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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
DOE OSTI2025

Efficient lattice QCD computation of radiative-leptonic-decay form factors at multiple positive and negative photon virtualities

In previous work [D. Giusti, Methods for high-precision determinations of radiative-leptonic decay form factors using lattice QCD, Phys. Rev. D 107, 074507 (2023)], we showed that form factors for radiative leptonic decays of pseudoscalar mesons can be determined efficiently and with high precision from lattice QCD using the “three-dimensional (3D) method,” in which three-point functions are computed for all values of the current insertion time and the time integral is performed at the data-analysis stage. Here, we demonstrate another benefit of the 3D method: the form factors can be extracted for any number of nonzero photon virtualities from the same three-point functions at no extra cost. We present results for the $D_s → ℓνγ*$ vector form factor as a function of photon energy and photon virtuality, for both positive and negative virtuality, for a single ensemble with 340 MeV pion mass and 0.11 fm lattice spacing. In our analysis, we separately consider the two different time orderings and the different quark flavors in the electromagnetic current. We discuss in detail the behavior of the unwanted exponentials contributing to the three-point functions, as well as the choice of fit models and fit ranges used to remove them for various values of the virtuality. While positive photon virtuality is relevant for decays to multiple charged leptons, negative photon virtuality suppresses soft contributions and is of interest in QCD-factorization studies of the form factors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Constitutive model fingerprints in medium-amplitude oscillatory shear

Rheologists have expectations for signatures of linear viscoelastic properties, such as shapes of G'(ω) and G"(ω). Medium amplitude (or asymptotically-nonlinear) oscillatory shear (MAOS) provides additional nonlinear rheological information with low dimensional, well-defined material functions. Here, we develop expectations of signatures (or fingerprints) for the four asymptotically-nonlinear material functions associated with MAOS, [e 1 ](ω), [e 3 ](ω), [v 1 ](ω), [v 3 ](ω). Although the linear fingerprints may be identical for different models, the asymptotically-nonlinear fingerprints may be different in magnitude, frequency-scaling, curve shapes, and sign changes. To perform the analysis, we collect/translate a library of available analytical strain-controlled MAOS fingerprints for seven different constitutive models. Using this library, we identify general trends and highlight key differences of asymptotic-nonlinear viscoelasticity. Asymptotic nonlinearities for all models considered here obey the terminal regime inter-relations and frequency scaling predicted by Bharadwaj and Ewoldt. Unlike the positive linear viscoelastic measures, at least one of the four asymptotic nonlinearities changes signs with Deborah number (De). Following sign interpretations of Ewoldt and Bharadwaj, we show that nonlinearities tend to be driven by strain-rates at small De, and by strains at large De, a trend observed for nearly all the constitutive models studied here, the exception being the model for dilute rigid dumbbell suspensions. Some constitutive models exhibit multiple sign changes at intermediate De and there may be no universal behavior of asymptotically-nonlinear fingerprints in this regime. Therefore, frequency-dependent signatures can be material-specific. Furthermore, this will allow inverse problems to infer structure, select models, and fit model parameters using asymptotically-nonlinear signatures. To illustrate this aspect, we demonstrate a fingerprint matching exercise with experimental measurements on a transiently cross-linked hydrogel system. We find that currently available model fingerprints can match the qualitative magnitudes and frequency dependence, but not the signs of the experimental transient network response.

42 ENGINEERING↗
DOE OSTI2016

DETECTION OF SOLAR-LIKE OSCILLATIONS, OBSERVATIONAL CONSTRAINTS, AND STELLAR MODELS FOR θ CYG, THE BRIGHTEST STAR OBSERVED BY THE KEPLER MISSION

