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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
NASA NTRS1974

Radiative property investigation

A detailed formulation of radiative heat transfer problems involving the use of bidirectional reflectance is discussed. Except for very simple systems this formulation is very intricate. For this reason and the fact that bidirectional data are scarce, such a formulation is not in common use. However, with the development of the digital computer there have been numerical methods developed for detailed radiative investigations using the bidirectional reflectance. Since computations using bidirectional reflectance are coming into use for spacecraft radiative studies, it is necessary to have reflectance data on the materials involved. Materials that are frequently studied are coatings which are used in controlling the thermal environment of spacecrafts. This study is primarily concerned with the bidirectional reflectance of zinc oxide which is one constituent commonly used for coatings.

Scott, R. L., Jr.↗
NASA NTRS1992

Retrieval of biophysical parameters with AVIRIS and ISM: The Landes Forest, south west France

The first steps of an experiment for investigating the capability of airborne spectrometer data for retrieval of biophysical parameters of vegetation, especially water conditions are presented. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and ISM data were acquired in the frame of the 1991 NASA/JPL and CNES campaigns on the Landes, South west France, a large and flat forest area with mainly maritime pines. In-situ measurements were completed at that time; i.e. reflectance spectra, atmospheric profiles, sampling for further laboratory analyses of elements concentrations (lignin, water, cellulose, nitrogen,...). All information was integrated in an already existing data base (age, LAI, DBH, understory cover,...). A methodology was designed for (1) obtaining geometrically and atmospherically corrected reflectance data, (2) registering all available information, and (3) analyzing these multi-source informations. Our objective is to conduct comparative studies with simulation reflectance models, and to improve these models, especially in the MIR.

Zagolski, F.↗
NASA NTRS1998

Wheel Abrasion Experiment Conducted on Mars

Sojourner rover showing Lewis' wheel abrasion experiment. The Mars Pathfinder spacecraft soft-landed on Mars on July 4, 1997. Among the many experiments on its small Sojourner rover are three technology experiments from the NASA Lewis Research Center, including the Wheel Abrasion Experiment (WAE). The WAE was designed, built, delivered, and operated on Mars by a team of engineers and scientists from Lewis' Photovoltaics and Space Environments Branch. This experiment collected data to assess wheel surface wear on the Sojourner. It used a specially designed rover wheel, with thin films (200 to 1000 angstroms) of aluminum, nickel, and platinum deposited on black, anodized aluminum strips attached to the rover's right center wheel. As the wheel spun in the Martian soil, a photovoltaic sensor monitored changes in film reflectivity. These changes indicated abrasion of the metal films by Martian surface material. Rolling wear data were accumulated by the WAE. Also, at frequent intervals, all the rover wheels, except the WAE test wheel, were locked to hold the rover stationary while the test wheel alone was spun and dug into the Martian regolith. These tests created wear conditions more severe than simple rolling. The WAE will contribute substantially to our knowledge of Martian surface characteristics. Marked abrasion would indicate a surface composed of hard, possibly sharply edged grains, whereas lack of abrasion would suggest a somewhat softer surface. WAE results will be correlated with ground simulations to determine which terrestrial materials behave most like those on Mars. This knowledge will enable a deeper understanding of erosion processes on Mars and the role they play in Martian surface evolution. Preliminary results show that electrostatic charging of the rover wheels sometimes caused dust to accumulate on the WAE wheel, making interpretation of the reflectance data problematic. If electrostatic charging is the mechanism for dust attraction, this indicates that the Martian dust has a size somewhat smaller than 40 microns in diameter. The WAE experiment has detected electrostatic charging in the Martian environment for the first time; however, under conditions when the wheel is relatively clean of Martian dust, flight data now indicate that abrasion has also been detected. Crude limits so far place the hardness of the Martian dust at harder than aluminum but softer than nickel, and place the grain size at somewhat smaller than 40 microns.

