Search NASA⌕ Search

SEARCH · Search NASA

Results for “parameter inference”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Quantifying Uncertainty in Particle Size Distribution Parameters Inferred from SAGE III/ISS Extinction Spectra

Stratospheric aerosols play key roles in the chemistry and radiation balance of the atmosphere and are a key input parameter for global chemistry and climate models. The degree to which aerosols impact chemistry and radiation balance depends primarily on their microphysical properties such as particle size distribution (PSD). The PSD is a mathematical description of the relative abundance of different sized particles within a sampling volume. If the PSD is accurately known then other key modeling parameters (e.g., surface area density) can be derived. Occultation observations from orbital instruments such as SAGE III/ISS have been used to infer these PSD parameters by inverting the extinction coefficient spectra. However, past efforts failed to address two key issues with this methodology: 1. The measurement uncertainty was not accounted for; 2. They assumed the PSDs to be single-mode only, while “real-world” PSDs are predominantly bi-modal. Accounting for both issues in the retrieval will yield an expanded solution space to the inferred PSD parameters; the question is “by how much?” To address this knowledge gap, we propose to carry out a series of simulations and, for every valid SAGE III/ISS data point, determine the range of PSD parameters that yield extinction spectra that are indistinguishable from the SAGE III/ISS data, within the limits of the reported uncertainty. Further, we will expand the solution space, for the first time, to include bimodal distributions. The results of this work will advance Earth system modeling/prediction capability through identifying the uncertainty of PSD parameter estimates using SAGE III/ISS data. The key benefits of this study over previous studies are twofold: 1. we will provide PSD estimates that include bimodal distributions in the solution space, 2. we will provide an uncertainty estimate for these parameters. The results of this study may be used directly in current and future climate and chemistry models.

SAGE III/ISS↗
NASA NTRS2019

Parameters Inference and Model Reduction for the Single-Particle Model of Li Ion Cells

The Single-Particle Model (SPM) of Li ion cell is a computationally efficient model for simulating Li ion cell for weak to moderate currents. The model depends n a number of parameters describing the geometry and material properties of a cell components. In order to apply the model to simulating a cell, the best-fit parametric values have to be inferred from a constant discharge data. We report our efforts to determine the best-fit set for 18650 LP batteries. We found that rather than being best-fit by a particular point in the parametric space the data is fit equally well by an ensemble of points clustering about an effective multidimensional manifold in the parametric space. This property of the SPM is known to be shared by a multitude of the so-called "sloppy models" of complex systems, characterized by a few stiff directions in the parametric space, in which the predicted behavior varies significantly, and a number of sloppy directions in which the behavior doesn't change appreciably. Only the stiff parameters combinations are identifiable. Geometrical features of the BFM give insights to possible reduction of the SPM to a model having fewer sloppy parameters. We have constructed a hierarchy of such models. The fully reduced model depends on only stiff effective parameters which are identifiable and can be used for characterization of the battery's state of health.

Khasin, Michael↗
NASA NTRS1987

Solar active region physical parameters inferred from a thermal cyclotron line and soft X-ray spectral lines

Simultaneous high-resolution observations of coronal loops were made at the 20-cm wavelength with the VLA and at soft X-ray wavelengths with the SMM FCS. The images obtained at both wavelengths have nearly identical sizes and ellipsoidal shapes, with the emission stretching between and across regions of opposite magnetic polarity in the underlying photosphere. The results indicate that the radiation at 20 cm and soft X-ray wavelengths originates from the same region, and that 20 cm maps can image X-ray coronal loops. The X-ray spectral lines were used to obtain values of electron temperature, T(e), of about 2.6 x 10 to the 6th K and electron density, N(e), of about 3.1 x 10 to the 9th/cu cm. These parameters were used to show that the layers emitting 20-cm radiation can be optically thick to either thermal bremsstrahlung or thermal gyroresonance radiation, depending upon unknown but plausible values of loop thickness, magnetic scale height, and magnetic field strength.

