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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

An evaluation of the signature extension approach to large area crop inventories utilizing space image data

The author has identified the following significant results. Two examples of haze correction algorithms were tested: CROP-A and XSTAR. The CROP-A was tested in a unitemporal mode on data collected in 1973-74 over ten sample segments in Kansas. Because of the uniformly low level of haze present in these segments, no conclusion could be reached about CROP-A's ability to compensate for haze. It was noted, however, that in some cases CROP-A made serious errors which actually degraded classification performance. The haze correction algorithm XSTAR was tested in a multitemporal mode on 1975-76 LACIE sample segment data over 23 blind sites in Kansas and 18 sample segments in North Dakota, providing wide range of haze levels and other conditions for algorithm evaluation. It was found that this algorithm substantially improved signature extension classification accuracy when a sum-of-likelihoods classifier was used with an alien rejection threshold.

Nalepka, R. F.↗
NASA NTRS2025

Subsonic Ultra Green Aircraft Research: Phase V – Buffet Test Report

This test report summarizes work performed by the Boeing Subsonic Ultra-Green Aircraft Research (SUGAR) team in the Phase V Transonic Truss-Braced Wing contract task. The task was awarded in September 2020, and ended at the end of September 2022. As a part of the SUGAR Phase V contract task, Boeing developed a wind tunnel test plan, model requirements, then fabricated and conducted a dedicated transonic buffet wind tunnel test. The test focused on the investigation of buffet onset, and the ability to accurately predict buffet onset for the TTBW configuration. This report summarizes the results and post-test analysis of the 9% scale, semispan, Transonic Truss-Braced Wing (TTBW) transonic buffet model tested at the NASA Ames Research Center Unitary Plan Wind Tunnel (UPWT) 11-Foot Transonic Wind Tunnel (11-Ft TWT) facility located at Moffett Field, CA. It was tested from January 24, 2022, through February 18, 2022. The wind tunnel test was successful in capturing buffet onset at the model design dynamic pressure. Multiple configurations were tested starting in the wing-body-strut configuration and ending with the full configuration including wing-body-strut-nacelle/pylon, and flap hinge. The test also measured the effect of control surface deflections (ailerons and spoilers), as well as the effect of an outboard strut flap. Steady data collected during the test included standard force and moment measurements, as well as wing, strut, nacelle, and body (fuselage) static pressures. These data were collected in a standard pitch-pause mode. Unsteady data captured in the test, collected in continuous pitch mode, included wing and strut dynamic pressures, accelerations, and strains. According to test data, previous concerns regarding critical buffet onset on the strut (at low vehicle lift coefficient) and in the wing-strut channel have been mitigated. Buffet onset on the TTBW appears to follow conventional wing-induced buffet onset mechanisms. However, the critical station where buffet onset first occurs has moved inboard to the wing-strut juncture span location (55-60% span) from the typical ~70% span location. Test data obtained by unsteady pressure transducers provided a good match to expected buffet onset modes. An assessment of different tools and methodologies for predicting buffet onset was conducted. Reasonable agreement was found for buffet boundary predictions between most of the methods examined when using a forward trip location, with the greatest discrepancies from the pitching moment break and trailing edge pressure divergence methods. When an aft trip location was used the buffet boundary predictions diverged more significantly from unsteady pressure measurements. In addition, good agreement between the buffet onset trends were found when the Reynolds number, configuration, or spanload was changed.

strut↗
DOE OSTI2024

Revealing subterahertz atomic vibrations in quantum paraelectrics by surface-sensitive spintronic terahertz spectroscopy

Understanding surface collective dynamics in quantum materials is crucial for advancing quantum technologies. For example, surface phonon modes in quantum paraelectrics are thought to be essential in facilitating interfacial superconductivity. However, detecting these modes, especially below 1 terahertz, is challenging because of limited sampling volumes and the need for high spectroscopic resolution. Here, we report surface soft transverse optical (TO1) phonon dynamics in KTaO 3 and SrTiO 3 by surface-sensitive spintronic terahertz spectroscopy that can sense the collective modes only a few nanometers deep from the surface. In KTaO 3 , the TO1 mode softens and sharpens with decreasing temperature, leveling off at 0.7 terahertz. In contrast, this mode in SrTiO 3 broadens substantially below the quantum paraelectric crossover and coincides with the hardening of a sub–milli–electron volt phonon mode related to the antiferrodistortive transition. These observations that deviate from their bulk properties may have implications for interfacial superconductivity and ferroelectricity. The developed technique opens opportunities for sensing low-energy surface collective excitations.