Ferguson, Dale C.↗
DOE OSTI2019

New hints on Maya Blue formation process by PCA-assisted in situ XRPD/PDF and optical spectroscopy

The exact recipe to prepare the ancient Maya Blue (MB), an incredibly resistant and brilliant pigment prepared from indigo (dye) and Paligorskite (clay), is lost to the ages. To unravel the key features of the MB formation process, several inorganic-dye couples were heated to 200°C and cooled to RT, to investigate their reactivity and the diffusion and degree of sequestration of the dye into the inorganic host. In situ XRPD/PDF and fiber optic reflectance spectroscopy (FORS) data, sided by TGA, provided a comprehensive overview on MB formation mechanism. XRPD/PDF gave information on long/short range behaviors of water desorption/adsorption and indigo sequestration, while TGA and in situ FORS gave information on mass and optical changes within temperature. Ex situ dye removal was used to understand the sample stability after the thermal treatments. A statistical approach based on Principal Component Analysis was exploited to efficiently and jointly analyze the ~3000 collected patterns. MB formation starts below 110°C with disordered distribution of indigo within the channels, reaching maximum reaction speed and higher ordering at 150°C. Above 175°C, color changes and a stronger sequestration of indigo into framework channels are observed, while the affinity for water is dramatically reduced. The origin of different colors, hues and stability in historical MB samples can then explained in term of different thermal history of the starting mechanical indigo-palygorskite mixture.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A Data-Driven Method for Modeling Creep-Fatigue Stress- Strain Behavior Using Neural ODEs

In this paper, we introduce a data-driven machine learning approach for modeling one-dimensional stress–strain behavior under cyclic loading, utilizing experimental data from the nickel-based Alloy 617. The study employs uniaxial creep–fatigue test data acquired under various loading histories and compares two distinct neural network-based ODE models. The first model, known as the black-box model, comprehensively describes the strain–stress relationship using a Neural ODE equation. To interpret this black-box model, we apply the Sparse Identification of Nonlinear Dynamical Systems (SINDy) technique, transforming the black-box model into an equation-based model using symbolic regression. The second model, the Neural flow rule model, incorporates Hooke’s Law for the linear elastic component, with the nonlinear part characterized by a Neural ODE. Both models are trained with experimental data to accurately reflect the observed stress–strain behavior. We conduct a detailed comparison with the standard Chaboche model, which includes three back stresses. Our results demonstrate that the neural network-based ODE models precisely capture the experimental creep–fatigue mechanical behavior, exceeding the standard Chaboche model’s accuracy. Furthermore, an interpretable model derived from the black-box neural ODE model through symbolic regression achieves accuracy comparable to the Chaboche model, enhancing its interpretability. The results highlight the potential of neural network-based ODE models to depict complex creep–fatigue behavior, eliminating the necessity for experts to define a specific, material-focused model form.

creep-fatigue↗
DOE OSTI2022

Multifunctional Cu 2 TSiS 4 (T = Mn and Fe): Polar Semiconducting Antiferromagnets with Nonlinear Optical Properties

In this work, Cu 2 TSiS 4 (T = Mn and Fe) polycrystalline and single-crystal materials were prepared with high-temperature solid-state and chemical vapor transport methods, respectively. The polar crystal structure (space group Pmn2 1 ) consists of chains of corner-sharing and distorted CuS 4 , Mn/FeS 4 , and SiS 4 tetrahedra, which is confirmed by Rietveld refinement using neutron powder diffraction data, X-ray single-crystal refinement, electron diffraction, energy-dispersive X-ray spectroscopy, and second harmonic generation (SHG) techniques. Magnetic measurements indicate that both compounds order antiferromagnetically at 8 and 14 K, respectively, which is supported by the temperature-dependent (100–2 K) neutron powder diffraction data. Additional magnetic reflections observed at 2 K can be modeled by magnetic propagation vectors k = (1/2,0,1/2) and k = (1/2,1/2,1/2) for Cu 2 MnSiS 4 and Cu 2 FeSiS 4 , respectively. The refined antiferromagnetic structure reveals that the Mn/Fe spins are canted away from the ac plane by about 14°, with the total magnetic moments of Mn and Fe being 4.1(1) and 2.9(1) μ B , respectively. Both compounds exhibit an SHG response with relatively modest second-order nonlinear susceptibilities. Density functional theory calculations are used to describe the electronic band structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Dynamics-Based Peptide–MHC Binding Optimization by a Convolutional Variational Autoencoder: A Use-Case Model for CASTELO

