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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

A systematic program of cometary spectroscopy

Some early results of a systematic program of observing the spectroscopic behavior of comets as a function of heliocentric distance are presented. An ultraviolet sensitive microchannel plate intensifier spectrograph was used to record the 3000-5000A spectrum of comets brighter than magnitude 17 with a spectral resolution of 8 or 16A, followed by direct image for better interpretation of the spatial distribution of spectral features. Although the goals of the program require much more time and data, some interesting results from Comets Schwassmann-Wachmann, 1, Bradfield and Bowell were obtained.

Larson, S. M.↗
DOE OSTI2022

A robust deep learning workflow to predict multiphase flow behavior during geological C O 2 sequestration injection and Post-Injection periods

Simulation of multiphase flow in porous media is essential to manage the geologic CO 2 sequestration (GCS) process, and physics-based simulation approaches usually take prohibitively high computational cost due to the nonlinearity of the coupled physics. This paper contributes to the development and evaluation of a deep learning workflow that accurately and efficiently predicts the temporal-spatial evolution of pressure and CO 2 plumes during injection and post-injection periods of GCS operations. Based on a Fourier Neural Operator, the deep learning workflow takes input variables or features including rock properties, well operational controls and time steps, and predicts the state variables of pressure and CO 2 saturation. To further improve the predictive fidelity, separate deep learning models are trained for CO 2 injection and post-injection periods due to the difference in primary driving force of fluid flow and transport during these two phases. We also explore different combinations of features to predict the state variables. We use a realistic example of CO 2 injection and storage in a 3D heterogeneous saline aquifer, and apply the deep learning workflow that is trained from physics-based simulation data and emulate the physics process. Through this numerical experiment, we demonstrate that using two separate deep learning models to distinguish post-injection from injection period generates the most accurate prediction of pressure, and a single deep learning model of the whole GCS process including the cumulative injection volume of CO 2 as a deep learning feature, leads to the most accurate prediction of CO 2 saturation. For the post-injection period, it is key to use cumulative CO 2 injection volume to inform the deep learning models about the total carbon storage when predicting either pressure or saturation. The deep learning workflow not only provides high predictive fidelity across temporal and spatial scales, but also offers a speedup of 250 times compared to full physics reservoir simulation, and thus will be a significant predictive tool for engineers to manage the long-term process of GCS.

58 GEOSCIENCES↗
NASA NTRS2017

Vertical Profiles of Mars 1.27 Micrometer O2 Dayglow from MRO CRISM Limb Spectra: Seasonal/global Behaviors, Comparisons to LMDGCM Simulations, and a Global Definition for Mars Water Vapor Profiles