Chu, Zhaodong↗
NASA NTRS2020

Improving Quantitative Laboratory Analysis of Phycobiliproteins to Provide High Quality Validation Data for Ocean Color Remote Sensing Algorithm

Identification and characterization of phytoplankton communities and their physiology is a primary aim of NASA's PACE satellite mission. The concentration and composition of phytoplankton pigments modulate the spectral distribution of light emanating from the ocean, which is measured by ocean color satellites, and thus provide critical information on phytoplankton community composition and physiological parameters. One diagnostic class of pigments not routinely well-characterized is the phycobiliproteins (PBPs), and NASA has a requirement to collect and distribute high quality in situ data in support of data product validation activities for ocean color missions. Phycobiliproteins are light-harvesting proteins that are the predominant photosynthetic pigments in some classes of phytoplankton including cyanobacteria, such as Synechococcus, Trichodesmium, and Microcystis. With the advance of hyperspectral ocean color sensors such as on PACE (expected to launch in late 2022), it is essential that we implement routine analysis of PBPs that satisfies several considerations: reproducible, high extraction efficiency for a variety of environments, and Suitable for large scale analysis. Published techniques for PBP analysis vary in recommendations for: collection, extraction, disruption mode, and analysis; evidence suggests the variation in results may depend at least in part on the species and even strain(s) of interest. Experiments that tested variations in these parameters have drawn very different conclusions regarding extraction efficiency and reproducibility. Cyanobacteria are more difficult to extract than other PBP-containing algae such as cryptophytes, but can be important primary producers. We used a cryptophyte (Rhodomonas salina) and cyanobacterium (Synechococcus sp.) to compare extraction efficiencies of water samples concentrated via centrifugation to filtered samples using two different extraction buffers (phosphate and asolectin-CHAPS). Samples were analyzed on a fluorometer configured for PC and PE detection. The results have important implications for collection and storage of samples for routine analysis; some previous studies (although not all) have suggested that filtered samples have a much lower extraction efficiency than whole water samples.

Kenemer, Christopher↗
NASA NTRS2006

Computing frequency by using generalized zero-crossing applied to intrinsic mode functions

This invention presents a method for computing Instantaneous Frequency by applying Empirical Mode Decomposition to a signal and using Generalized Zero-Crossing (GZC) and Extrema Sifting. The GZC approach is the most direct, local, and also the most accurate in the mean. Furthermore, this approach will also give a statistical measure of the scattering of the frequency value. For most practical applications, this mean frequency localized down to quarter of a wave period is already a well-accepted result. As this method physically measures the period, or part of it, the values obtained can serve as the best local mean over the period to which it applies. Through Extrema Sifting, instead of the cubic spline fitting, this invention constructs the upper envelope and the lower envelope by connecting local maxima points and local minima points of the signal with straight lines, respectively, when extracting a collection of Intrinsic Mode Functions (IMFs) from a signal under consideration.

Huang, Norden E.↗
NASA NTRSDate not supplied

Airborne Observations of Particle Density in High Ice Water Content (HWC) Cloud Systems

