Search NASA⌕ Search

SEARCH · Search NASA

Results for “data space inversion”

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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Ensemble Data Assimilation Without Ensembles: Methodology and Application to Ocean Data Assimilation

Two methods to estimate background error covariances for data assimilation are introduced. While both share properties with the ensemble Kalman filter (EnKF), they differ from it in that they do not require the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The first method is referred-to as SAFE (Space Adaptive Forecast error Estimation) because it estimates error covariances from the spatial distribution of model variables within a single state vector. It can thus be thought of as sampling an ensemble in space. The second method, named FAST (Flow Adaptive error Statistics from a Time series), constructs an ensemble sampled from a moving window along a model trajectory. The underlying assumption in these methods is that forecast errors in data assimilation are primarily phase errors in space and/or time.

Data Assimilation↗
DOE OSTI2012

Nucleon structure studies through Timelike Compton Scattering

Hard exclusive processes have emerged as a class of reactions providing novel information on the quark and gluon distributions in hadrons. Factorization theorems allow one to express amplitudes of these processes in terms of Generalized Parton Distributions (GPDs). The measurement of suitable experimental observables and the extraction of GPDs is one of the high priority 12 GeV Jefferson Lab programs. Deeply Virtual Compton Scattering (DVCS) is generally thought of as the cleanest tool for accessing the valence quark GPDs of the nucleon. A new and promising opportunity on the road to constraining GPDs is presented by Timelike Compton scattering (TCS) the inverse process to space-like DVCS. TCS offers straightforward access to the real part of the Compton amplitude. Combining space-like and time-like data thus makes it possible to test the universality of GPDs. The first studies of TCS using real tagged and quasi-real untagged photons were performed at Jefferson Lab 6 GeV. In this talk preliminary results on angular asymmetries and extraction of the real part of Compton form-factors using electroproduction data and a comparison with photoproduction data will be presented. We will also discuss future plans for di-lepton production in the Jefferson Lab 12-GeV era.

Horn, Tanja↗
NASA NTRS1991

Remote sensing of earth terrain

In remote sensing, the encountered geophysical media such as agricultural canopy, forest, snow, or ice are inhomogeneous and contain scatters in a random manner. Furthermore, weather conditions such as fog, mist, or snow cover can intervene the electromagnetic observation of the remotely sensed media. In the modelling of such media accounting for the weather effects, a multi-layer random medium model has been developed. The scattering effects of the random media are described by three-dimensional correlation functions with variances and correlation lengths corresponding to the fluctuation strengths and the physical geometry of the inhomogeneities, respectively. With proper consideration of the dyadic Green's function and its singularities, the strong fluctuation theory is used to calculate the effective permittivities which account for the modification of the wave speed and attenuation in the presence of the scatters. The distorted Born approximation is then applied to obtain the correlations of the scattered fields. From the correlation of the scattered field, calculated is the complete set of scattering coefficients for polarimetric radar observation or brightness temperature in passive radiometer applications. In the remote sensing of terrestrial ecosystems, the development of microwave remote sensing technology and the potential of SAR to measure vegetation structure and biomass have increased effort to conduct experimental and theoretical researches on the interactions between microwave and vegetation canopies. The overall objective is to develop inversion algorithms to retrieve biophysical parameters from radar data. In this perspective, theoretical models and experimental data are methodically interconnected in the following manner: Due to the complexity of the interactions involved, all theoretical models have limited domains of validity; the proposed solution is to use theoretical models, which is validated by experiments, to establish the region in which the radar response is most sensitive to the parameters of interest; theoretically simulated data will be used to generate simple invertible models over the region. For applications to the remote sensing of sea ice, the developed theoretical models need to be tested with experimental measurements. With measured ground truth such as ice thickness, temperature, salinity, and structure, input parameters to the theoretical models can be obtained to calculate the polarimetric scattering coefficients for radars or brightness temperature for radiometers and then compare theoretical results with experimental data. Validated models will play an important role in the interpretation and classification of ice in monitoring global ice cover from space borne remote sensors in the future. We present an inversion algorithm based on a recently developed inversion method referred to as the Renormalized Source-Type Integral Equation approach. The objective of this method is to overcome some of the limitations and difficulties of the iterative Born technique. It recasts the inversion, which is nonlinear in nature, in terms of the solution of a set of linear equations; however, the final inversion equation is still nonlinear. The derived inversion equation is an exact equation which sums up the iterative Neuman (or Born) series in a closed form and, thus, is a valid representation even in the case when the Born series diverges; hence, the name Renormalized Source-Type Integral Equation Approach.

