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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

ALMA Observations of Molecular Clouds in Three Group-centered Elliptical Galaxies:NGC 5846, NGC 4636, and NGC 5044

We present new ALMA CO(2–1) observations of two well-studied group-centered elliptical galaxies: NGC 4636 and NGC 5846. In addition, we include a revised analysis of Cycle 0 ALMA observations of the central galaxy in the NGC 5044 group. We find evidence that molecular gas is a common presence in bright group-centered galaxies (BGG). CO line widths are broader than Galactic molecular clouds, and using the reference Milky Way XCO, the total molecular mass ranges from 2.6 x 10(exp 5)M(☉) in NGC 4636 to 6.1 x 10(exp 7) M(☉) in NGC 5044. Complementary observations using the ALMA Compact Array do not exhibit any detection of a CO diffuse component at the sensitivity level achieved by current exposures. The origin of the detected molecular features is still uncertain, but these ALMA observations suggest that they are the end product of the hot gas cooling process and not the result of merger events. Some of the molecular clouds are associated with dust features as revealed by HST dust extinction maps, suggesting that these clouds formed from dust-enhanced cooling. The global nonlinear condensation may be triggered via the chaotic turbulent field or buoyant uplift. The large virial parameter of the molecular structures and correlation with the warm (10(exp 3)–10(exp 5) K)/hot (≥ 10(exp 6)) phase velocity dispersion provide evidence that they are unbound giant molecular associations drifting in the turbulent field, consistent with numerical predictions of the chaotic cold accretion process. Alternatively, the observed large CO line widths may be generated by molecular gas flowing out from cloud surfaces due to heating by the local hot gas atmosphere.

Pasquale Temi↗
NASA NTRS2017

Gaining the most utility from our geospace observational system: Network analysis of total electron content as a means to understand space weather to the point of prediction

We present the first network analysis of interplanetary magnetic field (IMF) clock angle dependent, high-latitude, hemispheric-specific total electron content (TEC) data. We examine network parameters to describe spatio-temporal correlations in the TEC data for January 2016. We find that significant network structure exists distinguishing the dayside and nightside ionosphere, and specific features in the high-latitudes (cusp/ionospheric footpoints of magnetospheric boundary layers, polar cap, and auroral zone), and that these features vary with IMF clock angle. In this brief summary paper, we provide proof of concept results and identify important areas of future research, providing a basis for the discussion of network analysis and machine learning approaches for space weather applications.

Malik, Nishant↗
NASA NTRS2021

The Effect of Composition on Microstructure and Properties for Additively Manufactured Superalloy 718

Additive manufacturing (AM) represents an exciting new approach towards producing metallic aerospace components. The ability to make complex geometries that were impossible to create using conventional manufacturing methods has sparked interest from the aerospace community, including NASA. The use of AM components for crucial and human rated space missions necessitates a full characterization of the differences between AM and more conventional wrought and cast processes. For this study, sixteen different commercially available superalloy 718 powder feedstocks were obtained, built using laser powder bed fusion(L-PBF), and microstructurally and mechanically analyzed. These measurements revealed a wide range of build qualities and microstructures despite all powder lots falling within the 718chemical specification and being processed using the same prescribed build and heat treatment parameters. Statistical analysis found a strong correlation of the amount of carbon in the powder with the final grain size and strength of the heat-treated 718 part. Ultimately, this study highlights the need of a refined superalloy 718 chemical specification for powder lots to be used in AM.

Timothy M Smith↗
NASA NTRS2022

Determining Latitudinal Extent of Energetic Electron Precipitation Using MEPED On-Board NOAA/POES