A series of airborne field campaigns has been conducted since 2014 to measure the microphysical properties of high ice-water content (HIWC) clouds in maritime mesoscale convective systems (MCS) and tropical storms. Two of these, the HIWC RADAR-2 campaign (2018) targeting cloud systems in the Gulf of Mexico and Pacific Ocean, and the HIWC-2022 campaign targeting cloud systems in the Gulf of Mexico, Caribbean Sea, and Atlantic Ocean, have been analyzed to investigate graupel encounters at typical jet aircraft cruise altitudes. In-situ cloud observations from these two campaigns confirmed results from the prior studies, indicating that high concentrations of small ice particles exist in areas of HIWC. However, in the 2022 campaign, 90% of the cloud regions with ice water content (IWC) above 2.0 g/m3 also contained significant amounts of graupel and/or frozen drops. Using a mass-size parameterization that accounts for both small ice and larger high-density particles, we show that the mass distributions in cloud regions above 2.0 g/m3 are often strongly bimodal, with the small particle mode containing roughly half of the collective cloud mass, and the graupel mode containing the other half. In contrast, HIWC cloud passes in a 2018 tropical cyclone contained less relative graupel mass than the MCS cloud systems of 2018 and 2022. We present two different methods of estimating particle mass for mixed populations of small-ice and graupel particles, one using a hybrid two-class approach, and another using a single-class approach that takes both particle size and shape metrics into account. Derived IWC using these methods are compared to bulk IWC measurements collected during the campaigns. We also show the relative occurrence of graupel at various IWC levels and discuss the potential application of these results in evaluating density-aware microphysical schemes in cloud and weather models.

Aircraft Icing↗
DOE OSTI2021

Shocks and information exchange in de Sitter space

We discuss some implications of recent progress in understanding the black hole information paradox for complementarity in de Sitter space. Extending recent work by two of the authors, we describe a bulk procedure that allows information expelled through the cosmological horizon to be received by an antipodal observer. Generically, this information transfer takes a scrambling time t=H- 1 (S ds ). We emphasize that this procedure relies crucially on selection of the Bunch-Davies vacuum state, interpreted as the thermofield double state that maximally entangles two antipodal static patches. The procedure also requires the presence of an (entangled) energy reservoir, created by the collection of Hawking modes from the cosmological horizon. We show how this procedure avoids a cloning paradox and comment on its implications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Automated Grain Boundary (GB) Segmentation and Microstructural Analysis in 347H Stainless Steel Using Deep Learning and Multimodal Microscopy

Austenitic 347H stainless steel offers superior mechanical properties and corrosion resistance required for extreme operating conditions such as high temperature. The change in microstructure due to composition and process variations is expected to impact material properties. Identifying microstructural features such as grain boundaries thus becomes an important task in the process-microstructure-properties loop. Applying convolutional neural network (CNN)-based deep learning models is a powerful technique to detect features from material micrographs in an automated manner. In contrast to microstructural classification, supervised CNN models for segmentation tasks require pixel-wise annotation labels. However, manual labeling of the images for the segmentation task poses a major bottleneck for generating training data and labels in a reliable and reproducible way within a reasonable timeframe. Microstructural characterization especially needs to be expedited for faster material discovery by changing alloy compositions. Here, in this study, we attempt to overcome such limitations by utilizing multimodal microscopy to generate labels directly instead of manual labeling. We combine scanning electron microscopy images of 347H stainless steel as training data and electron backscatter diffraction micrographs as pixel-wise labels for grain boundary detection as a semantic segmentation task. The viability of our method is evaluated by considering a set of deep CNN architectures. We demonstrate that despite producing instrumentation drift during data collection between two modes of microscopy, this method performs comparably to similar segmentation tasks that used manual labeling. Additionally, we find that naïve pixel-wise segmentation results in small gaps and missing boundaries in the predicted grain boundary map. By incorporating topological information during model training, the connectivity of the grain boundary network and segmentation performance is improved. Finally, our approach is validated by accurate computation on downstream tasks of predicting the underlying grain morphology distributions which are the ultimate quantities of interest for microstructural characterization.