Lang, Kenneth R.↗
NASA NTRS2021

Conjugate Photoelectron Energy Spectra Derived From Coincident FUV and Radio Measurements

We present a method for estimating incident photoelectrons' energy spectra as a function of altitude by combining global scale far-ultraviolet (FUV) and radio-occultation (RO) measurements. This characterization provides timely insights important for accurate interpretation of ionospheric parameters inferred from the recently launched Ionospheric Connection Explorer (ICON) observations. Quantification of photoelectron impact is enabled by the fact that conjugate photoelectrons (CPEs) directly affect FUV airglow emissions but not RO measurements. We demonstrate a technique for estimation of photoelectron fluxes and their spectra by combining coincident ICON and COSMIC2 measurements and show that a significant fraction of ICON-FUV measurements is affected by CPEs during the winter solstice. A comparison of estimated photoelectron fluxes with measured photoelectron spectra is used to gain further insights into the estimation method and reveals consistent values within 10–60 eV. Plain Language Summary The impact of solar radiation on the atmosphere produces highly energetic electrons, which travel freely along the magnetic Earth's field lines from one hemisphere to the other. When these electrons flow from the sunlit side into the nightside hemisphere, they interact with the neutral species and produce noticeable effects in the ionosphere such as an increase in electron temperature and enhancement of airglow emissions. This study presents a method to quantify the amount of precipitating electrons and their energy on a global scale using two recent satellite missions, ICON and COSMIC2. Our results demonstrate that coincident far-ultraviolet (ICON) and radio-occultation (COSMIC2) measurements from space are valuable resources to study precipitating electrons in the ionosphere and their impact on inferring ionospheric plasma parameters.

J M Urco↗
NASA NTRS1975

Isothermal blast wave model of supernova remnants

The validity of the 'adiabatic' assumption in supernova-remnant calculations is examined, and the alternative extreme of an isothermal blast wave is explored. It is concluded that, because of thermal conductivity, the large temperature gradients predicted by the adiabatic model probably are not maintained in nature. Self-similar solutions to the hydrodynamic equations for an isothermal blast wave have been found and studied. These solutions are then used to determine the relationship between X-ray observations and inferred parameters of supernova remnants. A comparison of the present results with those for the adiabatic model indicates differences which are less than present observational uncertainties. It is concluded that most parameters of supernova remnants inferred from X-ray measurements are relatively insensitive to the specifics of the blast-wave model.

Solinger, A.↗
NASA NTRS1981

The asymmetric 4.8 hour X-ray modulation of Cygnus X-3 - Model light curves and inferred orbital parameters

The 4.8 hour X-ray light curve of Cygnus X-3 is quantitatively described by several proposed models under the assumption that the binary orbit of Cyg X-3 is elliptic. The cocoon model implies an apparent size for the X-ray star's companion, which is larger than that of its critical lobe, and it is suggested that the emission of a dense stellar wind by the companion could lead to such a situation. It is shown that a helium star, with or without a hydrogen-rich envelope, seems to be the most likely Cyg X-3 companion, and that some of the observed variations in the 4.8 hour period can be accounted for by the apparent period variations due to apsidal motion.

Ghosh, P.↗
NASA NTRS2011

AIRS-Observed Interrelationships of Anomaly Time-Series of Moist Process-Related Parameters and Inferred Feedback Values on Various Spatial Scales

In the beginning, a good measure of a GMCs performance was their ability to simulate the observed mean seasonal cycle. That is, a reasonable simulation of the means (i.e., small biases) and standard deviations of TODAY?S climate would suffice. Here, we argue that coupled GCM (CG CM for short) simulations of FUTURE climates should be evaluated in much more detail, both spatially and temporally. Arguably, it is not the bias, but rather the reliability of the model-generated anomaly time-series, even down to the [C]GCM grid-scale, which really matter. This statement is underlined by the social need to address potential REGIONAL climate variability, and climate drifts/changes in a manner suitable for policy decisions.