Since July of 2009, The Compact Reconnaissance Imaging Spectral Mapper (CRISM) onboard the Mars Re- connaissance Orbiter (MRO) has periodically obtained pole-to-pole observations (i.e., full MRO orbits) of limb scanned visible/near IR spectra (lambda= 0.4 - 4.0 micrometers, delta lambda approx. 10 nm- Murchie et al., 2007). These CRISM limb observations support the first seasonally and spatially extensive set of Mars 1.27 micometers O2 (1 delta(sub g)) day-glow profile retrievals (approx. 1100) over greater than or equal to 8-80 km altitudes. Their comparison to Laboratoire de Meteorologie Dynamique (LMD) global climate model (GCM) simulated O2 (1 delta(sub g)) volume emission rate (VER) profiles, as a function of altitude, latitude, and season (solar longitude, L(sub s), supports several key conclusions regarding Mars atmospheric water vapor (which is derived from O2 (1 delta(sub g)) emission rates), Mars O3, and the collisional de-excitation of O2 (1 delta(sub g)) in the Mars CO2 atmosphere. Current (Navarro et al., 2014) LMDGCM simulations of Mars atmospheric water vapor fall 2-3 times below CRISM derived water vapor abundances at 20-40 km altitudes over low-to-mid latitudes in northern spring (L(sub s) = 30-60 deg), and northern mid-to-high latitudes over northern summer (L(sub s) = 60-140 deg). In contrast, LMDGCM simulated water vapor is 2-5 times greater than CRISM derived values at all latitudes and seasons above 40 km, within the aphelion cloud belt (ACB), and over high-southern to mid-southern latitudes in southern summer (L(sub s) = 190-340 deg) at 15-35 km altitudes. Overall, the solstitial summer-to-winter hemisphere gradients in water vapor are reversed between the LMDGCM modeled versus the CRISM derived water vapor abundances above 10-30 km altitudes. LMDGCM-CRISM differences in water vapor profiles correlate with LMDGCM-CRISM differences in cloud mixing profiles; and likely reflect limitations in simulating cloud microphysics and radiative forcing, both of which restrict meridional transport of water from summer- to-winter hemispheres on Mars (Clancy et al., 1996; Montmessin et al., 2004; Steele et al., 2014; Navarro et al., 2014) and depend on uncertain cloud microphysical properties (Navarro et al., 2014). The derived low-to-mid latitude changes in Mars water vapor vertical distributions should reduce current model- data disagreements in column O3 and H2O2 abundances over low-to-mid latitudes (e.g., within the ACB; Lefevre et al., 2008; Encrenaz et al., 2015; Clancy et al., 2016). Lastly, the global/seasonal average com- parison of CRISM and LMDGCM O2 (1 delta(sub g)) VER below 20 km altitudes indicates a factor of approx. 3 times lower value (0.25 x 10(exp -20) cu cm sec(exp -1)) for the CO2 collisional de-excitation rate coefficient of O2 (1 delta(sub g)) than derived recently by Guslyakova et al. (2016).

Clancy, R. Todd↗
DOE OSTI2019

Evolution of Microstructure and Creep Behavior in an Fe-Ni-Cr-Nb-C Alloy during Service in Hydrocarbon Cracker Tubes

Heat resistant, cast austenitic Fe-Ni-Cr-Nb-C alloy tubes are used by the petrochemical industry to transport hydrocarbons at temperatures between 850 and 1050 °C. Exposure to carbon from the process stream and nitrogen from the air causes severe carburization and nitridation in the tube walls, which influences creep resistance and degrades their ductility. A better understanding of these processes would enable their service life to be extended. To this end, we report the results of an experimental and computational study of the changes in microstructure and creep behavior in a representative alloy during service. The microstructure of the fresh material is compared to that of 8- and 10-year-old tubes. The results confirm the presence of M{sub 23}C{sub 6}, M{sub 7}C{sub 3}, and M{sub 2}(CN) phases reported in prior studies, and also reveal the nucleation and growth of the carbo-nitride phase M{sub 6}(CN). We show that the spatial variations of carbide and nitride particle volume fractions in aged tubes can be predicted by a simple reaction–diffusion equation. In addition, the uniaxial compressive creep response of the fresh and aged tubes was obtained as functions of temperature and strain rate. The materials deform by power-law creep, with strain rate versus stress relation as ε-dot =Aσ{sup n}. Aging reduces the stress exponent from n = 8 in fresh tubes to n = 5 in aged tubes, and also reduces the pre-exponential coefficient A. Tests on model alloys with composition identical to that of the matrix combined with finite element simulations of creep in model microstructures reveal that Cr depletion is responsible for the change in stress exponent, while the change in A is caused by the increase in particle volume fraction. By combining the microstructure-scale simulations of creep with the predictions of the reaction–diffusion model of microstructure evolution, the creep behavior of tubes left in service beyond 10 years is estimated.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Probing the Nanoscale Excitonic Landscape and Confinement of Excitons in Gated Monolayer Semiconductors

Engineering and probing excitonic properties at the nanoscale remains a central challenge in quantum photonics and optoelectronics. While exciton confinement via electrical control and strain engineering has been demonstrated in 2D semiconductors, substantial nanoscale heterogeneity limits the scalability of 2D quantum photonic device architectures. Here, in this work, we use cathodoluminescence spectroscopy to probe the excitonic landscape of monolayer WS 2 under electrostatic gating. Exploiting the high spatial resolution of the converged electron beam, we resolve a homojunction arising between gated and ungated regions. Moreover, we reveal an exciton confinement channel arising from an unconventional doping mechanism driven by the interplay between the electron beam and the applied gate fields. These findings offer new insights into the optoelectronic behavior of monolayer semiconductors under the combined influence of electron-beam excitation and electrostatic gating. Our approach provides a pathway for exciton manipulation at the nanoscale and opens opportunities for controlling quantum-confined exciton transport in 2D materials.