36 MATERIALS SCIENCE↗
DOE OSTI2024

237 Np Fission Spectrum Cumulative Fission Product Yield Measurement Using Godiva IV Critical Assembly

Precise integral measurement of fast neutron-induced fission product yields for various actinides is of high interest for applied nuclear science. The goal of this effort is to improve uncertainties in fission product yield values of 237 Np. Fission was induced in a NpO 2 (NO 3 ) target using the Godiva IV critical assembly in burst mode. The irradiated sample was transferred to a high-resolution γ-ray detection setup within 50 minutes. γ-ray list mode data was collected from 50 minutes to 1 week after the irradiation. γ-ray spectroscopy was performed to analyze the time dependent γ-ray yields using an automated peak search algorithm to identify isotopes by their decay γ-ray energy and half-life. Finally, the initial activity for each isotope identified was used to calculate their fission product yield.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

239 Pu Fission Spectrum Cumulative Fission Product Yield Measurement Using Godiva IV Critical Assembly

Precise integral measurement of fast neutron-induced fission product yields for various actinides is of high interest for applied nuclear science. The goal of this effort is to improve uncertainties in fission product yield values of 239 Pu. Fission was induced in a pure 239 Pu (>99%) target using the Godiva IV critical assembly in burst mode. Further, the irradiated sample was transferred to a high-resolution γ-ray detector within 45 minutes. γ-ray list mode data was collected from 45 minutes to 1 week after the irradiation. γ-ray spectroscopy was performed to analyze the time dependent γ-ray yields using an automated peak search algorithm to identify isotopes by their decay γ-ray energy and half-life. The initial activity for each isotope identified was used to calculate their fission product yield.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Low Frequency Vibrational Modes of Two-Dimensional Lead-Free Metal Halide Double Perovskites

2D layered double perovskites of (S-MPA) 4 AgBiI 8 (MPA-AgBiI 8 ) and (S-MPA) 4 CuBiI 8 (MPA-CuBiI 8 ) (S-MPA, S-β-methylphenethylammonium) were synthesized with a hydrothermal method. The crystal structure of MPA-AgBiI 8 was determined using single-crystal X-ray diffraction (scXRD). Powder XRD (pXRD) data suggest that the crystal structure of MPA-CuBiI 8 is more complex than that of MPA-AgBiI 8 . UV-Vis electronic absorption spectra of these perovskites reveal a bandgap of 2.03 eV for both. Short exciton lifetime from time-resolved photoluminescence (TRPL) results and low PL intensity of the Cu-based perovskite suggest a high density of trap states within the bandgap. Low frequency Raman spectra of both materials show distinct peaks and a slightly higher frequency for the Cu-based perovskite than the Ag-based perovskite. Density functional theory (DFT) calculations were conducted to simulate the low frequency Raman spectra and help explain the different phonon modes, which are collective vibrations of metal halide bond bending and stretching within the Ag- and Cu-centered octahedra coupled with MPA libration and twisting within the inorganic layer. The DFT theory also quantified octahedral distortions in the two perovskites. Furthermore, this combined experimental and computational study provides new insights into the low frequency vibrations of 2D perovskites.

Halogens↗
DOE OSTI2020

Forecasting the Decay of Hybrid Perovskite Performance Using Optical Transmittance or Reflected Dark-Field Imaging

The practicality and economic viability of hybrid perovskite solar cells hinge on their operational lifetime, and methods for forecasting the performance of perovskites under different operational stresses are urgently needed. Here, we explore the evolution of material-level optoelectronic properties as MAPbI 3 degrades and discover universal behaviors where the carrier diffusion length (L D ) decays before quasi-Fermi-level splitting (ΔE F ), regardless of the specific stress protocol (oxygen, humidity, thermal stress, or a combination). We employ a machine learning greedy feature selection model that uses initially measured properties to predict the time it takes L D to decrease to 85% of its initial value with a prediction accuracy of 12.8%. This model reveals a strong correlation between the initial rate of transmittance change and the time until loss of transport. We translate this material-level finding to photovoltaic device-level forecasting by demonstrating that the rate of change of transmittance is equivalent to the rate of change of the spatial standard deviation of dark-field image intensity (i.e., scattered light intensity) collected in reflection mode (and thus applicable to devices with opaque contacts). Furthermore, this work demonstrates that transmittance and scattering methods are highly effective for accelerated material (and device) stability evaluation and forecasting.