Energetic Electron Precipitation (EEP) from the plasma sheet and the radiation belts ionizes the polar lower thermosphere and mesosphere. EEP increases the production of NO x and HO x , which will catalytically destroy ozone, an important element of atmospheric dynamics. Therefore, measurement of the latitudinal extent of the precipitation boundaries is important in quantifying the atmospheric effects of the Sun-Earth interaction. This study uses measurements by the Medium Energy Proton Electron Detector (MEPED) of six NOAA/POES and EUMETSAT/METOP satellites from 2004 to 2014 to determine the latitudinal boundaries of EEP and their variability with geomagnetic activity and solar wind drivers. Variation of the boundaries for different electron energies and Magnetic Local Time (MLT) is studied. Regression analyses are applied to determine the best predictor variable based on solar wind parameters and geomagnetic indices. The highest correlation was found for the pressure-corrected Dst index when applying a linear regression model. A model of the equatorward EEP boundary is developed separately for three different energy channels, >43, >114, and >292 keV, and for 3 hour MLT sectors. For >43 keV EEP, 80% of the equatorward boundaries predicted by the model are within ±2.2° cgmlat. The model exhibits a solar cycle bias where it systematically exaggerates the equatorward movement of the EEP region during solar minimum. The highest accuracy of the model is found in periods dominated by corotating interaction regions/high speed solar wind streams. The result will be a key element for constructing a model of EEP variability to be applied in atmosphere climate models.

E. M. Babu↗
NASA NTRS2022

Validation and Interpretation of a Three-dimensional Configuration of a Magnetic Cloud Flux Rope

One strong magnetic cloud (MC)with a magnetic field magnitude reaching∼40 nT at 1 au during 2012 June16–17 is examined in association with a preexisting magnetic flux rope (MFR)identified on the Sun. The MC is characterized by a quasi-three-dimensional(3D) flux rope model based on in situ measurements from the Wind spacecraft. The contents of the magnetic flux and other parameters are quantified. In addition, a correlative study with the corresponding measurements of the same structure crossed by the Venus Express (VEX)spacecraft at a heliocentric distance of 0.7 au and with an angular separation of∼6°in longitude is performed to validate the MC modeling results. The spatial variation between the Wind and VEX magnetic field measurements is attributed to the3D configuration of the structure appearing as a knotted bundle of flux. A comparison of the magnetic flux contents between the MC and the preexisting MFR on the Sun indicates that the 3D reconnection process accompanying anM1.9flare may correspond to the magnetic reconnection between the field lines of the preexisting MFR rooted in the opposite polarity foot points. Such a process reduces the amount of the axial magnetic flux in the erupted flux rope, by approximately 50%, in this case.

Qiang Hu↗
DOE OSTI2023

Refining fast simulation using machine learning

At the CMS experiment, a growing reliance on the fast Monte Carlo application (FastSim) will accompany the high luminosity and detector granularity expected in Phase 2. The FastSim chain is roughly 10 times faster than the application based on the GEANT4 detector simulation and full reconstruction referred to as FullSim. However, this advantage comes at the price of decreased accuracy in some of the final analysis observables. In this contribution, a machine learning-based technique to refine those observables is presented. We employ a regression neural network trained with a sophisticated combination of multiple loss functions to provide post-hoc corrections to samples produced by the FastSim chain. The results show considerably improved agreement with the FullSim output and an improvement in correlations among output observables and external parameters. This technique is a promising replacement for existing correction factors, providing higher accuracy and thus contributing to the wider usage of FastSim.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Morphology and Evolution of 14Cr Powder During Mechanical Alloying for Oxide Dispersion Strengthened Ferritic Alloys

Oxide Dispersion Strengthened (ODS) Ferritic steel alloys are candidate materials for Generation IV and Fusion reactor concepts due to their high temperature material properties and their irradiation stability. However, these material properties are strongly influenced by nanocluster dispersion and grain size distributions, which are directly correlated to mechanical alloying methodologies and parameters. Current powder processing strategies use ball milling times greater than or equal to 40 hrs to achieve sufficient dispersoid, i.e Y{sub 2}O{sub 3}, incorporation within the metal matrix, but these time intensive milling cycles are neither practical nor economical. This work aims to investigate how the particle morphology evolves during mechanical alloying during the processing of a 14Cr ODS ferritic alloy, and if higher-intensity milling, shorter milling cycles can still achieve sufficient mixing of yttria in comparison to the dispersion and incorporation observed in conventional lower-intensity milling methodologies. Comparisons of milled particle size distributions are presented for low and high intensity milling cycles, while microscopy and high-temperature tensile data are presented for consolidated samples using higher-intensity milling parameters. (authors)