2D materials↗
DOE OSTI2019

Unexpected Strong Thermally Induced Phonon Energy Shift for Mapping Local Temperature

Measuring temperature in nanoscale is crucial for the research and development of microelectronic devices. Plasmon resonance has been utilized to map local temperature gradient in metallic materials (Al) due to their large coefficients of thermal expansion. However, most semiconductors (including Si and SiC) possess much smaller coefficients of thermal expansion due to their strong covalent bonding in crystal structure, for which the plasmon-based temperature measurement becomes unreliable. Here, we report an unexpected strong, thermally induced phonon energy shift in SiC by spatially resolved vibrational spectroscopy in transmission electron microscopy with in situ heating, demonstrating that this shift can be applied as a useful tool for measuring nanoscale temperature. When a bulk phonon spectrum is used, the spatial resolution of vibrational spectroscopy can be as high as one nanometer. Molecular dynamics simulations reveal that lattice expansion only contributes a small fraction of phonon energy shift and that vibrant motions away from the bonds are predominate factors. In conclusion, this study gains deeper insight into the understanding of dynamic behaviors of the phonon and provides a new avenue to measure local temperature in nanodevices.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Application of a long short-term memory for deconvoluting conductance contributions at charged ferroelectric domain walls

Ferroelectric domain walls are promising quasi-2D structures that can be leveraged for miniaturization of electronics components and new mechanisms to control electronic signals at the nanoscale. Despite the significant progress in experiment and theory, however, most investigations on ferroelectric domain walls are still on a fundamental level, and reliable characterization of emergent transport phenomena remains a challenging task. Here, we apply a neural-network-based approach to regularize local I ( V )-spectroscopy measurements and improve the information extraction, using data recorded at charged domain walls in hexagonal (Er 0.99 ,Zr 0.01 )MnO 3 as an instructive example. Using a sparse long short-term memory autoencoder, we disentangle competing conductivity signals both spatially and as a function of voltage, facilitating a less biased, unconstrained and more accurate analysis compared to a standard evaluation of conductance maps. The neural-network-based analysis allows us to isolate extrinsic signals that relate to the tip-sample contact and separating them from the intrinsic transport behavior associated with the ferroelectric domain walls in (Er 0.99 ,Zr 0.01 )MnO 3 . Our work expands machine-learning-assisted scanning probe microscopy studies into the realm of local conductance measurements, improving the extraction of physical conduction mechanisms and separation of interfering current signals.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Electric Field Measurements at the Surface of a Piezoelectric Transformer for Plasma Jet Formation using the Plasma Research Facility at Sandia National Laboratory (Final Report)

The overall goal of this research is to understand how low-temperature non-equilibrium plasmas form directly off the surface of piezoelectric crystals. Specifically, this project aims to temporally and spatially resolve how the electric field evolves on and near the surface of a piezoelectric transformer (PT) at conditions that produce an atmospheric-pressure air plasma jet emanating from the corner of the PT. In this work, we used the Plasma Research Facility (PRF) at Sandia National Laboratory to conduct temporally- and spatially-resolved electric field induced second harmonic (E-FISH) measurements of the electric field at and near the surface of a piezoelectric transformer, providing a fundamental understanding of how piezoelectric crystals can be used for plasma generation. We carried out two Objectives: Objective 1 – The first objective was to measure the temporal and spatial evolution of the electric field along the surfaces approaching the corner of a rectangular PT just below conditions that lead to plasma jet formation. Such a measurement can be used to explain when and where the electric field peaks, leading to plasma formation; Objective 2 – The second objective was to measure the temporal and spatial evolution of the electric field along the surfaces approaching the corner of a rectangular PT just at conditions of plasma jet formation. This, in principle, gives a more accurate determination of how the electric field leads to plasma formation but is more difficult due to the relatively stochastic plasma jet behavior of a PT. This work was complemented by an award from the Sandia PRF, and we worked with Dr. Edward Barnat at the Sandia PRF to carry out these objectives.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Understanding the Drivers of Mobility during the COVID-19 Pandemic in Florida, USA Using a Machine Learning Approach