An unsolved challenge in the development of antigen-specific immunotherapies is determining the optimal antigens to target. Comprehension of antigen–major histocompatibility complex (MHC) binding is paramount toward achieving this goal. Here, we apply CASTELO, a combined machine learning-molecular dynamics (ML-MD) approach, to identify per-residue antigen binding contributions and then design novel antigens of increased MHC-II binding affinity for a type 1 diabetes-implicated system. We build upon a small-molecule lead optimization algorithm by training a convolutional variational autoencoder (CVAE) on MD trajectories of 48 different systems across four antigens and four HLA serotypes. We develop several new machine learning metrics including a structure-based anchor residue classification model as well as cluster comparison scores. ML-MD predictions agree well with experimental binding results and free energy perturbation-predicted binding affinities. Moreover, ML-MD metrics are independent of traditional MD stability metrics such as contact area and root-mean-square fluctuations (RMSF), which do not reflect binding affinity data. Finally, our work supports the role of structure-based deep learning techniques in antigen-specific immunotherapy design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Ship-based Observations and Climate Model Simulations of Cloud Phase over the Southern Ocean

The Southern Ocean (SO) clouds exert a significant influence on the Earth’s radiation budget. Here we analyzed ship-based remote sensing observations of SO clouds over a five-month long DOE ARM Measurements of Aerosols, Radiation and Clouds over the Southern Oceans (MARCUS) field campaign to better understand cloud phase variability. We developed a method to classify eight categories of hydrometeors (ice, liquid, mixed phase, rain, drizzle, snow, aerosols, and clear sky) based on measurements of lidar, radar and radiosondes. Cloud thermodynamic phases (liquid, ice and mixed phase) at coarser scales were further derived to compare with the DOE Energy Exascale Earth System Model version 1 (E3SMv1) simulation and the Earth Model Column Collaboratory (EMC 2 ) instrument simulator. For a scale-aware comparison with climate model simulations, we found that spatially averaging the raw remote sensing data (e.g., backscatter, reflectivity) results in increased cloud cover and cloud liquid, whereas, directly averaging cloud phase from higher to lower resolution maintains clear air regions and is thus recommended for in-cloud frequency comparisons. For cloud thermodynamic phases in stratiform clouds, the E3SM underestimates cloud ice and overestimates cloud liquid at temperatures between -40 and 0°C. When latitudes increase, both observations and simulations show a transition of dominant phase from liquid to ice for cloud tops as well as for the entire cloud columns, but the model underestimation of ice phase is more severe at higher latitudes. Such model bias is unlikely caused by spatial scale differences or lack of heterogeneity in cloud vertical structure in the simulation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

3D characterisation and quantification of an offshore freshened groundwater system in the Canterbury Bight

Although offshore freshened groundwater (OFG) systems have been documented in numerous continental margins worldwide, their geometry, controls and emplacement dynamics remain poorly constrained. Here we integrate controlled-source electromagnetic, seismic reflection and borehole data with hydrological modelling to quantitatively characterise a previously unknown OFG system near Canterbury, New Zealand. The OFG system consists of one main, and two smaller, low salinity groundwater bodies. The main body extends up to 60 km from the coast and a seawater depth of 110 m. We attribute along-shelf variability in salinity to permeability heterogeneity due to permeable conduits and normal faults, and to recharge from rivers during sea level lowstands. A meteoric origin of the OFG and active groundwater migration from onshore are inferred. However, modelling results suggest that the majority of the OFG was emplaced via topographically-driven flow during sea level lowstands in the last 300 ka. Global volumetric estimates of OFG will be significantly revised if active margins, with steep coastal topographies like the Canterbury margin, are considered.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Planck 2018 results - IV. Diffuse component separation

We present full-sky maps of the cosmic microwave background (CMB) and polarized synchrotron and thermal dust emission, derived from the third set of Planck frequency maps. These products have significantly lower contamination from instrumental systematic effects than previous versions. The methodologies used to derive these maps follow closely those described in earlier papers, adopting four methods (Commander, NILC, SEVEM, and SMICA) to extract the CMB component, as well as three methods (Commander, GNILC, and SMICA) to extract astrophysical components. Our revised CMB temperature maps agree with corresponding products in the Planck 2015 delivery, whereas the polarization maps exhibit significantly lower large-scale power, reflecting the improved data processing described in companion papers; however, the noise properties of the resulting data products are complicated, and the best available end-to-end simulations exhibit relative biases with respect to the data at the few percent level. Using these maps, we are for the first time able to fit the spectral index of thermal dust independently over 3° regions. We derive a conservative estimate of the mean spectral index of polarized thermal dust emission of β d = 1.55 ± 0.05, where the uncertainty marginalizes both over all known systematic uncertainties and different estimation techniques. For polarized synchrotron emission, we find a mean spectral index of β s = -3.1 ± 0.1, consistent with previously reported measurements. We note that the current data processing does not allow for construction of unbiased single-bolometer maps, and this limits our ability to extract CO emission and correlated components. The foreground results for intensity derived in this paper therefore do not supersede corresponding Planck 2015 products. For polarization the new results supersede the corresponding 2015 products in all respects.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Spatially-resolved measurements of spin valley polarization in MOCVD-grown monolayer WSe 2