36 MATERIALS SCIENCE↗
DOE OSTI2025

Development of a Discrepancy Checker for the Digital Twin in a Supervisory Control System for a Thermal Energy Delivery System

Defined as a virtual representation of a physical object, process, or service, and used to support real-world decision-making, a digital twin (DT) can be utilized to combine classical and novel frameworks in sensors, state predictions, and multi-input/multi-output systems, and to enable optimal autonomous operations. However, a DT’s usefulness largely depends on its ability to adequately mirror the state of its physical counterpart, and this adequacy should be reflected by the level of uncertainty in the underlying simulation models when estimating and predicting quantities of interest (QOIs). Moreover, simulation models in a DT may involve multiple fidelities of representations—ranging from physics-based models to data-driven ones—but classical uncertainty quantification (UQ) methods struggle to handle numerous uncertainty sources, nor are they designed for real-time applications. This work presents a UQ-based discrepancy checking and diagnosis tool for a DT-based supervisory control system applied to a thermal energy delivery system (TEDS) at Idaho National Laboratory. The discrepancy checker was developed using metadata from an automated DT development process, and these metadata included different combinations of physical model forms and model parameters, training data and hyperparameters for surrogate models, and design parameters for supervisory control systems. Next, correlations between the uncertainty results and the metadata were established and then applied to the DT operations. The discrepancy checker evaluates the discrepancies between model predictions from virtual and sensor measurements and backtraces them to the corresponding major sources of uncertainty. The discrepancy checker showed reasonable performance in detecting discrepancies and diagnosing sources of uncertainty in testing scenarios.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

Positron annihilation characteristics in mesostructural silica films with various porosities

Porous silica films with various porosities were prepared via a sol-gel method using a nonionic amphiphilic triblock copolymer F127 as the structure-directing agent. Doppler broadening of positron annihilation radiation (DBAR) spectra were collected for the prepared films using a variable energy slow positron beam. Different linear relationships between positron annihilation line shape parameters S and W are found for the as-deposited films and calcined ones, indicative of the decomposition of the copolymer porogen in the as-deposited films upon calcination. This also reveals the variation of positron annihilation sites as a function of F127 loading or porosity. Strong correlations between positronium 3γ annihilation fraction, S parameter and porosity of the mesoporous silica films with isolated pores are obtained, which may provide a complementary method to determine closed porosities of mesoporous silica films by DBAR.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Spectral, Compositional, and Physical Properties of the Upper Murray Formation and Vera Rubin Ridge, Gale Crater, Mars

During 2018 and 2019, the Mars Science Laboratory Curiosity rover investigated the chemistry, morphology, and stratigraphy of Vera Rubin ridge (VRR). Using orbital data from the Compact Reconnaissance Imaging Spectrometer for Mars, scientists attributed the strong 860 nm signal associated with VRR to the presence of red crystalline hematite. However, Mastcam multispectral data and CheMin X-ray diffraction (XRD) measurements show that the depth of the 860 nm absorption is negatively correlated with the abundance of red crystalline hematite, suggesting that other mineralogical or physical parameters are also controlling the 860 nm absorption. Here, we examine Mastcam and ChemCam passive reflectance spectra from VRR and other locations to link the depth, position, and presence or absence of iron-related mineralogic absorption features to the XRD-derived rock mineralogy. Correlating CheMin mineralogy to spectral parameters showed that the ~860 nm absorption has a strong positive correlation with the abundance of ferric phyllosilicates. New laboratory reflectance measurements of powdered mineral mixtures can reproduce trends found in Gale crater. We hypothesize that variations in the 860 nm absorption feature in Mastcam and ChemCam observations of VRR materials are a result of three factors: (1) variations in ferric phyllosilicate abundance due to its ~800–1,000 nm absorption; (2) variations in clinopyroxene abundance because of its band maximum at ~860 nm; and (3) the presence of red crystalline hematite because of its absorption centered at 860 nm. We also show that relatively small changes in Ca-sulfate abundance is one potential cause of the erosional resistance and geomorphic expression of VRR.

