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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Low-frequency magnetic fluctuation spectra in the magnetosheath and plasma depletion layer

Recent observations have delineated several different kinds of enhanced magnetic fluctuation spectra below the proton cyclotron frequency in the terrestrial magnetosheath. A model is presented that represents the variation of plasma parameters across the plasma depletion layer and into the magnetosheath proper. Using this model, we find that many of the properties of the observed spectra follow directly from the predictions of linear Vlasov instability theory. The observed progression of spectral features is a natural progression from mirror mode to merged (in frequency range) proton and He(2+) cyclotron modes to bifurcated (in frequency range) cyclotron modes as plasma convects earthward in the magnetosheath. The necessary change in dispersion surface topology from separated proton and He(2+) cyclotron surfaces at low beta to merged surfaces at high beta is described.

Denton, Richard E.↗
NASA NTRS1995

Testing Solar Flare Models with BATSE

We propose to use high-sensitivity Burst and Transient Source Experiment (BATSE) hard X-ray observations to test the thick-target and electric field acceleration models of solar flares. We will compare the predictions made by these models with hard X-ray spectral observations obtained with BATSE and simultaneous soft X-ray Ca XIX emission observed with the Yohkoh Bragg Crystal Spectrometer (BCS). The increased sensitivities of the BATSE and BCS (relative to previous detectors) permits a renewed study of the relationship between heating and dynamical motions during the crucial rise phase of flares. With these observations, we will: (1) investigate the ability of the thick-target model to explain the temporal evolution of hard X-ray emission relative to the soft X-ray blueshift during the earliest stages of the impulsive phase; and (2) search for evidence of electric-field acceleration as implied by temporal correlations between hard X-ray spectral breaks and the Ca XIX blueshift. The proposed study will utilize hard X-ray lightcurve and spectral measurements in the 10-100 keV energy range obtained with the BATSE Large Area Detectors (LAD). The DISCLA and CONT data will be the primary data products used in this analysis.

Zarro, Dominic M.↗
NASA NTRS1999

Measurement of the Plasma Density Using the Intensification of z-Mode Waves at the Electron Plasma Frequency

A new method is proposed for measuring the number density of a plasma using spectral measurements of plasma wave. The method is based on predictions that the ratio electric to magnetic fields and the electric intensity is significantly enhanced in a narrow frequency band without the electron plasma frequency for z-mode waves propagating at small angles to the back-ground magnetic field in cold relatively strongly magnetized plasmas. The method is applied to emissions observed in space over Earth's polar cap, allowing identification of the plasma frequency and the mode consistent with the data available. This method should be useful for other cold, strongly magnetized plasmas in space and in the laboratory.

Cairns, Iver H.↗
NASA NTRS2000

Onset of Convection Due to Surface Tension Variations in Multicomponent and Binary Fluid Layers

Under certain conditions, such as in thin liquid films or microgravity, surface tension variations along a free surface can induce convection. Convection onset due to surface tension variation is important to many terrestrial technological processes in addition to microgravity materials processing applications. Examples include coating, drying crystallization, solidification, liquid surface contamination, and containerless processing. In double-diffusive and multicomponent systems, the spatial variations of surface tension are associated with two or more stratifying agencies, respectively. For example, both temperature and species (concentration) gradients are associated with convection in the solidification of binary alloys or salt ponds. The direction of the two (or more) gradients has a profound effect on the nature of the flow at or slightly beyond the onset of convection. Our recent work at the NASA Lewis Research Center focused on characterizing surface-tension-induced onset of convection, often referred to as Marangoni-Benard convection. Exact solutions for the stationary neutral stability of multicomponent fluid layers with interfacial deformation were derived. These solutions also permit the computation of a boundary curve that separates the long and finite wavelength instabilities. Computing points along this boundary using the exact solution (when possible) is more efficient than the typical numerical approaches, such as finite difference or spectral methods. Above the curve, a long wavelength instability was predicted, suggesting that convection would occur principally through one large flow cell in the layer, whereas below the curve, finite wavelength instabilities occur which suggest multiple finite-sized circulation cells. For many common liquids with layer depths greater than 100 mm, finite wave instability is predicted under terrestrial conditions; however, with little exception, long wavelength instability is predicted in microgravity for the identical fluid systems.