θ Cygni is an F3 spectral type magnitude V = 4.48 main-sequence star that was the brightest star observed by the original Kepler spacecraft mission. Short-cadence (58.8 s) photometric data using a custom aperture were first obtained during Quarter 6 (2010 June–September) and subsequently in Quarters 8 and 12–17. We present analyses of solar-like oscillations based on Q6 and Q8 data, identifying angular degree l = 0, 1, and 2 modes with frequencies of 1000–2700 μ Hz, a large frequency separation of 83.9 ± 0.4 μ Hz, and maximum oscillation amplitude at frequency ν {sub max} = 1829 ± 54 μ Hz. We also present analyses of new ground-based spectroscopic observations, which, combined with interferometric angular diameter measurements, give T {sub eff} = 6697 ± 78 K, radius 1.49 ± 0.03 R {sub ⊙}, [Fe/H] = -0.02 ± 0.06 dex, and log g = 4.23 ± 0.03. We calculate stellar models matching these constraints using the Yale Rotating Evolution Code and the Asteroseismic Modeling Portal. The best-fit models have masses of 1.35–1.39 M {sub ⊙} and ages of 1.0–1.6 Gyr. θ Cyg’s T {sub eff} and log g place it cooler than the red edge of the γ Doradus instability region established from pre- Kepler ground-based observations, but just at the red edge derived from pulsation modeling. The pulsation models show γ Dor gravity modes driven by the convective blocking mechanism, with frequencies of 1–3 cycles per day (11 to 33 μ Hz). However, gravity modes were not seen in Kepler data; one signal at 1.776 cycles per day (20.56 μ Hz) may be attributable to a faint, possibly background, binary.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

SIMPLIFIED PREDICTIVE MODELS FOR CO₂ SEQUESTRATION PERFORMANCE ASSESSMENT RESEARCH TOPICAL REPORT ON TASK #3 STATISTICAL LEARNING BASED MODELS

We compare two approaches for building a statistical proxy model (metamodel) for CO₂ geologic sequestration from the results of full-physics compositional simulations. The first approach involves a classical Box-Behnken or Augmented Pairs experimental design with a quadratic polynomial response surface. The second approach used a space-filling maxmin Latin Hypercube sampling or maximum entropy design with the choice of five different meta-modeling techniques: quadratic polynomial, kriging with constant and quadratic trend terms, multivariate adaptive regression spline (MARS) and additivity and variance stabilization (AVAS). Simulations results for CO₂ injection into a reservoir-caprock system with 9 design variables (and 97 samples) were used to generate the data for developing the proxy models. The fitted models were validated with using an independent data set and a cross-validation approach for three different performance metrics: total storage efficiency, CO₂ plume radius and average reservoir pressure. The Box-Behnken–quadratic polynomial metamodel performed the best, followed closely by the maximin LHS–kriging metamodel.

Mishra, Srikanta↗
DOE OSTI2022

Semi-analytic spectral fitting: simultaneously modelling the mass accumulation and chemical evolution in MaNGA spiral galaxies

We develop a novel semi-analytic spectral fitting approach to quantify the star formation histories (SFHs) and chemical enrichment histories (ChEHs) of individual galaxies. We construct simple yet general chemical evolution models that account for gas inflow and outflow processes as well as star formation, to investigate the evolution of merger-free star-forming systems. These models are fitted directly to galaxies’ absorption-line spectra, while their emission lines are used to constrain current gas phase metallicity and star formation rate. We apply this method to spiral galaxies selected from the SDSS-IV Mapping Nearby Galaxies at Apache Point Observatory survey. By fitting the co-added absorption-line spectra for each galaxy, and using the emission-line constraints on present-day metallicity and star formation, we reconstruct both the SFHs and the ChEHs for all objects in the sample. We can use these reconstructions to obtain archaeological measures of derived correlations such as the mass–metallicity relation at any redshift, which compare favourably with direct observations. We find that both the SFHs and ChEHs have strong mass dependence: massive galaxies accumulate their stellar masses and become enriched earlier. This mass dependence causes the observed flattening of the mass–metallicity relation at lower redshifts. The model also reproduces the observed gas-to-stellar mass ratio and its mass dependence. Moreover, we are able to determine that more massive galaxies have earlier gas infall times and shorter infall time-scales, and that the early chemical enrichment of low-mass galaxies is suppressed by strong outflows, while outflows are not very significant in massive galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Statistical Analysis of the Phase 3 Emissions Data Collected in the EPAct/V2/E89 Program: January 7, 2010 - July 6, 2012

