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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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NASA NTRSDate not supplied

Influence of Thermophysical Property Variability on Thermal Predictions of Ti-6Al-4V

The additive manufacturing (AM) industry has experienced rapid growth in recent decades as industrial interest in the process has grown. Because of this, there are many groups interested in simulations of the AM process. However, the influence of thermophysical property variability on the melt pool geometry during processing of various AM alloys is unclear. The goal of my work at NASA Langley Research Center (LaRC) was to characterize this influence on Ti-6Al-4V during AM processing alongside developing a tool to enable equivalent studies on other AM materials. To facilitate this process, a database tool was developed to contain and organize thermophysical data previously reported by primary sources. The specific thermophysical properties of interest for this study were density, specific heat capacity, and conductivity. Thermal diffusivity was calculated using the other three properties. This data was then fit with a Gaussian distribution and then randomly sampled from using Monte Carlo random value sampling. Using the Rosenthal equation, this sample data was used to simulate the temperature field during additive manufacturing and extract the melt pool geometry. Specifically, the melt pool’s length, width, and depth. This process was repeated an arbitrary number of times, with the default being 1000. Once this information was obtained, histograms were made showing the distributions of the sizes of the melt pool’s length, width, and depth. Representative statistical metrics of the distributions were calculated (mean, standard deviation, and coefficient of variance). This work found that at the simulated processing values, the melt pool’s width and depth had a 5.7% variation while the length had a 3.2% variation. Additionally, a tool was constructed to graph a thermal color map representation of the melt pool for specific, arbitrary values of density, specific heat, and conductivity. This tool allowed for more efficient plotting of individual queries of the thermophysical properties. The results that were observed in the research were that values reported in literature vary and this variance can have a significant impact on the simulation. Predictions of the melt pool’s dimensions show that length has a standard deviation of approximately 6 μm, width has a standard deviation of approximately 5 μm, and depth can vary by approximately 3 μm. Considering the mean sizes of length, width, and depth are 185 μm, 88 μm, and 44 μm respectively, such a deviation is significant. This shows that depth, for example, could be more than 10% larger or smaller than expected. This demonstrates that variability in the reported thermophysical properties are not negligible and should be expected to have an influence on the results of the laser powder bed fusion additive manufacturing process. When simulating this process in the future, measures should be taken to account for this discrepancy and the uncertainty involved

Justin Martin↗
NASA NTRS1974

Graphite thermal expansion reference for high temperature

The design requirements of the aerospace and high-temperature nuclear reactor industries necessitate reliable thermal expansion data for graphite and other carbonaceous materials. The feasibility of an acceptable reference for calibration of expansion measuring systems that operate in carbon-rich atmospheres at temperatures ranging to 2500 C is the prime subject of this work. Present-day graphite technology provides acceptable materials for stable, reproducible references, as reflected by some of the candidate materials. The repeatability for a single specimen in a given expansion measuring system was found to be plus or minus 1%, while the combined results of several tests made on a number of samples fell within a plus or minus 2.5% band.

Gaal, P. S.↗
NASA NTRS1984

Aerodynamic heating rate distributions induced by trailing edge controls on hypersonic aircraft configurations at Mach 8

Aerodynamic surface heating rate distributions in three dimensional shock wave boundary layer interaction flow regions are presented for a generic set of model configurations representative of the aft portion of hypersonic aircraft. Heat transfer data were obtained using the phase change coating technique (paint) and, at particular spanwise and streamwise stations for sample cases, by the thin wall transient temperature technique (thermocouples). Surface oil flow patterns are also shown. The good accuracy of the detailed heat transfer data, as attested in part by their repeatability, is attributable partially to the comparatively high temperature potential of the NASA-Langley Mach 8 Variable Density Tunnel. The data are well suited to help guide heating analyses of Mach 8 aircraft, and should be considered in formulating improvements to empiric analytic methods for calculating heat transfer rate coefficient distributions.