Skarda, J. Raymond Lee↗
NASA NTRS2005

Laser Remote Sensing at NASA

NASA is developing active remote sensors to monitor the health of Planet Earth and for exploration of other planets. Development and deployment of these remote sensors can have a huge economic impact. Lasers for these active remote sensors span the spectral range from the ultraviolet to the mid infrared spectral regions. Development activities range from quantum mechanical modeling and prediction of new laser materials to the design, development, and demonstration be deployed in the field.

Barnes, Norman P.↗
NASA NTRS1979

A method for predicting the noise levels of coannular jets with inverted velocity profiles

A coannular jet was equated with a single stream equivalent jet with the same mass flow, energy, and thrust. The acoustic characteristics of the coannular jet were then related to the acoustic characteristics of the single jet. Forward flight effects were included by incorporating a forward exponent, a Doppler amplification factor, and a Strouhal frequency shift. Model test data, including 48 static cases and 22 wind tunnel cases, were used to evaluate the prediction method. For the static cases and the low forward velocity wind tunnel cases, the spectral mean square pressure correlation coefficients were generally greater than 90 percent, and the spectral sound pressure level standard deviation were generally less than 3 decibels. The correlation coefficient and the standard deviation were not affected by changes in equivalent jet velocity. Limitations of the prediction method are also presented.

Russell, J. W.↗
NASA NTRS2003

In Situ Raman Microscopy of a Single Graphite Microflake Electrode in a Li(+)-containing Electrolyte

Highly detailed Raman spectra from a single KS-44 graphite microflake electrode as a function of the applied potential have been collected in situ using a Raman microscope and a sealed spectroelectrochemical cell isolated from the laboratory environment. Correlations were found between the Raman spectral features and the various Li(+) intercalation stages while recording in real time Raman spectra during a linear potential scan from 0.7 down ca. 0.0V vs Li/Li(+) at a rate of 0.1 mV/s in a 1M LiClO4 solution in a 1:l (by volume) ethylene carbonate (EC):diethyl carbonate (DEC) mixture. In particular, clearly defined isosbestic points were observed for data collected in the potential range where the transition between dilute phase 1 and phase 4 of lithiated graphite is known to occur, i.e. 0.157 < E < 0.215 vs Li/Li(+). Statistical analysis of the spectroscopic data within this region made it possible to determine independently the fraction of each of the two phases present as a function of potential without relying on coulometric information and then predict, based on the proposed stoichiometry for the transition, a spectrally-derived voltammetric feature.

Shi, Qing-Fang↗
DOE OSTI2024

Correlative multimodal chemical imaging via machine learning

Machine learning approach can combine mass spectral imaging (MSI) techniques, one with low spatial resolution but intact molecular spectra and the other with nanometer spatial resolution but fragmented molecular signatures, to predict molecular MSI spectra with submicron spatial resolution. The machine learning approach can perform transformations on the spectral image data of the two MSI techniques to reduce dimensionality, and using a correlation technique, find relationships between the transformed spectral image data. The determined relationships can be used to generate MSI spectra of desired resolution.

Ovchinnikova, Olga S.↗
NASA NTRS1985

Remote sensing of wetland biomass and productivity for global biosystem research

The study of ecosystem function and the contributions of particular ecosystems to global elemental cycling will require data collection from orbital platforms. Presently used ground sampling techniques are not adequate for large area vegetation assessments. The research was directed toward an understanding of the relationship between spectral radiance and plant canopy biomass. Changes in the architecture of the canopy alters the observed spectral radiance patterns. The green components of a plant canopy interacts most strongly with incident radiation and usually reflect edaphic conditions as they relate to plant vigor. Plant biomass serves as an excellent integrator of the environmental factors encountered by the plant and can be used as an indicator for predicting soil redox, nutrient status, microbial activity, etc. The use was examined of TM spectral data to discriminate biomass classes and, in turn, to relate the biomass classes to the chemical status of the soil. Several preliminary studies have indicated that solar angle can be used to improve biomass predictions. This important observation also suggests that latitudinal extrapolation of the biomass predicting models will be possible if selected characteristics of the incident radiation are known.