Phase 3 of the EPAct/V2/E-89 Program investigated the effects of 27 program fuels and 15 program vehicles on exhaust emissions and fuel economy. All vehicles were tested over the California Unified Driving Cycle (LA-92) at 75 degrees F. The program fuels differed on T50, T90, ethanol, Reid vapor pressure, and aromatics. The vehicles tested were new, low-mileage 2008 model year Tier 2 vehicles. A total of 956 test runs were made. Comprehensive statistical modeling and analyses were conducted on methane, carbon dioxide, carbon monoxide, fuel economy, non-methane hydrocarbons, non-methane organic gases, oxides of nitrogen, particulate matter, and total hydrocarbons. In general, model fits determined that emissions and fuel economy were complicated by functions of the five fuel parameters. An extensive evaluation of alternative model fits produced a number of competing model fits. Many of these alternative fits produce similar estimates of mean emissions for the 27 program fuels but should be carefully evaluated for use with emerging fuels with combinations of fuel parameters not included here. The program includes detailed databases on each of the 27 program fuels on each of the 15 vehicles and on each of the vehicles on each of the program fuels.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Theoretical Systematics of Future Baryon Acoustic Oscillation Surveys

Future Baryon Acoustic Oscillation surveys aim at observing galaxy clustering over a wide range of redshift and galaxy populations at great precision, reaching tenths of a percent, in order to detect any deviation of dark energy from the lambda cold dark matter ( ΛCDM ) model. We utilize a set of paired quasi- N -body FastPM simulations that were designed to mitigate the sample variance effect on the BAO feature and evaluated the BAO systematics as precisely as ~0.01 percent. We report anisotropic BAO scale shifts before and after density field reconstruction in the presence of redshift-space distortions over a wide range of redshift, galaxy/halo biases, and shot noise levels. We test different reconstruction schemes and different smoothing filter scales, and introduce physically motivated BAO fitting models. For the first time, we derive a Galilean-invariant infrared resummed model for halos in real and redshift space. We test these models from the perspective of robust BAO measurements and non-BAO information such as growth rate and non-linear bias. We find that pre-reconstruction BAO scale has moderate fitting-model dependence at the level of 0.1–0.2 percent for matter while the dependence is substantially reduced to less than 0.07 percent for halos. We find that post-reconstruction BAO shifts are generally reduced to below 0.1 percent in the presence of galaxy/halo bias and show much smaller fitting model dependence. Different reconstruction conventions can potentially make a much larger difference on the line-of-sight BAO scale, upto 0.3 percent. Furthermore, the precision (error) of the BAO measurements is quite consistent regardless of the choice of the fitting model or reconstruction convention.

(cosmology:) cosmological parameters↗
DOE OSTI2021

Performance characterization of nanofiltration, reverse osmosis, and ion exchange technologies for acetic acid separation

A major obstacle to widespread implementation of bio-based fuels and chemicals is the lack of efficient and costeffective separation methods. To purify acetic acid produced by biochemical conversion of biomass via anaerobic digestion, this work employs two commonly used separation technologies: (1) ion-exchange (IX) resin and (2) pressure-driven membranes. This study tested five commercially available strong- and weak-base anion-exchange resins and five commercially available nanofiltration (NF) and reverse osmosis (RO) membranes. The pH of the feed solution significantly affected adsorption capacity. At pH 6.3, a strong-base IX resin (IRN-78) performed best (95.1% acetate removal). With strong-base IX resins, the Langmuir isotherm model fit well, whereas for weak-base IX resins, the Freundlich isotherm provided a better fit. A pseudo-second-order kinetic model fit well for both IRN-78 and IRA-67. Regarding membrane separation, RO (BW30XFR membrane) achieved the highest rejection (98.6% acetate rejection), whereas an NF membrane (NF*) achieved the best combination of permeate flux (105 L/(h∙m 2 )) and rejection (83.1% acetate rejection). For membrane performance, the experimental data were fit using the solution diffusion model. Increased pH in the feed solution lowered permeate flux but increased acetic acid rejection. Finally, then the acetic acid concentration in the feed solution increased, both permeate flux and acetic acid rejection decreased for membrane NF*.

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

Fourier domain dynamic correction method for complex optical fringes in laser spectrometers

A method is provided for Fourier domain dynamic correction of optical fringes in a laser spectrometer. The method includes Fourier transforming a background spectrum contaminated with the optical fringes to obtain baseline fringes in a frequency domain. The method includes partitioning the baseline fringes in the frequency domain to obtain partitioned baseline fringes. The method includes reconstructing the partitioned baseline fringes as separate spectra. The method includes constructing a fitting model to approximate the background spectrum by assigning a first and a second free parameter to each of partitioned baseline fringe components to respectively allow for drift and amplitude adjustments during a fitting of the fitting model. The method includes applying the fitting model to a newly acquired spectrum to provide an interpretation of the newly acquired spectrum having a reduced influence of spectral contamination on concentration retrieval.