14 SOLAR ENERGY↗
DOE OSTI2024

Experimental Observation of a New Attenuation Mechanism in hcp ‐Metals That May Operate in the Earth's Inner Core

Abstract Seismic observations show the Earth's inner core has significant and unexplained variation in seismic attenuation with position, depth and direction. Interpreting these observations is difficult without knowledge of the visco‐ or anelastic dissipation processes active in iron under inner core conditions. Here, a previously unconsidered attenuation mechanism is observed in zinc, a low pressure analog ofhcp‐iron, during small strain sinusoidal deformation experiments. The experiments were performed in a deformation‐DIA combined with X‐radiography, at seismic frequencies (∼0.003–0.1 Hz), high pressure and temperatures up to ∼80% of melting temperature. Significant dissipation (0.077 ≤ Q −1 (ω) ≤ 0.488) is observed along with frequency dependent softening of zinc's Young's modulus and an extremely small activation energy for creep (⩽7 kJ mol −1 ). In addition, during sinusoidal deformation the original microstructure is replaced by one with a reduced dislocation density and small, uniform, grain size. This combination of behavior collectively reflects a mode of deformation called “internal stress superplasticity”; this deformation mechanism is unique to anisotropic materials and activated by cyclic loading generating large internal stresses. Here we observe a new form of internal stress superplasticity, which we name as “elastic strain mismatch superplasticity.” In it the large stresses are caused by the compressional anisotropy. If this mechanism is also active inhcp‐iron and the Earth's inner‐core it will be a contributor to inner‐core observed seismic attenuation and constrain the maximum inner‐core grain‐size to ≲10 km.

Geochemistry & Geophysics↗
DOE OSTI2021

High-brightness self-seeded X-ray free-electron laser covering the 3.5 keV to 14.6 keV range

A self-seeded X-ray free-electron laser (XFEL) is a promising approach to realize bright, fully coherent free-electron laser (FEL) sources in the hard X-ray domain that have been a long-standing issue with longitudinal coherence remaining challenging. Additionally, at the Pohang Accelerator Laboratory XFEL, we have demonstrated a hard X-ray self-seeded XFEL with a peak brightness of 3.2 × 10 35 photons s –1 mm –2 mrad –2 0.1% bandwidth (BW) –1 at 9.7 keV. The bandwidth (0.19 eV) is about 1/70 times as wide (close to the Fourier transform limit) and the peak spectral brightness is 40 times higher than in self-amplified spontaneous emission (SASE), with substantial improvements in the stability of self-seeding and noticeably suppressed pedestal effects. We could reach an excellent self-seeding performance at a photon energy of 3.5 keV (lowest) and 14.6 keV (highest) with the same stability as the 9.7 keV self-seeding. The bandwidth of the 14.6 keV seeded FEL was 0.32 eV, and the peak brightness was 1.3 × 10 35 photons s –1 mm –2 mrad –2 0.1%BW –1 . We show that the use of seeded FEL pulses with higher reproducibility and a cleaner spectrum results in serial femtosecond crystallography data of superior quality compared with data collected using SASE mode.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Subcritical Neutron and Gamma Noise Measurements at the Seven Percent Critical Experiment (7uPCX)

As part of a collaborative international effort organized by Lawrence Livermore National Laboratory (LLNL), with key participants from L’Institut de radioprotection et de sûreté nucléaire (IRSN), Los Alamos National Laboratory (LANL), and Sandia National Laboratories (SNL), a series of high-multiplication subcritical neutron and gamma noise measurements were planned and executed. The primary aim of this research was to advance detector technology, assess the validity of gamma noise for subcriticality measurements, and nuclear criticality safety, focusing on collecting list-mode or time-series data from various reactor configurations with multiplication values ranging from 20 to 310. This comprehensive dataset enabled a detailed comparative analysis of multiple detector systems and the results of both neutron and gamma noise measurements. In this work we focus on experimentally comparing the results from neutron and gamma noise measurements. We note good agreement between estimations of the prompt neutron decay constant and demonstrate the effects of changing reactor geometry on the efficiency of the differing methods.