Hardisky, M. A.↗
NASA NTRS1990

Flare heating and ionization of the low solar chromosphere. II - Observations of five solar flares

Two neutral Mg spectral lines formed in the temperature-minimum region and the low chromosphere, at 4571 and 5173 A, are used to quantify the changes in the atmospheric structure as a function of time during five solar flares. Eight proposed flare heating and ionization mechanisms and predictions of the effects of each on the temperature minimum region are discussed. Two Mg spectral observations made at the National Solar Observatory (Sacramento Peak), along with observations of hard and soft X-rays from the SMM and GOES satellites, are compared to the predictions of the eight proposed mechanisms. The initial effects in all five flares are consistent with backwarming by enhanced Balmer- and Paschen-continuum radiation originating in the upper chromosphere. Extended heating observed in two of the flares is most likely due to UV irradiation. In all cases heating by the dissipation of nonreversed electric currents, collisions with an electron or proton beam, irradiation by soft X-rays, and dissipation of Alfven waves are eliminated.

Metcalf, Thomas R.↗
DOE OSTI2020

Machine-Learning X-Ray Absorption Spectra to Quantitative Accuracy

Simulations of excited state properties, such as spectral functions, are often computationally expensive and therefore not suitable for high-throughput modeling. As a proof of principle, here we demonstrate that graph-based neural networks can be used to predict the x-ray absorption near-edge structure spectra of molecules to quantitative accuracy. Specifically, the predicted spectra reproduce nearly all prominent peaks, with 90% of the predicted peak locations within 1 eV of the ground truth. Besides its own utility in spectral analysis and structure inference, our method can be combined with structure search algorithms to enable high-throughput spectrum sampling of the vast material configuration space, which opens up new pathways to material design and discovery.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1990

Yield estimation of sugarcane based on agrometeorological-spectral models

This work has the objective to assess the performance of a yield estimation model for sugarcane (Succharum officinarum). The model uses orbital gathered spectral data along with yield estimated from an agrometeorological model. The test site includes the sugarcane plantations of the Barra Grande Plant located in Lencois Paulista municipality in Sao Paulo State. Production data of four crop years were analyzed. Yield data observed in the first crop year (1983/84) were regressed against spectral and agrometeorological data of that same year. This provided the model to predict the yield for the following crop year i.e., 1984/85. The model to predict the yield of subsequent years (up to 1987/88) were developed similarly, incorporating all previous years data. The yield estimations obtained from these models explained 69, 54, and 50 percent of the yield variation in the 1984/85, 1985/86, and 1986/87 crop years, respectively. The accuracy of yield estimations based on spectral data only (vegetation index model) and on agrometeorological data only (agrometeorological model) were also investigated.

Rudorff, Bernardo Friedrich Theodor↗
DOE OSTI2020

Pseudosmooth tribrid inflation in SU(5)

A realistic tribrid model of sneutrino inflation is constructed in an R-symmetric SU(5) grand unified theory (GUT). To avoid the monopole problem, a pseudosmooth inflationary trajectory is generated with the help of an additional Z 5 symmetry which is broken during and after inflation. The predictions of inflationary parameters are made at the central value of the scalar spectral index, n s =0.968. The largest possible value of the tensor to scalar ratio, r ≲ 0.0027, is obtained with sub-Planckian field values (≲m P ). A successful realization of reheating and leptogenesis is achieved by avoiding the gravitino problem with a reheat temperature as low as 10 6 GeV. The predicted range of the gauge symmetry breaking scale, 5 × 10 16 ≲ M/GeV ≲ 5 × 10 17 , turns out to be somewhat larger than the typical GUT scale. Finally, with additional vector-like families, a successful gauge coupling unification is achieved by avoiding the no-go theorem related to R-symmetric SU(5) GUT.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Enhancing Fluid Flow Pressure and Saturation Prediction Accuracy and Reducing Uncertainty with Committee Machine – Illinois Basin Decatur Project (IBDP) as a Case Study

Presentation at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24, 2024. Carbon capture and storage (CCS) is a way to play a critical role in the global transition to a low-emission economy. Current progress is hampered by a number of factors, among which the lack of risk-informed design tools and decision support frameworks is seen as a major roadblock. Significant interest exists in using artificial intelligence to accelerate CCS site feasibility studies, as well as to facilitate the permit application process. Existing works commonly train a single deep learning model. This work investigates the feasibility of using a conventional ensemble learning (committee machine) technique to further improve prediction accuracy. Ensemble-based algorithms generally improve over individual base learners in terms of robustness and accuracy. Deep ensembles, however, are time-consuming to create and train. A pragmatic question is whether small-sized ensembles may lead to prediction improvement. Here we evaluated the efficacy of an ensemble learning technique using the latent spectral model (LSM), an efficient deep neural operator algorithm, as base learners. Preliminary results, obtained using the Illinois Basin-Decatur Project (IBDP) carbon sequestration data/model, show that small-sized ensembles can improve prediction over the base learners, achieving prediction accuracy of ~1.6 psi root mean square error (RMSE) on pressure (relative the average reservoir pressure of 3150 psi), and less than 1.3% for saturation.