Time-resolved Kerr rotation microscopy is used to generate and measure spin valley polarization in MOCVD-grown monolayer tungsten diselenide (WSe 2 ). The Kerr signal reveals bi-exponential decay with time constants of 100 ps and 3 ns. Measurements are performed on several triangular flakes from the same growth cycle and reveal larger spin valley polarization near the edges of the flakes. This spatial dependence is observed across multiple WSe 2 flakes in the Kerr rotation measurements but not in the spatially resolved reflectivity or microphotoluminescence data. Time-resolved pump-probe overlap measurements further reveal that the Kerr signal’s spatial dependence is not due to spin diffusion on the nanosecond timescale.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

A Spatiotemporal-Aware Weighting Scheme for Improving Climate Model Ensemble Predictions

Multimodel ensembling has been widely used to improve climate model predictions, and the improvement strongly depends on the ensembling scheme. In this work, we propose a Bayesian neural network (BNN) ensembling method, which combines climate models within a Bayesian model averaging framework, to improve the predictive capability of model ensembles. Our proposed BNN approach calculates spatiotemporally varying model weights and biases by leveraging individual models' simulation skill, calibrates the ensemble prediction against observations by considering observation data uncertainty, and quantifies epistemic uncertainty when extrapolating to new conditions. More importantly, the BNN method provides interpretability about which climate model contributes more to the ensemble prediction at which locations and times. Thus, beyond its predictive capability, the method also brings insights and understanding of the models to guide further model and data development. In this study, we design experiments using an ensemble of CMIP6 climate model simulations to illustrate the BNN ensembling method's capability with respect to prediction accuracy, interpretability, and uncertainty quantification (UQ). We demonstrate that BNN can correctly assign larger weights to the regions and seasons where the individual model fits the observation better. Moreover, its offered interpretability is consistent with our understanding of localized climate model performance. Additionally, BNN shows an increasing uncertainty when the prediction is farther away from the period with constrained data, which appropriately reflects our trustworthiness of the models in the changing climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Gamma Spectrometry Examination of the AGR-3/4 Irradiation

The results from gamma spectrometry examination of the different components from the combined third and fourth U.S. Advanced Gas Reactor (AGR) TRISO-coated particle fuel irradiation tests (AGR-3/4) have been analyzed. This experiment was designed to provide information about in-pile fission product migration. In each of the 12 capsules, a single stack of four compacts with designed-to-fail (DTF) particles surrounded by inner and outer graphite and/or graphitic matrix rings and a graphite sink ring were irradiated in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). Gamma spectrometry has been used to evaluate the gamma-emitting fission product inventory of compacts from the irradiation and evaluate the burnup of these compacts based on the activity of the radioactive cesium isotopes (i.e., Cs-134 and Cs-137) in the compacts. Burnup from gamma spectrometry compares well with predicted burnup from simulations. The inner and outer rings were also examined by gamma spectrometry to evaluate the total fission product inventory of the rings, and gamma emission computed tomography (GECT) was used to investigate the spatial distribution of gamma-emitting fission products within the rings. This report focuses on results obtained via the Precision Gamma Scanner (PGS) for the compacts and inner and outer rings. These non-destructive gamma measurements are currently being compared to recent destructive measurements of spatial fission product distributions in the rings and to predictions made via mathematical modeling. A separate report discusses the entire AGR-3/4 fission product mass balance for all irradiation capsule components including the inner and outer rings, graphite sink rings, capsule spacers, capsule foils, through tubes, and felts. This report is similar to the conference proceedings: Harp, J.M., Demkowicz, P.A., and Stempien, J.D., “Initial gamma spectrometry examination of the AGR-3/4 irradiation,” International Topical Meeting High Temperature Reactor Technology (HTR 2016), Las Vegas, NV, USA, November 2016, Paper HTR2016-18593, but it has been updated to reflect all the data that has been collected on AGR-3/4 using PGS. The Appendices contain extensive data from the collected gamma spectra.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Acoustic Impedance Inversions for Offshore CO 2 Storage: South Georgia Embayment, United States