Criticality↗
DOE OSTI2023

Simulations with machine learning potentials identify the ion conduction mechanism mediating non-Arrhenius behavior in LGPS

Abstract Li 10 Ge(PS 6 ) 2 (LGPS) is a highly concentrated solid electrolyte, in which Coulombic repulsion between neighboring cations is hypothesized as the underlying reason for concerted ion hopping, a mechanism common among superionic conductors such as Li 7 La 3 Zr 2 O 12 (LLZO) and Li 1.3 Al 0.3 Ti 1.7 (PO 4 ) 3 (LATP). While first principles simulations using molecular dynamics (MD) provide insight into the Li + transport mechanism, historically, there has been a gap in the temperature ranges studied in simulations and experiments. Here, we used a neural network potential trained on density functional theory (DFT) simulations, to run up to 40-nanosecond long MD simulations at DFT-like accuracy to characterize the ion conduction mechanisms across a range of temperatures that includes previous simulations and experimental studies. We have confirmed a Li + sublattice phase transition in LGPS around 400 K, below which the ab -plane diffusivity D a b ∗ is drastically reduced. Concomitant with the sublattice phase transition near 400 K, there is less cation-cation (cross) correlation, as characterized by Haven ratios closer to 1, and the vibrations in the system are more harmonic at lower temperature. Intuitively, at high temperature, the collection of vibrational modes may be sufficient to drive concerted ion hops. However, near room temperature, the vibrational modes available may be insufficient to overcome electrostatic repulsion, thus resulting in less correlated ion motion and comparatively slower ion conduction. Such phenomena of a sublattice phase transition, below which concerted hopping plays a less significant role, may be extended to other highly concentrated solid electrolytes such as LLZO and LATP.

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

Infrared surface phonon nanospectroscopy of an interacting dielectric-particle–dielectric-substrate dimer using fast electrons

Refinements in energy monochromation and aberration correction in state-of-the-art scanning transmission electron microscopes has opened access to the far infrared regime for spectroscopic characterization at the nanoscale. At these low energies, the dielectric environment, such as a dielectric slab adjacent to the target specimen, may no longer play a passive role in the spectrum. Instead, the environment may itself host resonances that mix with those of the target and complicate interpretation of its spectral responses. This article explores a theoretical description of the coupling between the collective vibrational surface modes of a dielectric particle and dielectric slab of varying thickness for the purpose of elucidating the interacting phononic excitations in dielectric materials typical of inelastic electron scattering measurements in the infrared. Dynamical coordinates and a governing Hamiltonian are rigorously defined in the quasistatic limit to account for phonon mode mixing and forcing by an aloof electron probe, which travels along a grazing trajectory, parallel to the dielectric slab. As the spectral window of interrogation by fast electron probes has been extended down to thermal energies with unprecedented meV energy resolution, theoretical models like that presented herein are crucial for accurate interpretation of experimental data.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Quasisteady evolution of fast neutrino-flavor conversions

In astrophysical environments such as core-collapse supernovae (CCSNe) and binary neutron star mergers (BNSMs), neutrinos potentially experience substantial flavor mixing due to the refractive effects of neutrino self-interactions. Determining the survival probability of neutrinos in asymptotic states is paramount to incorporating flavor conversions’ effects in the theoretical modeling of CCSN and BNSM. Some phenomenological schemes have shown good performance in approximating asymptotic states of fast neutrino-flavor conversions (FFCs), known as one of the collective neutrino oscillation modes induced by neutrino self-interactions. However, a recent study showed that they would yield qualitatively different asymptotic states of FFC if the neutrino number is forced to evolve. It is not yet fully understood why the canonical phenomenological models fail to predict asymptotic states. In this paper, we perform detailed investigations through numerical simulations and then provide an intuitive explanation with a quasihomogeneous analysis. Based on the analysis, we propose a new phenomenological model, in which the quasisteady evolution of FFCs is analytically determined. The model also allows us to express the convolution term of spatial wave number as a concise form, which corresponds to useful information on analyses for the nonlinear feedback from small-scale flavor conversions to large-scale ones. Furthermore, our model yields excellent agreement with numerical simulations, which lends support to our interpretation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