Sun, Alexander↗
DOE OSTI2024

Enhancing Fluid Flow Pressure and Saturation Prediction Accuracy and Reducing Uncertainty with Committee Machine – Illinois Basin Decatur Project (IBDP) as a Case Study

This is the conference paper accompanying an oral presentation at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24, 2024. Carbon capture and storage (CCS) is a way to play a critical role in the global transition to a low-emission economy. Current progress is hampered by a number of factors, among which the lack of risk-informed design tools and decision support frameworks is seen as a major roadblock. Significant interest exists in using artificial intelligence to accelerate CCS site feasibility studies, as well as to facilitate the permit application process. Existing works commonly train a single deep learning model. This work investigates the feasibility of using a conventional ensemble learning (committee machine) technique to further improve prediction accuracy. Ensemble-based algorithms generally improve over individual base learners in terms of robustness and accuracy. Deep ensembles, however, are time-consuming to create and train. A pragmatic question is whether small-sized ensembles may lead to prediction improvement. Here we evaluated the efficacy of an ensemble learning technique using the latent spectral model (LSM), an efficient deep neural operator algorithm, as base learners. Preliminary results, obtained using the Illinois Basin-Decatur Project (IBDP) carbon sequestration data/model, show that small-sized ensembles can improve prediction over the base learners, achieving prediction accuracy of ~1.6 psi root mean square error (RMSE) on pressure (relative the average reservoir pressure of 3150 psi), and less than 1.3% for saturation.

Sun, Alexander↗
DOE OSTI2022

Characterization and Optimization of a Spectral Window for Direct Gaseous Uranium Hexafluoride Enrichment Assay Using Laser-Induced Breakdown Spectroscopy

Through a systematic scanning of 235 U and 238 U emission lines between 280 nm and 745 nm, the optimal emission line for direct gaseous uranium hexafluoride (UF 6 ) enrichment assay using laser-induced breakdown spectroscopy (LIBS) was found. Screening for spectral features that are potentially useful for U isotopic analysis was gauged from the magnitude of the 235 U– 238 U isotopic shift and the signal-to-background ratio of the emission line through a parameter termed ΔSBR 235U–238U . The ΔSBR spectrum shows peaks at wavelength positions where there are strong lines with significant 235 U– 238 U shifts. The screening identified 13 spectral-window candidates, which were down selected based on their overall accuracy in predicting the 235 U enrichment of three UF 6 samples of natural (0.720 atom% 235 U) and low-enriched (4.675 atom% and 9.157 atom% 235 U) grades. The U(I) 646.498 nm emission line, with a determined 235 U– 238 U isotopic shift of -17.7 pm, was found to be the optimal spectral window for direct UF 6 enrichment assay. The root mean square error for enrichment assays on the three natural and low-enriched UF 6 samples, with each sample measured in six replicates, was 0.31% in absolute 235 U content. Each measurement comprised LIBS signals accumulated from 3000 laser shots. In conclusion, the analytical bias and precision were better than 0.5% and 0.3%, respectively, in absolute [ 235 U/( 235 U + 238 U)] ratios. Specific for the two low-enriched UF 6 samples, the relative standard deviations from six replicated measurements were around 2%.

47 OTHER INSTRUMENTATION↗
NASA NTRS1987

Multiple-Scale Turbulence Model

Turbulence in complex, recirculating flows not in spectral equilibrium. Report discusses mathematical fluid-flow model that includes multiple turbulence scales. Model developed for numerical prediction of confined, recirculating flows. Based on multiple-timescale concepts introduced in previous study, model takes into account turbulence in recirculating flow not in spectral equilibrium and different energy-transfer rates for eddies of different spatial scales treated separately.

Chen, C.↗