Kaufman, L. G., II↗
NASA NTRS2017

Segmented Aperture Interferometric Nulling Testbed (SAINT) II: Component Systems Update

"This work presents updates to the coronagraph and telescope components of the Segmented Aperture Interfer-ometric Nulling Testbed (SAINT). The project pairs an actively-controlled macro-scale segmented mirror withthe Visible Nulling Coronagraph (VNC) towards demonstrating capabilities for the future space observatoriesneeded to directly detect and characterize a significant sample of Earth-sized worlds around nearby stars inthe quest for identifying those which may be habitable and possibly harbor life. Efforts to improve the VNCwavefront control optics and mechanisms towards repeating narrowband results are described. A narrative isprovided for the design of new optical components aimed at enabling broadband performance. Initial work withthe hardware and software interface for controlling the segmented telescope mirror is also presented."

high-contrast imaging↗
NASA NTRS2023

Electronic Nose Development and Preliminary Human Breath Testing for Rapid, Non-Invasive COVID-19 Detection

We adapted an existing, spaceflight-proven, robust “electronic nose” (E-Nose) that uses an array of electrical resistivity-based nanosensors mimicking aspects of mammalian olfaction to conduct on-site, rapid screening for COVID-19 infection by measuring the pattern of sensor responses to volatile organic compounds (VOCs) in exhaled human breath. We built and tested multiple copies of a hand-held prototype E-Nose sensor system, composed of 64 chemically sensitive nanomaterial sensing elements tailored to COVID-19 VOC detection; data acquisition electronics; a smart tablet with software (App) for sensor control, data acquisition and display; and a sampling fixture to capture exhaled breath samples and deliver them to the sensor array inside the E-Nose. The sensing elements detect the combination of VOCs typical in breath at parts-per-billion (ppb) levels, with repeatability of 0.02% and reproducibility of 1.2%; the measurement electronics in the E-Nose provide measurement accuracy and signal-to-noise ratios comparable to benchtop instrumentation. Preliminary clinical testing at Stanford Medicine with 63 participants, their COVID-19-positive or COVID-19-negative status determined by concomitant RT-PCR, discriminated between these two categories of human breath with a 79% correct identification rate using “leave-one-out” training-and-analysis methods. Analyzing the E-Nose response in conjunction with body temperature and other non-invasive symptom screening using advanced machine learning methods, with a much larger database of responses from a wider swath of the population, is expected to provide more accurate on-the-spot answers. Additional clinical testing, design refinement, and a mass manufacturing approach are the main steps toward deploying this technology to rapidly screen for active infection in clinics and hospitals, public and commercial venues, or at home.

COVID-19↗
DOE OSTI2025

Single-shot electro-optic sampling with arbitrary terahertz polarization

With the recent development of diversity electro-optic sampling (DEOS), significant progress has been made in the range of applicability of single-shot EOS measurements, allowing broadband THz waveforms to be captured in a single shot over large temporal windows. In addition to the decrease in acquisition time compared to standard multishot data acquisition, this technique allows measurements on systems far from equilibrium with large shot-to-shot noise or with irreversible or poorly repeatable dynamics. Although DEOS has been demonstrated and verified for linearly polarized THz waveforms, we investigate the effects resulting from the presence of a secondary polarization component. This imposes new challenges for accurate waveform reconstruction, and opens the opportunity to measure out complex polarization states such as arbitrary elliptically polarized THz field. We demonstrate a single-shot diversity-electro-optic-sampling-based approach to capture both x- and y-THz fields simultaneously with a single (110)-cut EO crystal for THz polarimetry and ellipsometry over a wide range of frequencies.