58 GEOSCIENCES↗
DOE OSTI2024

Exchange–correlation entropy from the generalized thermal adiabatic connection

Warm dense matter is a highly energetic phase characterized by strong correlations, thermal effects, and quantum mechanical electrons. Thermal density functional theory is commonly used in simulations of this challenging phase, driving the development of temperature-dependent approximations to the exchange–correlation free energy. Approaches using the adiabatic connection formula are well known at zero temperature and have been recently leveraged at non-zero temperatures as well. In this work, a generalized thermal adiabatic connection (GTAC) formula is proposed, introducing a fictitious temperature parameter. This allows extraction of the exchange–correlation entropy S XC using simulated interaction strength scaling. Here, this procedure uses a Hellmann–Feynman approach to express the exchange–correlation entropy in terms of a temperature- and interaction strength-dependent exchange–correlation potential energy. In addition, analysis of S XC as a function of interaction strength suggests new forms for approximations, and GTAC itself offers a new framework for exploring both the exact and approximate interplay of temperature, density, and interaction strength across a wide range of conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2016

Assessing the Transferability of Statistical Predictive Models for Leaf Area Index Between Two Airborne Discrete Return LiDAR Sensor Designs Within Multiple Intensely Managed Loblolly Pine Forest Locations in the South-Eastern USA

Leaf area is an important forest structural variable which serves as the primary means of mass and energy exchange within vegetated ecosystems. The objective of the current study was to determine if leaf area index (LAI) could be estimated accurately and consistently in five intensively managed pine plantation forests using two multiple-return airborne LiDAR datasets. Field measurements of LAI were made using the LiCOR LAI2000 and LAI2200 instruments within 116 plots were established of varying size and within a variety of stand conditions (i.e. stand age, nutrient regime and stem density) in North Carolina and Virginia in 2008 and 2013. A number of common LiDAR return height and intensity distribution metrics were calculated (e.g. average return height), in addition to ten indices, with two additional variants, utilized in the surrounding literature which have been used to estimate LAI and fractional cover, were calculated from return heights and intensity, for each plot extent. Each of the indices was assessed for correlation with each other, and was used as independent variables in linear regression analysis with field LAI as the dependent variable. All LiDAR derived metrics were also entered into a forward stepwise linear regression. The results from each of the indices varied from an R2 of 0.33 (S.E. 0.87) to 0.89 (S.E. 0.36). Those indices calculated using ratios of all returns produced the strongest correlations, such as the Above and Below Ratio Index (ABRI) and Laser Penetration Index 1 (LPI1). The regression model produced from a combination of three metrics did not improve correlations greatly (R2 0.90; S.E. 0.35). The results indicate that LAI can be predicted over a range of intensively managed pine plantation forest environments accurately when using different LiDAR sensor designs. Those indices which incorporated counts of specific return numbers (e.g. first returns) or return intensity correlated poorly with field measurements. There were disparities between the number of different types of returns and intensity values when comparing the results from two LiDAR sensors, indicating that predictive models developed using such metrics are not transferable between datasets with different acquisition parameters. Each of the indices were significantly correlated with one another, with one exception (LAI proxy), in particular those indices calculated from all returns, which indicates similarities in information content for those indices. It can then be argued that LiDAR indices have reached a similar stage in development to those calculated from optical-spectral sensors, but which offer a number of advantages, such as the reduction or removal of saturation issues in areas of high biomass.

Sumnall, Matthew↗
DOE OSTI2015

Geometric phase and entanglement of Raman photon pairs in the presence of photonic band gap

Robustness of the geometric phase (GP) with respect to different noise effects is a basic condition for an effective quantum computation. Here, we propose a useful quantum system with real physical parameters by studying the GP of a pair of Stokes and anti-Stokes photons, involving Raman emission processes with and without photonic band gap (PBG) effect. We show that the properties of GP are very sensitive to the change of the Rabi frequency and time, exhibiting collapse phenomenon as the time becomes significantly large. The system allows us to obtain a state which remains with zero GP for longer times. This result plays a significant role to enhance the stabilization and control of the system dynamics. Finally, we investigate the nonlocal correlation (entanglement) between the pair photons by taking into account the effect of different parameters. An interesting correlation between the GP and entanglement is observed showing that the PBG stabilizes the fluctuations in the system and makes the entanglement more robust against the change of time and frequency.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1992