This study builds and expands on previous CO 2 storage resource assessment studies of the southeastern offshore Atlantic margin by providing a detailed evaluation on how rock porosities and permeabilities are distributed across the Upper Cretaceous strata restricted to the South Georgia Embayment (SGE). Using legacy industry two-dimensional seismic reflection and well data, this assessment is the first application of multiple seismic inversion techniques in this area. This workflow provides a reliable and repeatable model-based inversion which gives an improved image to discriminate lithology and predict porosity. The workflow is applicable to future CO 2 storage resource assessment studies elsewhere. The inversion results indicate that distinct porosity and permeability regimes are present and distributed in the Upper Cretaceous strata within the SGE. The impedance and porosity relationships show well-founded and reliable correlation. These relationships reveal low impedance coincident to the high porosity intervals which are proposed as potential reservoir intervals for CO 2 storage. In addition, the result shows that the Upper Cretaceous strata have two main potential reservoirs in the lower part. These are overlain by a thick impermeable interval, mostly shale, which has high impedance, low porosity, and low permeability and extends within the SGE. This result is in agreement with a previous study that also proposed two significant storage reservoirs for CO 2 in the Upper Cretaceous strata. Since porosity distribution is estimated using multiple methods, it follows the trends of seismic signature and structures of the Upper Cretaceous strata. The extracted values of porosity, ranging from 15 to 36%, and permeability, ranging from 1 to 100 mD, are close to the measured values from the well core data at the Upper Cretaceous strata interval.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Advancing Industry 4.0: Multimodal Sensor Fusion for AI-Based Fault Detection in 3D Printing

Additive manufacturing, particularly fused deposition modeling, is transforming modern production by enabling rapid prototyping and complex part fabrication. However, its layer-by-layer process remains vulnerable to faults such as nozzle clogging, filament runout, and layer misalignment, which compromise print quality and reliability. Traditional inspection methods are costly, time-intensive, and often limited to post-process analysis, making them unsuitable for real-time intervention. In this current study, the authors developed a novel, low-cost, and portable faultdetection system that leverages multimodal sensor fusion and artificial intelligence for real-time monitoring in FDM-based 3D printing. The system integrates acoustic, vibration, and thermal sensing into a non-intrusive architecture, capturing complementary data streams that reflect both mechanical and process-related anomalies. Acoustic and thermal sensors operate in a fully contactless manner, while the vibration sensor requires minimal attachment such that it will not interfere with printer hardware, thereby preserving portability and ease of deployment. The multimodal signals are processed into spectrograms and time-frequency features, which are classified using convolutional neural networks for intelligent fault detection. The proposed system advances Industry 4.0 objectives by offering an affordable, scalable, and practical monitoring solution that improves faultdetection accuracy, reduces waste, and supports sustainable, adaptive manufacturing.

42 ENGINEERING↗
NASA NTRS1972

The emissivity of sea foam at microwave frequencies.

A consistent picture of the emission characteristics of sea foam at microwave frequencies has emerged from a survey of published radiometric measurements. The results are summarized, as functions of frequency and angle, by means of simple equations. Available data on the reflection properties of foam are also examined and shown to be qualitatively, but not quantitatively, in agreement with the radiometric results.

Stogryn, A.↗
NASA NTRS1973

Flight investigation of XB-70 structural response to oscillatory aerodynamic shaker excitation and correlation with analytical results

The low frequency symmetric structural response and damping characteristics of the XB-70 airplane were measured at four flight conditions: heavyweight at a Mach number of 0.87 at an altitude of 7620 meters (25,000 feet); lightweight at a Mach number of 0.86 at an altitude of 7620 meters (25,000 feet); a Mach number of 1.59 at an altitude of 11,918 meters (39.100 feet); and a Mach number of 2.38 and an altitude of 18,898 meters (62,000 feet). The flight data are compared with the response calculated by using early XB-70 design data and with the response calculated with mass, structural, and aerodynamic data updated to reflect as closely as possible the airplane characteristics at three of the flight conditions actually flown.

Mckay, J. M.↗