Lenz, Maximilian [University of California, Los An↗
NASA NTRS1991

Effect of sulfur removal on Al2O3 scale adhesion

The effect of removing sulfur impurity on the adhesion of Al2O3 scale to NiCrAl was investigated in four experiments. It was found that removing sulfur to concentration less than 1 ppm per weight is sufficient to produce a very significant degree of alpha-Al2O3 scale adhesion to undoped NiCrAl alloys. Results of experiments show that repeated oxidation, and polishing after each oxidation cycle, of pure NiCrAl alloy lowered sulfur content from 10 to 2 ppm by weight (presumably by removing the segregated interfacial layer after each cycle); thinner samples became adherent after fewer oxidation-polishing cycles because of more limited supply of sulfur. It was found that spalling in subsequent cyclic oxidation tests was a direct function of the initial sulfur content. The transition between the adherent and nonadherent behavior was modeled in terms of sulfur flux, sulfur content, and sulfur segregation.

Smialek, James L.↗
NASA NTRS2011

Calibration of the MSL/ChemCam/LIBS Remote Sensing Composition Instrument

The ChemCam instrument suite on board the 2011 Mars Science Laboratory (MSL) Rover, Curiosity, will provide remote-sensing composition information for rock and soil samples within seven meters of the rover using a laser-induced breakdown spectroscopy (LIBS) system, and will provide context imaging with a resolution of 0.10 mradians using the remote micro-imager (RMI) camera. The high resolution is needed to image the small analysis footprint of the LIBS system, at 0.2-0.6 mm diameter. This fine scale analytical capability will enable remote probing of stratigraphic layers or other small features the size of "blueberries" or smaller. ChemCam is intended for rapid survey analyses within 7 m of the rover, with each measurement taking less than 6 minutes. Repeated laser pulses remove dust coatings and provide depth profiles through weathering layers, allowing detailed investigation of rock varnish features as well as analysis of the underlying pristine rock composition. The LIBS technique uses brief laser pulses greater than 10 MW/square mm to ablate and electrically excite material from the sample of interest. The plasma emits photons with wavelengths characteristic of the elements present in the material, permitting detection and quantification of nearly all elements, including the light elements H, Li, Be, B, C, N, O. ChemCam LIBS projects 14 mJ of 1067 nm photons on target and covers a spectral range of 240-850 nm with resolutions between 0.15 and 0.60 nm FWHM. The Nd:KGW laser is passively cooled and is tuned to provide maximum power output from -10 to 0 C, though it can operate at 20% degraded energy output at room temperature. Preliminary calibrations were carried out on the flight model (FM) in 2008. However, the detectors were replaced in 2009, and final calibrations occurred in April-June, 2010. This presentation describes the LIBS calibration and characterization procedures and results, and details plans for final analyses during rover system thermal testing, planned for early March.

Wiens, R. C.↗
DOE OSTI2024

Field-Emission Properties of Vertically Aligned Carbon Nanotube Cathodes of Varying Geometries

This work characterizes the bulk emission properties of carbon nanotube (CNT) forest cathodes fabricated with various geometries. Geometries explored include dense nanotube forests of varying height grown on 5×5 mm silicon (Si) substrates and discrete, patterned CNT pillars fabricated using UV photolithography. Dense forests heights ranged from 526 μ m to 1.41 mm, with packing fraction for dense forest calculated to be 4e10 nanotubes/cm2 based on an average nanotube separation distance of 100 nm for fixed growth dense forests. Patterned sample micro pillar heights ranged from 47 to 393 μ m with pillar widths on tested samples ranging from 250 to 270 μ m . Properties explored include emission current, turn-on field, and emission current performance over time. A parallel plate electron beam diode with a 100- μ m A-K gap and an automated test apparatus were developed to provide a configurable experiment that provides accurate and repeatable measurements for dc, dc sweep, and timed performance testing. Operating voltages for the voltage sweeps spanned from 0 to −350 V. Furthermore, testing has shown evidence of a hysteresis effect on the emission current tied to the applied field history as well as shifting of the turn-on field magnitude throughout the testing period, suggesting a conditioning effect during use. Three separate emission regions in the I–V curves during sweep testing have also been observed. In the geometric study, dense forests and patterned samples were sweep tested up to a peak applied voltage of −250 V, with the taller samples generally performing better. Currents produced in the geometric study from the dense forest emitters ranged from 36.8 to 572.34 μ A , with current densities ranging from 15 to 2.29 mA/cm2. Currents produced from the patterned micropillar emitters ranged from 39.4 to 317.51 μ A , with current densities ranging from 67 to 3 mA/cm2. DC time testing s...