As of March 2021, the State of Florida, U.S.A. had accounted for approximately 6.67% of total COVID-19 (SARS-CoV-2 coronavirus disease) cases in the U.S. The main objective of this research is to analyze mobility patterns during a three month period in summer 2020, when COVID-19 case numbers were very high for three Florida counties, Miami-Dade, Broward, and Palm Beach counties. To investigate patterns, as well as drivers, related to changes in mobility across the tri-county region, a random forest regression model was built using sociodemographic, travel, and built environment factors, as well as COVID-19 positive case data. Mobility patterns declined in each county when new COVID-19 infections began to rise, beginning in mid-June 2020. While the mean number of bar and restaurant visits was lower overall due to closures, analysis showed that these visits remained a top factor that impacted mobility for all three counties, even with a rise in cases. Our modeling results suggest that there were mobility pattern differences between counties with respect to factors relating, for example, to race and ethnicity (different population groups factored differently in each county), as well as social distancing or travel-related factors (e.g., staying at home behaviors) over the two time periods prior to and after the spike of COVID-19 cases.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1979

Possible inverse cascade behavior for drift-wave turbulence

The turbulent spectral properties of the dynamical equation of Hasegawa and Mima (1978) governing the evolution of the electrostatic potential in drift-wave turbulence is investigated for two formulations of the problem: (1) as a nondissipative initial value problem, with the potential represented by a truncated Fourier series with large number of terms, and (2) as a dissipative problem with a small viscous dissipation at very short spatial scales, and a long wavelength forcing term at longer wavelengths. It is found that Hasegawa and Mima's prediction for the nondissipative, truncated initial value modal problem is accurate, but substantial differences exist for the forced dissipative case between computer results and analytical predictions based on a wave kinetic equation of Kadomtsev. Much better agreement is found with a simple dual-cascade model based on Kraichnan's generalization of Kolmogorov's cascade arguments.

Fyfe, D.↗
DOE OSTI2020

Carrier recombination parameters in diamond after surface boron implantation and annealing

In this study, an optical pump–probe technique was used to detect spatial distribution of carrier lifetimes across the thickness of a high-quality diamond device structure. Two samples with as-received and boron implanted surfaces were compared to assess the role of implantation and related processing on carrier recombination mechanisms. It was found that the two implanted surfaces show very different behaviors despite undergoing the same treatment. At one of the surfaces, carrier lifetimes remained relatively unchanged, indicating surface recombination rates in the 102–103 cm/s range. At the other surface, carrier lifetimes were almost a magnitude lower and correlated with the locally detected nitrogen vacancy defect that was attributed to the elevated concentration of residual nitrogen.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Spatiotemporal measurements of striations in a glow discharge’s positive column using laser-collisional induced fluorescence

Here we have observed the behavior of striations caused by ionization waves propagating in low-pressure helium DC discharges using the non-invasive laser-collision induced fluorescence (LCIF) diagnostic. To achieve this, we developed an analytic fit of collisional radiative model (CRM) predictions to interpret the LCIF data and recover quantitative two-dimensional spatial maps of the electron density, n e , and the ratios of LCIF emission states that can be correlated with T e with the use of accurate distribution functions at localized positions within striated helium discharges at 500 mTorr, 750 mTorr, and 1 Torr. To our knowledge, these are the first spatiotemporal, laser-based, experimental measurements of n e in DC striations. The n e and 447:588 ratio distributions align closely with striation theory. Constriction of the positive column appears to occur with decreased gas pressure, as shown by the radial n e distribution. We identify a transition from a slow ionization wave to a fast ionization wave between 750 mTorr and 1 Torr. These experiments validate our analytic fit of n e , allowing the implementation of an LCIF diagnostic in helium without the need to develop a CRM.