Teng, Cheyenne↗
DOE OSTI2014

Electrically detected magnetic resonance modeling and fitting: An equivalent circuit approach

The physics of electrically detected magnetic resonance (EDMR) quadrature spectra is investigated. An equivalent circuit model is proposed in order to retrieve crucial information in a variety of different situations. This model allows the discrimination and determination of spectroscopic parameters associated to distinct resonant spin lines responsible for the total signal. The model considers not just the electrical response of the sample but also features of the measuring circuit and their influence on the resulting spectral lines. As a consequence, from our model, it is possible to separate different regimes, which depend basically on the modulation frequency and the RC constant of the circuit. In what is called the high frequency regime, it is shown that the sign of the signal can be determined. Recent EDMR spectra from Alq{sub 3} based organic light emitting diodes, as well as from a-Si:H reported in the literature, were successfully fitted by the model. Accurate values of g-factor and linewidth of the resonant lines were obtained.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Quantitative analysis of Raman spectral parameters for carbon fibers: practical considerations and connection to mechanical properties

Although the literature on the Raman spectra of carbon fibers is vast, no consistent, robust predictive relationship between mechanical properties of carbon fibers and spectral parameters exists. This shortcoming is due to the use of numerous fitting functions to evaluate Raman spectra of carbon fibers and the inconsistencies in establishing the best fitting models in a statistically robust fashion. To address this gap, we present a comprehensive work on the Raman spectra of carbon fibers that combines a vast library of experimental data with a robust numerical analysis and a statistical evaluation of a wide range of suggested fitting models. This manuscript begins with a brief review of the commonly applied fitting models. Then, the Raman spectra of 32 commercially available polyacrylonitrile-based carbon fibers collected at excitation wavelengths 532, 633, and 785 nm are presented and the best fit for all fibers is evaluated based on several statistical criteria in conjunction with numerical calculations and physical arguments. The results suggest that high-performance fibers must be fit with at least five peaks, whereas high-tensile modulus fibers are best fit with at least six distinct peaks. Finally, we employ simultaneous fitting of the Raman spectra of specific fibers and wavelengths and demonstrate that strong correlations exist between mechanical properties and the D1 peak position and shape across the range of evaluated mechanical properties. Finally, we suggest straightforward improvements in fitting analysis procedures that can be implemented to increase coherency in the understanding of the underlying carbon fiber microstructure intuited from Raman spectroscopy.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Deriving Stable Peak Models to Fit Complex XPS Data From Cu Contaminated Pt Electrocatalysts

X-ray Photoelectron Spectroscopy spectra peak models, designed to partition photoemission signals emanating from different elements or chemical states within an atom, are fitted to data limited to an energy interval over which inelastically scattered photoemission signal can be estimated. While the choice of background approximation and line shapes of components to the peak model requires careful consideration, the energy interval used to define the data to which the peak model is optimized has a significant impact on the final peak model. The relationship between the background intensity and data intensity at the start and end of the energy interval dictates the line shapes used in the peak model. In this work, we devise a method to peak fit a complex overlapping Cu 3p and Pt 4f XPS peak structure to perform the elemental quantification. We first use an Al 2s peak to illustrate how background curves approach data at the limits of the energy interval over which the background is defined, influencing the analysis of XPS spectra. Next, we demonstrate the nature of interactions between specific line shapes (Voigt and pseudo-Voigt profiles) suitable for photoemission peaks and a specific background curve (Shirley) and a peak model is presented that includes components to the peak model that accommodates background intensity during fitting of the peak model to data. The peak model allowed for quantification of the contributions of Pt 4f peaks emanating from the substrate that exhibits strong asymmetry in the presence of the inhomogeneously distributed Cu species, mostly of Lorentzian character.