Molnar, Gyula I.↗
NASA NTRS2016

Degree of Ice Particle Surface Roughness Inferred from Polarimetric Observations

The degree of surface roughness of ice particles within thick, cold ice clouds is inferred from multidirectional, multi-spectral satellite polarimetric observations over oceans, assuming a column-aggregate particle habit. An improved roughness inference scheme is employed that provides a more noise-resilient roughness estimate than the conventional best-fit approach. The improvements include the introduction of a quantitative roughness parameter based on empirical orthogonal function analysis and proper treatment of polarization due to atmospheric scattering above clouds. A global 1-month data sample supports the use of a severely roughened ice habit to simulate the polarized reflectivity associated with ice clouds over ocean. The density distribution of the roughness parameter inferred from the global 1- month data sample and further analyses of a few case studies demonstrate the significant variability of ice cloud single-scattering properties. However, the present theoretical results do not agree with observations in the tropics. In the extra-tropics, the roughness parameter is inferred but 74% of the sample is out of the expected parameter range. Potential improvements are discussed to enhance the depiction of the natural variability on a global scale.

surface↗
NASA NTRS1996

The Properties of the local Interstellar Medium and the Interaction of the Stellar Winds of epsilon Indi and lambda Andromedae with the Interstellar Environment

We present new observations of the Ly alpha lines of Epsilon Indi (K5 5) and A Andromedae (G8 4-3 + ?) These data were obtained by the Goddard High Resolution Spectrograph (GHRS) on the Hubble Space Telescope. Analysis of the interstellar H 1 and D 1 absorption lines reveals that the velocities and temperatures inferred from the H 1 lines are inconsistent with the parameters inferred from the D 1 lines, unless the H 1 absorption is assumed to be produced by two absorption components. One absorption component is produced by interstellar material. For both lines of sight observed, the velocity of this component is consistent with the velocity predicted by the local flow vector. For the Epsilon Indi data, the large velocity separation between the stellar emission and the interstellar absorption allows us to measure the H 1 column density independent of the shape of the intrinsic stellar Ly alpha profile. This approach permits us to quote an accurate column density and to assess its uncertainty with far more confidence than in previous analyses, for which the errors were dominated by uncertainties in the assumed stellar profiles.

Wood, Brian E.↗
NASA NTRS1980

Inversion of multiwavelength radiometer measurements by three-dimensional filtering

Remote sensing data from satellites typically have three dimensions: scan position, spacecraft position, and wavelength. Inversion of the radiometric data to infer geophysical parameters is a filtering problem in which the dimension of wavelength (or channel number) is transformed into a dimension of geophysical parameters, and the most general solution is a three-dimensional filter. Linear filters have the advantages of computational speed and easily described transfer functions; but often the measurements are nonlinear functions of the parameters to be inferred. To the extent that the nonlinear inversion problem is overdetermined, it can be modeled by a critically determined linear problem. As an example, inversion of Scanning Multichannel Microwave Radiometer (SMMR) data by means of a three-dimensional Wiener Filter is described. Atmospheric water vapor content, rain liquid water content, surface wind speed and surface temperature are the parameters inferred from the measurements. Nonprecipitating liquid water and water vapor scale height are also modeled but not retrieved. The a priori statistics on which the filter is trained have the effect of governing the selection of a trade-off point of noise as a function of resolution (in all three retrieval dimensions).

Rosenkranz, P. W.↗
NASA NTRS2010

Evolution of Geometric Sensitivity Derivatives from Computer Aided Design Models

The generation of design parameter sensitivity derivatives is required for gradient-based optimization. Such sensitivity derivatives are elusive at best when working with geometry defined within the solid modeling context of Computer-Aided Design (CAD) systems. Solid modeling CAD systems are often proprietary and always complex, thereby necessitating ad hoc procedures to infer parameter sensitivity. A new perspective is presented that makes direct use of the hierarchical associativity of CAD features to trace their evolution and thereby track design parameter sensitivity. In contrast to ad hoc methods, this method provides a more concise procedure following the model design intent and determining the sensitivity of CAD geometry directly to its respective defining parameters.