42 ENGINEERING↗
DOE OSTI2021

The Transportation Energy and Mobility Pathway Options (TEMPO) Model: Overview and Validation of V1.0 [Slides]

This presentation documents the approaches and methods used in the Transportation Energy & Mobility Pathway Options™ (TEMPO) model to evaluate passenger and freight demand for transportation and mobility services, project vehicle ownership and technology adoption decisions, and determine transport mode choices to derive scenarios of future energy use and emissions. TEMPO is an all-inclusive transportation demand model that covers the entire United States, with an implicit spatial resolution and an hourly temporal resolution that allows for generating time-resolved energy use profiles to assess multisectoral integration aspects. Key features of the TEMPO model include the ability to perform endogenous out-of-sample forecasting to extrapolate recent emerging trends and analyze impacts of disruptive technological breakthroughs and behavioral changes. TEMPO employs an innovative representation of passenger mobility demand stemming from household-level decisions that determine vehicle adoption, ownership, and use based on sociodemographics (e.g., income, household composition), technology attributes (e.g., travel cost, time), geography (e.g., urban, suburban, rural) and population-specific multiday mobility and travel requirements. This representation enables a more forward-looking perspective on the use of new mobility options and the adoption of alternative fuel vehicles, as well as a more accurate representation of their energy usage profiles than previous modeling approaches. A comparison with the U.S. Energy Information Administration’s Annual Energy Outlook showcases the ability of TEMPO to accurately replicate widely accepted projections by representing the key elements of the entire transportation sector at the appropriate level of resolution. TEMPO is intended to generate future scenarios of technology adoption, energy use, and emissions in the transportation sector to compare alternatives, inform decision makers, and assess integration with energy infrastructure and supply systems at an appropriate spatiotemporal resolution.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1986

Centroid tracking with area array detectors

A computer program (ALGEVAL) has been developed to simulate the position estimating behavior of a centroid estimator algorithm using data typical of optical point spread function data recorded by an area array detector. Typical results are shown of varying detector properties and optical point spread function types. The detector parameters currently available for study include read noise mean value, dark current mean value and spatial variation, charge transfer efficiency and point spread function location, saturation level, signal level and pixel size. The program is capable of calculating any order centroid using an array size from 2 x 2 to 15 x 15 pixels. The output of the program is either a performance map, histogram data or tabluar data. A number of further developments are recommended.

Glavich, T. A.↗
NASA NTRS1995

Triggering of longitudinal combustion instabilities in solid rocket motors: Nonlinear combustion response

Pulsed oscillations in solid rocket motors are investigated with emphasis on nonlinear combustion response. The study employs a wave equation governing the unsteady motions in a two-phase flow, and a solution technique based on spatial- and time-averaging. A wide class of combustion response functions is studied to second-order in fluctuation amplitude to determine if, when, and how triggered instabilities arise. Conditions for triggering are derived from analysis of limit cycles, and regions of triggering are found in parametric space. Based on the behavior of model dynamical systems, introduction of linear cross-coupling and quadratic self-coupling among the acoustic modes appears to be the manner in which the nonlinear combustion response produces triggering to a stable limit cycle. Regions of initial conditions corresponding to stable pulses were found, suggesting that stability depends on initial phase angle and harmonic content, as well as the composite amplitude, of the pulse.