Sea surface velocities from visible and infrared multispectral atmospheric mapping sensor imagery

High resolution (100 m), sequential Multispectral Atmospheric Mapping Sensor (MAMS) images were used in a study to calculate advective surface velocities using the Maximum Cross Correlation (MCC) technique. Radiance and brightness temperature gradient magnitude images were formed from visible (0.48 microns) and infrared (11.12 microns) image pairs, respectively, of Chandeleur Sound, which is a shallow body of water northeast of the Mississippi delta, at 145546 GMT and 170701 GMT on 30 Mar. 1989. The gradient magnitude images enhanced the surface water feature boundaries, and a lower cutoff on the gradient magnitudes calculated allowed the undesirable sunglare and backscatter gradients in the visible images, and the water vapor absorption gradients in the infrared images, to be reduced in strength. Requiring high (greater than 0.4) maximum cross correlation coefficients and spatial coherence of the vector field aided in the selection of an optimal template size of 10 x 10 pixels (first image) and search limit of 20 pixels (second image) to use in the MCC technique. Use of these optimum input parameters to the MCC algorithm, and high correlation and spatial coherence filtering of the resulting velocity field from the MCC calculation yielded a clustered velocity distribution over the visible and infrared gradient images. The velocity field calculated from the visible gradient image pair agreed well with a subjective analysis of the motion, but the velocity field from the infrared gradient image pair did not. This was attributed to the changing shapes of the gradient features, their nonuniqueness, and large displacements relative to the mean distance between them. These problems implied a lower repeat time for the imagery was needed in order to improve the velocity field derived from gradient imagery. Suggestions are given for optimizing the repeat time of sequential imagery when using the MCC method for motion studies. Applying the MCC method to the infrared brightness temperature imagery yielded a velocity field which did agree with the subjective analysis of the motion and that derived from the visible gradient imagery. Differences between the visible and infrared derived velocities were 14.9 cm/s in speed and 56.7 degrees in direction. Both of these velocity fields also agreed well with the motion expected from considerations of the ocean bottom topography and wind and tidal forcing in the study area during the 2.175 hour time interval.

Pope, P. A.↗
DOE OSTI2015

Theory of the special Smith-Purcell radiation from a rectangular grating

The recently uncovered special Smith-Purcell radiation (S-SPR) from the rectangular grating has significantly higher intensity than the ordinary Smith-Purcell radiation (SPR). Its monochromaticity and directivity are also much better. Here we explored the mechanism of the S-SPR by applying the fundamental electromagnetic theory and simulations. We have confirmed that the S-SPR is exactly from the radiating eigen modes of the grating. Its frequency and direction are well correlated with the beam velocity and structure parameters, which indicates its promising applications in tunable wave generation and beam diagnostic.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Calibrating transition-metal energy levels and oxygen bands in first-principles calculations: Accurate prediction of redox potentials and charge transfer in lithium transition-metal oxides