Jones, William T.↗
NASA NTRS2024

Masses of Sunyaev-Zel’dovich Galaxy Clusters Detected by the Atacama Cosmology Telescope: Stacked Lensing Measurements with Subaru HSC Year 3 Data

We present a stacked lensing analysis of 96 galaxy clusters selected by the thermal Sunyaev-Zel’dovich (SZ) effect in maps of the cosmic microwave background (CMB). We select foreground galaxy clusters with a 5σ-level SZ threshold in CMB observations from the Atacama Cosmology Telescope, while we define background source galaxies for the lensing analysis with secure photometric redshift cuts in Year 3 data of the Subaru Hyper Suprime Cam survey. We detect the stacked lensing signal in the range of 0.1 < R[h −1 Mpc] < 100 in each of three cluster redshift bins, 0.092 < z ≤ 0.445, 0.445 < z ≤ 0.695, and 0.695 < z ≤ 1.180, with 32 galaxy clusters in each bin. The cumulative signal-to-noise ratios of the lensing signal are 14.6, 12.0, and 6.6, respectively. Using a halo-based forward model, we then constrain statistical relationships between the mass inferred from the SZ observation (i.e. SZ mass) and the total mass derived from our stacked lensing measurements. At the average SZ mass in the cluster sample (2.1 − 2.4 × 10 14 h −1 M⊙), our likelihood analysis shows that the average total mass differs from the SZ counterpart by a factor of 1.3 ± 0.2, 1.6 ± 0.2, and 1.6 ± 0.3 (68%) in the aforementioned redshift ranges, respectively. Our limits are consistent with previous lensing measurements, and we find that the cluster modeling choices can introduce a 1σ-level difference in our parameter inferences.

Masato Shirasaki↗
NASA NTRS1975

Interstellar clouds containing optically thin H2

The theory of Black and Delgarno that the relative populations of the excited rotational levels of H2 can be understood in terms of cascading following absorption in the Lyman and Werner bands is employed to infer the gas densities and radiation fields within diffuse interstellar clouds containing H2 that is optically thin in those bands. The procedure is described for computing the populations of the different rotation levels, the relative distribution among the different rotation levels of newly formed H2 is determined on the basis of five simplified models, and the rate of H2 formation is estimated. The results are applied to delta Ori, two components of iota Ori, the second components of rho Leo and zeta Ori, tau Sco, gamma Vel, and zeta Pup. The inferred parameters are summarized for each cloud.

Jura, M.↗
NASA NTRS1983

Data processing techniques used with MST radars: A review

The data processing methods used in high power radar probing of the middle atmosphere are examined. The radar acts as a spatial filter on the small scale refractivity fluctuations in the medium. The characteristics of the received signals are related to the statistical properties of these fluctuations. A functional outline of the components of a radar system is given. Most computation intensive tasks are carried out by the processor. The processor computes a statistical function of the received signals, simultaneously for a large number of ranges. The slow fading of atmospheric signals is used to reduce the data input rate to the processor by coherent integration. The inherent range resolution of the radar experiments can be improved significant with the use of pseudonoise phase codes to modulate the transmitted pulses and a corresponding decoding operation on the received signals. Commutability of the decoding and coherent integration operations is used to obtain a significant reduction in computations. The limitations of the processors are outlined. At the next level of data reduction, the measured function is parameterized by a few spectral moments that can be related to physical processes in the medium. The problems encountered in estimating the spectral moments in the presence of strong ground clutter, external interference, and noise are discussed. The graphical and statistical analysis of the inferred parameters are outlined. The requirements for special purpose processors for MST radars are discussed.

Rastogi, P. K.↗
NASA NTRS1985

Discrete Random Media Techniques for Microwave Modeling of Vegetated Terrain

Microwave remote sensing of vegetated terrain has been studied. Vegetation is modeled so that backscattered radar signals can be used to infer parameters which characterize the vegetation and underlying ground. The vegetation is modeled by discrete lossy dielectric scatterers with prescribed characteristics. The goal of the modeling effort is to remotely sense vegetation type (classification), growth stage, and plant/ground moisture. This information can then be used as input into agricultural, forestry and global circulation models. The microwave frequency spectrum, particularly L and C bands, are especially appropriate for this purpose since the wavelength is comparable to plant leaf and stem size. The resulting resonant interaction leads to backscattered data highly depend on plant shape and orientation. In addition, the transparent nature of the atmosphere in this frequency regime allows for algorithm development which requires no atmospheric correction.

Lang, R. H.↗