Wicker, J. M.↗
NASA NTRS1991

Modeling the spatiotemporal organization of velocity storage in the vestibuloocular reflex by optokinetic studies

1. A generalized three-dimensional state space model of visual vestibular interaction was developed. Matrix and dynamical system operators associated with inputs from the semicircular canals, otolith velocity estimator, and the visual system have been incorporated into the model, which focus on their relationship to the velocity storage integrator. 2. A relationship was postulated between the eigenvalues and the direction of the eigenvectors of the system matrix and the orientation of the spatial vertical. It was assumed that the system matrix for a tilted position was a composition of two linear transformations of the system matrix for the upright position. One transformation modifies the eigenvalues of the system matrix, whereas another rotates the eigenvectors of the system matrix. The pitch and roll eigenvectors rotate with the head, whereas the yaw axis eigenvector remains approximately spatially invariant. 3. Based on the three-dimensional model, a computational procedure was formulated to identify the eigenvalues and eigenvectors of the system matrix with the use of a modification of the marquardt algorithm. With the use of data obtained from a monkey, it was shown that the three-dimensional behavior of velocity storage cannot be predicted solely in terms of its time constants, i.e., the inverse of its eigenvalues. With the use of the same eigenvalues the data could either be fit or not fit, depending on the eigenvector directions. Therefore, it is necessary to specify eigenvector directions when characterizing velocity storage in three dimensions. 4. Parameters found with the use of the Marquardt algorithm were incorporated into the model. Diagonal matrices in a head coordinate frame were introduced for coupling the visual system to the integrator and to the direct optokinetic pathway. Simulations of optokinetic nystagmus (OKN) and optokinetic after-nystagmus (OKAN) were run. The model predicted the behavior of yaw and pitch OKN and OKAN when the animal is upright. It also predicted the cross-coupling in the side down position. The trajectories in velocity space were also accurately simulated. 5. One of the predictions of the model is that when the stimulus direction is along an eigenvector, the trajectory in velocity space is a straight line. Using the "spectral width" of the residuals from a straight line sequence during OKAN, we developed a methodology to estimate how close the OKAN decay was to an eigenvector trajectory. 6. Thus we have developed a model-based approach for studying and interpreting the response characteristics of velocity storage in three dimensions.(ABSTRACT TRUNCATED AT 400 WORDS).

Non-NASA Center↗
NASA NTRSDate not supplied

The NASA Open Science Data Repository: Biomedical Data, Analysis Tools, and Informatic Collaborations

Increased biomedical risks and challenges associated with deep space missions require knowledge discovery, health countermeasures, and biomedical support capabilities. Maximally open-access and reusable data is needed by developers, scientists, and engineers to develop these systems. The NASA Open Science Data Repository (OSDR) is a maximally open access and FAIR database (ie., findable, accessible, interoperable, and reusable), and meets various scientific, technical, and operational needs. It offers users and submitters the ability to upload, download, search, share, analyze, cite, and visualize data across ‘omics, physiological, phenotypic, payload, hardware, behavioral, bioimaging, video, and environmental monitoring telemetry datasets. OSDR is an expanded database, based upon the successes of NASA GeneLab. OSDR has >460 studies with datasets covering model organisms to non-NASA human astronauts. There are ~12 datasets from the Inspiration 4 (I4) mission, spanning metagenomics, comprehensive metabolic panels, clonal hematopoiesis, spatial transcriptomics, proteomics, and cytokine panels. In the interest of data privacy, two I4 datasets with raw files relating to the epitranscriptome, and a new request feature is live in OSDR (with a backend review process established) developed from industry norms. OSDR is collecting and curating biomedical human data from a new sub-orbital research flight and is open to more space life science/biomedical submissions from the international and commercial sectors. OSDR also recently began a collaboration with the European Space Agency (ESA) to collect and curate >200 terabytes of human and model organism data. The OSDR submission portal is designed to ingest and curate ~25 ‘omics and ~50 physiological-phenotypic-imaging assay data types. Tools available for OSDR users include: 1) an Environmental Data Application to compare radiation, CO2, relative humidity, temperature, and other telemetry across missions and subjects, 2) the RadLab database, a collaboration between NASA, ESA, the German and Italian Space Agencies, and the Bulgarian Academy of Sciences, and 3) a Multi-study visualization tool which enables users to look across and combine ‘omics datasets. There are ~600 volunteer OSDR Analysis Working Group (AWG) members providing feedback on scientific data/metadata standards and collaborating to mine-reuse OSDR in research. OSDR/GeneLab has enabled ~60 publications reusing data as of October 2023.

space biology↗