Transition-metal (TM) oxides play an increasingly important role in technology today, including applications such as catalysis, solar energy harvesting, and energy storage. In many of these applications, the details of their electronic structure near the Fermi level are critically important for their properties. We propose a first-principles–based computational methodology for the accurate prediction of oxygen charge transfer in TM oxides and lithium TM (Li-TM) oxides. To obtain accurate electronic structures, the Heyd-Scuseria-Ernzerhof (HSE06) hybrid functional is adopted, and the amount of exact Hartree-Fock exchange (mixing parameter) is adjusted to reproduce reference band gaps. We show that the HSE06 functional with optimal mixing parameter yields not only improved electronic densities of states, but also better energetics (Li-intercalation voltages) for LiCoO 2 and LiNiO 2 as compared to the generalized gradient approximation (GGA), Hubbard U corrected GGA (GGA + U), and standard HSE06. We find that the optimal mixing parameters for TM oxides are system specific and correlate with the covalency (ionicity) of the TM species. The strong covalent (ionic) nature of TM-O bonding leads to lower (higher) optimal mixing parameters. We find that optimized HSE06 functionals predict stronger hybridization of the Co 3d and O 2p orbitals as compared to GGA, resulting in a greater contribution from oxygen states to charge compensation upon delithiation in LiCoO 2 . We also find that the band gaps of Li-TM oxides increase linearly with the mixing parameter, enabling the straightforward determination of optimal mixing parameters based on GGA (α = 0.0) and HSE06 (α = 0.25) calculations. Our results also show that G 0 W 0 @ GGA + U band gaps of TM oxides ( M O , M = Mn , Co , Ni ) and LiCoO 2 agree well with experimental references, suggesting that G 0 W 0 calculations can be used as a reference for the calibration of the mixing parameter in cases when no experimental band gap has been reported.

36 MATERIALS SCIENCE↗
NASA NTRS2018

Physics-Based Retrieval of Surface Roughness Parameters for Bare Soils from Combined Active-Passive Microwave Signatures

In the past the effect of soil roughness was often considered secondary within the determination of soil moisture from remote sensing data. Several studies showed that accurate determination of soil roughness leads to an improved estimation of soil moisture. Two default parameters to describe the surface roughness are the standard deviation of the surface height variation 𝑠 and the surface correlation length 𝑙 with its corresponding autocorrelation function. Both parameters (𝑠,𝑙) affect the emissivity measured by radiometers as well as the backscattering observed by radars. In this study, we develop a physics-based approach to retrieve 𝑠 and 𝑙 by combining both microwave signals based on active-passive microwave covariation. To test the approach, containing a forward model and a retrieval algorithm, we used active/passive microwave data measured with the ComRAD truck-based SMAP simulator at L-band. Results and validations with corresponding field measurements on ground show that 𝑠 and 𝑙 can be estimated simultaneously when using this approach. The physics-based retrieval algorithm works robustly for two investigated test fields having an RMS-Error of 0.68 cm and 0.69 cm between the microwave-based and field-measured 𝑠-values, and of 3.13 cm and 3.04 cm for 𝑙-values. The first validation of the results reveals that the influence of the autocorrelation function, needed within the retrieval, is distinct.

correlation length↗
DOE OSTI2024

Cross Correlating Cosmological Probes for LSST & CMB-S4

The upcoming years will be populated with state-of-the-art Stage-IV cosmological surveys. This paper forecasts the cosmological information we expect to constrain using probes from the Rubin Observatory Legacy Survey of Space and Time (LSST) and CMB-S4. We explore the effectiveness of different large-scale-structure probes, including the power spectra of galaxy weak lensing, galaxy position, Cosmic Microwave Background (CMB) lensing, and their cross-correlations. We use correlated lognormal simulations with the expected redshift distributions, galaxy number densities, and noise levels of the LSST survey. For CMB weak lensing, we use CMB-S4 lensing simulations with anticipated noise levels to obtain the expected error bars of each probe. We investigate the constraining power of the cosmological parameters for the individual probes and their combinations in an idealized scenario. We do not take into account astrophysical and observational parameters such as galaxy bias variations and photometric redshift un- certainties. Overall, we find the auto-correlated probes hold stronger constraints on cosmological parameters than the cross-correlated probes due to kernel differences. However, the cross-correlation of galaxy clustering and CMB lensing is very comparable to the auto-correlation of galaxy clustering with only an 8% stronger constraint in S8. It will be important for future surveys to use these auto and cross probes in combination due to the different astrophysical and systematic effects involved in CMB and late-time galaxy data. When systematics are added to this analysis, the cross probes will serve as a check for systematic biases in individual probes. In addition, we find a significant increase in constraint using all four probes in combination. This can be illustrated by the increase in constraint of S8 by 93.2% comparing galaxy clustering auto-correlation to a combination of all probes. Our study is a first step toward forecasting the high-precision cosmological constraints we expect to obtain using the next generation of large-scale structure probes.

Gibbins, Grace↗

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