36 MATERIALS SCIENCE↗
DOE OSTI2026

An algebraic convolution formulation for multiple-scattering correction in small-angle neutron scattering

Multiple scattering in small-angle neutron scattering (SANS) redistributes spectral weight and distorts structural interpretation, particularly for thick or strongly scattering samples. We develop a finite-dimensional spectral desmearing framework that corrects multiple scattering without resorting to integral transforms or model-dependent extrapolation. The primary intensity is expanded in an orthonormal basis adapted to the isotropic transverse-momentum measure, under which convolution reduces to a recursive tensor contraction, allowing the Poisson-weighted multiple-scattering series to be evaluated directly in a finite-dimensional basis representation. This formulation yields a stable forward–inverse mapping between apparent and primary spectra. Numerical tests demonstrate convergence under repeated convolution and accurate recovery of the single-scattering intensity. Application to SANS measurements collected at multiple neutron facilities, including the Spallation Neutron Source, the High Flux Isotope Reactor, and the Institut Laue-Langevin, shows the quantitative reconstruction of the underlying primary spectrum across a wide range of transmission conditions, including strongly attenuating samples. Here, the method provides a stable, model-agnostic framework for multiple-scattering correction in SANS and enables consistent structural interpretation across instruments and scattering regimes.

Tung, Chi-Huan [Oak Ridge National Laboratory (ORN↗
DOE OSTI2025

The role of fast and slow dynamics in nonlinear resonant ultrasound spectroscopy of consolidated granular materials

Abstract Elastic nonlinearity observed in consolidated granular media can be attributed to the combination of slow and fast effects, which give rise to hysteresis and relaxation of both modulus and damping after the sample is perturbed. A consequence is a high level of complexity in the measurements of the sample linear and nonlinear elastic parameters. The results of experiments are dependent on the experimental protocol that is adopted to measure the relevant quantities and it is hard to quantify parameters with accuracy and repeatability. Here we focus on examining Nonlinear Resonant Ultrasound Spectroscopy, showing experimentally the role of slow dynamics in the process and quantifying/discussing its influence on the quantification of nonlinearity. We also propose a model to describe the process, which shows that different contributions to nonlinearity (e.g., classical and hysteretic) could be due to physical features (defects) relaxing with different relaxation times.

Science & Technology - Other Topics↗
NASA NTRS1986

Multifrequency observations of blazars. II - The variability of the 1 micron to 2 mm continuum

The results of monitoring, over a period of two years, a sample of 12 blazars, in 11 wave bands between 1 micron and 2 mm are presented. All sources exhibit some variability, both in flux density and spectral shape. The infrared variability is consistent with repeated injections of reaccelerations of electrons, which subsequently suffer radiative losses. For OJ 287, 3C 279, and 3C 345, a decay and steepening of the infrared spectrum occurred as the submillimeter turnover evolved to lower frequencies, consistent with expansion of the emitting region. The peak flux, however, increased during this evolution. This behavior is inconsistent with most models for compact extragalactic sources, but it is naturally explained by shock waves traveling in an adiabatically expanding relativistic jet (Marscher and Gear, 1985).