XPS↗
DOE OSTI2021

Tensile Property and Lifetime Prediction for Low-Temperature Aged Uranium-Niobium Alloys

Thermal aging models and lifetime predictions for uranium-niobium (U-Nb) alloys were created using an approach similar to those previously employed. Lifetime estimates for generic U-6Nb components were thus updated; the reported value being 800 years. This update represents a small change in lifetime vs. that of the 2012 assessment (540 years). This lifetime estimate emerged from consideration of several model fits specific to the aging datasets and properties chosen. Aging was quantified using quasi-static tensile properties measured on specimens artificially aged for up to 10 years. The major change relative to the most recent 2012 LANL assessment was that a more comprehensive body of U-Nb literature data was mined, in addition to being augmented by the latest LANL and UK AWE data. The tensile data compilation was published separately (LANL report LA-14493, December 2016). Recognizing the chemical banding of industrially produced U-6Nb, models were developed for the mid-range (6 wt.%) and extrema (4 and 8 wt.%) compositions. Lifetime estimates were calculated for all three alloy classes (4, 6, 8 wt.% nominal) and two measures of total tensile elongation (TE) to failure, namely TE-ext. — extensometer method, and TE-NCD — normalized crosshead displacement method. The conservative assumption was made that whichever composition (4, 6, or 8 wt.% Nb) and property (TE-ext or TE-NCD) was the first to cross the ductility failure threshold would limit the lifetime of the entire component. Tensile strength properties did not figure into the lifetime predictions, but could be useful as age-sensitive diagnostics and were also modeled. Of these, only first yield strength is expected to show a change at 40°C aging vs. time = 0 over the ~100-year timespan of engineering interest. Second yield strength evolves more slowly, and ultimate tensile strength slower still. Among all the models, the apparent activation energies for aging were mostly in the narrow 29– 37 kcal/mol range, which is close to that for diffusion of Nb in gamma-uranium. This agreement may be coincidental. The data from recent long-term aging studies substantially improved the model fit quality and robustness of the lifetimes. Appendices document sensitivity studies of the model fits and lifetimes with respect to using more limited datasets. These results highlight the limitations of relying solely on data from scattered literature studies and smaller datasets more generally.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Effects of random forest modeling decisions on biogeochemical time series predictions

Abstract Random forests (RF) are an increasingly popular machine learning approach used to model biogeochemical processes in the Earth system. While RF models are robust to many assumptions that complicate deterministic models, there are several important parameterization decisions for appropriate use and optimal model fit. We explored the role that parameter decisions, including training/testing data splitting strategies, variable selection, and hyperparameters play on RF goodness‐of‐fit by constructing models using 1296 unique parameter combinations to predict concentrations of nitrate, a key nutrient for biogeochemical cycling in aquatic ecosystems. Models were built on long‐term, publicly available water quality and meteorology time series collected by the National Estuarine Research Reserve monitoring network for two contrasting ecosystems representing freshwater and brackish estuaries. We found that accounting for temporal dependence when splitting data into training and testing subsets was key for avoiding over‐estimation of model predictive power. In addition, variable selection, the ratio of training to testing data, and to a lesser degree, variables per split and number of trees, were significant parameters for optimizing RF goodness‐of‐fit. We also explored how model parameter decisions influenced interpretation of the relative importance of predictors to the model, and model predictor‐dependent variable relationships, with results suggesting that both data structure and model parameterization influence these factors. Because much of the current RF literature is written for the computational and statistical science communities, the primary goal of this study is to provide guidelines for aquatic scientists new to machine learning to apply RF techniques appropriately to aquatic biogeochemical datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Broadband distortion modeling in Lyman-α forest BAO fitting

Recently, the Lyman-α absorption observed in the spectra of high-redshift quasars has been used as a tracer of large-scale structure by means of the three-dimensional Lyman-α forest auto-correlation function at redshift z≃ 2.3, but the need to fit the quasar continuum in every absorption spectrum introduces a broadband distortion that is difficult to correct and causes a systematic error for measuring any broadband properties. Here, we describe a k-space model for this broadband distortion based on a multiplicative correction to the power spectrum of the transmitted flux fraction that suppresses power on scales corresponding to the typical length of a Lyman-α forest spectrum. In implementing the distortion model in fits for the baryon acoustic oscillation (BAO) peak position in the Lyman-α forest auto-correlation, we find that the fitting method recovers the input values of the linear bias parameter b F and the redshift-space distortion parameter β F for mock data sets with a systematic error of less than 0.5%. Applied to the auto-correlation measured for BOSS Data Release 11, our method improves on the previous treatment of broadband distortions in BAO fitting by providing a better fit to the data using fewer parameters and reducing the statistical errors on βF and the combination b F (1+β F ) by more than a factor of seven. The measured values at redshift z=2.3 are βF=1.39 +0.11 +0.24 +0.38 -0.10 -0.19 -0.28 and bF(1+βF)=-0.374 +0.007 +0.013 +0.020 -0.007 -0.014 -0.022 (1σ, 2σ and 3σ statistical errors). Our fitting software and the input files needed to reproduce our main results are publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

