure of the old galactic bulge from the OGLE RR Lyrae stars

We have analyzed a sample of 27,258 fundamental-mode RR Lyrae variable stars (type RRab) detected recently toward the Galactic bulge by the Optical Gravitational Lensing Experiment (OGLE) survey. The data support our earlier claim that these metal-poor stars trace closely the barred structure formed of intermediate-age red clump giants. The distance to the Galactic center (GC) inferred from the bulge RR Lyrae stars is R{sub 0}=8.27±0.01(stat)±0.40(sys) kpc. We show that their spatial distribution has the shape of a triaxial ellipsoid with a major axis located in the Galactic plane and inclined at an angle of i=20{sup ∘}±3{sup ∘} to the Sun–GC line of sight. The obtained scale-length ratio of the major axis to the minor axis in the Galactic plane and to the axis vertical to the plane is 1:0.49(2):0.39(2). We do not see evidence for the bulge RR Lyrae stars forming an X-shaped structure. Based on the light curve parameters, we derive metallicities of the RRab variables and show that there is a very mild but statistically significant radial metallicity gradient. About 60% of the bulge RRab stars form two very close sequences on the period–amplitude (or Bailey) diagram, which we interpret as two major old bulge populations: A and B. Their metallicities likely differ. Population A is about four times less abundant than the slightly more metal-poor population B. Most of the remaining stars seem to represent other, even more metal-poor populations of the bulge. The presence of multiple old populations indicates that the Milky Way bulge was initially formed through mergers.

79 ASTRONOMY AND ASTROPHYSICS↗