Gear, W. K.↗
NASA NTRS1983

Forest Resource Information System (FRIS)

The technological and economical feasibility of using multispectral digital image data as acquired from the LANDSAT satellites in an ongoing operational forest information system was evaluated. Computer compatible multispectral scanner data secured from the LANDSAT satellites were demonstrated to be a significant contributor to ongoing information systems by providing the added dimensions of synoptic and repeat coverage of the Earth's surface. Major forest cover types of conifer, deciduous, mixed conifer-deciduous and non-forest, were classified well within the bounds of the statistical accuracy of the ground sample. Further, when overlayed with existing maps, the acreage of cover type retains a high level of positional integrity. Maps were digitized by a graphics design system, overlayed and registered onto LANDSAT imagery such that the map data with associated attributes were displayed on the image. Once classified, the analysis results were converted back to map form as a cover type of information. Existing tabular information as represented by inventory is registered geographically to the map base through a vendor provided data management system. The notion of a geographical reference base (map) providing the framework to which imagery and tabular data bases are registered and where each of the three functions of imagery, maps and inventory can be accessed singly or in combination is the very essence of the forest resource information system design.

Source record↗
NASA NTRS1992

Artificial neural network implementation of a near-ideal error prediction controller

A theory has been developed at the University of Virginia which explains the effects of including an ideal predictor in the forward loop of a linear error-sampled system. It has been shown that the presence of this ideal predictor tends to stabilize the class of systems considered. A prediction controller is merely a system which anticipates a signal or part of a signal before it actually occurs. It is understood that an exact prediction controller is physically unrealizable. However, in systems where the input tends to be repetitive or limited, (i.e., not random) near ideal prediction is possible. In order for the controller to act as a stability compensator, the predictor must be designed in a way that allows it to learn the expected error response of the system. In this way, an unstable system will become stable by including the predicted error in the system transfer function. Previous and current prediction controller include pattern recognition developments and fast-time simulation which are applicable to the analysis of linear sampled data type systems. The use of pattern recognition techniques, along with a template matching scheme, has been proposed as one realizable type of near-ideal prediction. Since many, if not most, systems are repeatedly subjected to similar inputs, it was proposed that an adaptive mechanism be used to 'learn' the correct predicted error response. Once the system has learned the response of all the expected inputs, it is necessary only to recognize the type of input with a template matching mechanism and then to use the correct predicted error to drive the system. Suggested here is an alternate approach to the realization of a near-ideal error prediction controller, one designed using Neural Networks. Neural Networks are good at recognizing patterns such as system responses, and the back-propagation architecture makes use of a template matching scheme. In using this type of error prediction, it is assumed that the system error responses be known for a particular input and modeled plant. These responses are used in the error prediction controller. An analysis was done on the general dynamic behavior that results from including a digital error predictor in a control loop and these were compared to those including the near-ideal Neural Network error predictor. This analysis was done for a second and third order system.

Mcvey, Eugene S.↗
NASA NTRS2015

Time‐Series Analysis: A Cautionary Tale

Time-series analysis has often been a useful tool in atmospheric science for deriving long-term trends in various atmospherically important parameters (e.g., temperature or the concentration of trace gas species). In particular, time-series analysis has been repeatedly applied to satellite datasets in order to derive the long-term trends in stratospheric ozone, which is a critical atmospheric constituent. However, many of the potential pitfalls relating to the non-uniform sampling of the datasets were often ignored and the results presented by the scientific community have been unknowingly biased. A newly developed and more robust application of this technique is applied to the Stratospheric Aerosol and Gas Experiment (SAGE) II version 7.0 ozone dataset and the previous biases and newly derived trends are presented.

Damadeo, Robert↗
NASA NTRS2022

Reversible Colorimetric Sensing of Volatile Analytes By Wicking in Close Proximity to A Photonic Film