AT2017gfo: Bayesian inference and model selection of multicomponent kilonovae and constraints on the neutron star equation of state

The joint detection of the gravitational wave GW170817, of the short γ-ray burst GRB170817A and of the kilonova AT2017gfo, generated by the the binary neutron star (NS) merger observed on 2017 August 17, is a milestone in multimessenger astronomy and provides new constraints on the NS equation of state. We perform Bayesian inference and model selection on AT2017gfo using semi-analytical, multicomponents models that also account for non-spherical ejecta. Observational data favour anisotropic geometries to spherically symmetric profiles, with a log-Bayes’ factor of ~104, and favour multicomponent models against single-component ones. The best-fitting model is an anisotropic three-component composed of dynamical ejecta plus neutrino and viscous winds. Using the dynamical ejecta parameters inferred from the best-fitting model and numerical–relativity relations connecting the ejecta properties to the binary properties, we constrain the binary mass ratio to q < 1.54 and the reduced tidal parameter to $120\lt \tilde{\Lambda }\lt 1110$. Finally, we combine the predictions from AT2017gfo with those from GW170817, constraining the radius of a NS of 1.4 M ⊙ to 12.2 ± 0.5 km (1σ level). This prediction could be further strengthened by improving kilonova models with numerical-relativity information.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Absorption Properties of Supercooled Liquid Water between 31 and 225 GHz: Evaluation of Absorption Models Using Ground-Based Observations

Microwave radiometers (MWR) are commonly used to quantify the amount of supercooled liquid water (SLW) in clouds; however, the accuracy of the SLW retrievals is limited by the poor knowledge of the SLW dielectric properties at microwave frequencies. Six liquid water permittivity models were compared with ground-based MWR observations between 31 and 225 GHz from sites in Greenland, the German Alps, and a low-mountain site; average cloud temperatures of observed thin cloud layers range from 0° to –33°C. A recently published method to derive ratios of liquid water opacity from different frequencies was employed in this analysis. These ratios are independent of liquid water path and equal to the ratio of αL at those frequencies that can be directly compared with the permittivity model predictions. The observed opacity ratios from all sites show highly consistent results that are generally within the range of model predictions; however, none of the models are able to approximate the observations over the entire frequency and temperature range. Findings in earlier published studies were used to select one specific model as a reference model for αL at 90 GHz; together with the observed opacity ratios, the temperature dependence of αL at 31.4, 52.28, 150, and 225 GHz was derived. The results reveal that two models fit the opacity ratio data better than the other four models, with one of the two models fitting the data better for frequencies below 90 GHz and the other for higher frequencies. Furthermore, these findings are relevant for SLW retrievals and radiative transfer in the 31–225-GHz frequency region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Hall thruster plasma fluctuations identified as the E×B electron drift instability: Modeling and fitting on experimental data

Microturbulence has been implicated in anomalous transport at the exit of the Hall thruster, and recent simulations have shown the presence of an azimuthal wave which is believed to contribute to the electron axial mobility. In this paper, the 3D dispersion relation of this E×B electron drift instability is numerically solved. The mode is found to resemble an ion acoustic mode for low values of the magnetic field, as long as a non-vanishing component of the wave vector along the magnetic field is considered, and as long as the drift velocity is small compared to the electron thermal velocity. In these conditions, an analytical model of the dispersion relation for the instability is obtained and is shown to adequately describe the mode obtained numerically. This model is then fitted on the experimental dispersion relation obtained from the plasma of a Hall thruster by the collective light scattering diagnostic. The observed frequency-wave vector dependences are found to be similar to the dispersion relation of linear theory, and the fit provides a non-invasive measurement of the electron temperature and density.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