Isolation of volatile analytes from environmental or biological fluids is a rate-determining step that can delay the response time for continuous sensing. In this paper, we demonstrate a colorimetric sensing system that enables the rapid detection of gas-phase analytes released from a flowing micro-volume fluid sample. The sensor platform is an analyte-responsive metal-insulator-metal (MIM) thin-film structure integrated with a large area quartz micropillar array. This allows precise planar alignment and microscale separation (310 μm) of the optical and fluidic structures. This configuration offers rapid and homogeneous color changes over large areas that permits detection by low-resolution optics or eye, which is well-suited to portable/wearable devices. For our proof-of-principle demonstration, we utilized a poly(methyl methacrylate) (PMMA) spacer and evaluated the sensor's response (color change) to ethanol vapor. We show that the RGB color value is quantitatively linked to the spacer swelling, which is reversible and repeatable. The optofluidic platform reduces the sensor response time from minutes to seconds compared with experiments using a conventional chamber. The sensor's concentration-dependent response was examined, confirming the potential of the reported sensing platform for continuous, compact, and quantitative colorimetric analysis of volatile analytes in low-volume samples, such as biofluids.

Timothy J. Palinski↗
NASA NTRS2012

Instrumentation and First Results of the Reflected Solar Demonstration System for the Climate Absolute Radiance and Refractivity Observatory

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission key goals include enabling observation of high accuracy long-term climate change trends, use of these observations to test and improve climate forecasts, and calibration of operational and research sensors. The spaceborne instrument suites include a reflected solar spectroradiometer, emitted infrared spectroradiometer, and radio occultation receivers. The requirement for the RS instrument is that derived reflectance must be traceable to Sl standards with an absolute uncertainty of <0.3% and the error budget that achieves this requirement is described in previo1L5 work. This work describes the Solar/Lunar Absolute Reflectance Imaging Spectroradiometer (SOLARIS), a calibration demonstration system for RS instrument, and presents initial calibration and characterization methods and results. SOLARIS is an Offner spectrometer with two separate focal planes each with its own entrance aperture and grating covering spectral ranges of 320-640, 600-2300 nm over a full field-of-view of 10 degrees with 0.27 milliradian sampling. Results from laboratory measurements including use of integrating spheres, transfer radiometers and spectral standards combined with field-based solar and lunar acquisitions are presented. These results will be used to assess the accuracy and repeatability of the radiometric and spectral characteristics of SOLARIS, which will be presented against the sensor-level requirements addressed in the CLARREO RS instrument error budget.

McCorkel, Joel↗
NASA NTRS2017

Patterns of Canopy and Surface Layer Consumption in a Boreal Forest Fire from Repeat Airborne Lidar

Fire in the boreal region is the dominant agent of forest disturbance with direct impacts on ecosystem structure, carbon cycling, and global climate. Global and biome-scale impacts are mediated by burn severity, measured as loss of forest canopy and consumption of the soil organic layer. To date, knowledge of the spatial variability in burn severity has been limited by sparse field sampling and moderate resolution satellite data. Here, we used pre- and post-fire airborne lidar data to directly estimate changes in canopy vertical structure and surface elevation for a 2005 boreal forest fire on Alaskas Kenai Peninsula. We found that both canopy and surface losses were strongly linked to pre-fire species composition and exhibited important fine-scale spatial variability at sub-30m resolution. The fractional reduction in canopy volume ranged from 0.61 in lowland black spruce stands to 0.27 in mixed white spruce and broad leaf forest. Residual structure largely reflects standing dead trees, highlighting the influence of pre-fire forest structure on delayed carbon losses from above ground biomass, post-fire albedo, and variability in understory light environments. Median loss of surface elevation was highest in lowland black spruce stands (0.18 m) but much lower in mixed stands (0.02 m), consistent with differences in pre-fire organic layer accumulation. Spatially continuous depth-of-burn estimates from repeat lidar measurements provide novel information to constrain carbon emissions from the surface organic layer and may inform related research on post-fire successional trajectories. Spectral measures of burn severity from Landsat were correlated with canopy (r = 0.76) and surface (r = -0.71) removal in black spruce stands but captured less of the spatial variability in fire effects for mixed stands (canopy r = 0.56, surface r = -0.26), underscoring the difficulty in capturing fire effects in heterogeneous boreal forest landscapes using proxy measures of burn severity from Landsat.

Alonzo, Michael↗