Yueh, Herng-Aung↗
DOE OSTI2020

Real-time sparse-sampled Ptychographic imaging through deep neural networks

Ptychography has rapidly grown in the fields of X-ray and electron imaging for its unprecedented ability to achieve nano or atomic scale resolution while simultaneously retrieving chemical or magnetic information from a sample. A ptychographic reconstruction is achieved by means of solving a complex inverse problem that imposes constraints both on the acquisition and on the analysis of the data, which typically precludes real-time imaging due to computational cost involved in solving this inverse problem. In this work we propose PtychoNN, a novel approach to solve the ptychography reconstruction problem based on deep convolutional neural networks. We demonstrate how the proposed method can be used to predict real-space structure and phase at each scan point solely from the corresponding far-field diffraction data. The presented results demonstrate how PtychoNN can effectively be used on experimental data, being able to generate high quality reconstructions of a sample up to hundreds of times faster than state-of-the-art ptychography reconstruction solutions once trained. By surpassing the typical constraints of iterative model-based methods, we can significantly relax the data acquisition sampling conditions and produce equally satisfactory reconstructions. Besides drastically accelerating acquisition and analysis, this capability can enable new imaging scenarios that were not possible before, in cases of dose sensitive, dynamic and extremely voluminous samples.

Cherukara, Mathew J↗
NASA NTRS2008

Ground-Based Lidar Measurements During the CALIPSO and Twilight Zone (CATZ) Campaign

The CALIPSO and Twilight Zone (CATZ) field campaign was carried out between June 26th and August 29th of 2007 in the multi-state Maryland-Virginia-Pennsylvania region of the U.S. to study aerosol properties and cloud-aerosol interactions during overpasses of the CALIPSO satellite. Field work was conducted on selected days when CALIPSO ground tracks occurred in the region. Ground-based measurements included data from multiple Cimel sunphotometers that were placed at intervals along a segment of the CALIPSO ground-track. These measurements provided sky radiance and AOD measurements to enable joints inversions and comparisons with CALIPSO retrievals. As part of this activity, four ground-based lidars provided backscatter measurements (at 523 nm) in the region. Lidars at University of Maryland Baltimore County (Catonsville, MD) and Goddard Space Flight Center (Greenbelt, MD) provided continuous data during the campaign, while two micro-pulse lidar (MPL) systems were temporarily stationed at various field locations directly on CALIPSO ground-tracks. As a result, thirteen on-track ground-based lidar observations were obtained from eight different locations in the region. In some cases, nighttime CALIPSO coincident measurements were also obtained. In most studies reported to date, ground-based lidar validation efforts for CALIPSO rely on systems that are at fixed locations some distance away from the satellite ground-track. The CATZ ground-based lidar data provide an opportunity to examine vertical structure properties of aerosols and clouds both on and off-track simultaneously during a CALIPSO overpass. A table of available ground-based lidar measurements during this campaign will be presented, along with example backscatter imagery for a number of coincident cases with CALIPSO. Results indicate that even for a ground-based measurements directly on-track, comparisons can still pose a challenge due to the differing spatio-temporal properties of the ground and satellite observations. The multiple-lidar data during the CATZ campaign is expected to provide additional information on regional aerosol and cloud dynamics for give overpass, and enable a more realistic assessment of ground-to-satellite correlations. Future work is anticipated to finalize calibrated lidar backscatter profiles and utilization of wind trajectory information to further enable comparisons to CALIPS data.

Berkoff, Timothy↗
DOE OSTI2016

Warhead verification as inverse problem: Applications of neutron spectrum unfolding from organic-scintillator measurements

Verification of future warhead-dismantlement treaties will require detection of certain warhead attributes without the disclosure of sensitive design information, and this presents an unusual measurement challenge. Neutron spectroscopy—commonly eschewed as an ill-posed inverse problem—may hold special advantages for warhead verification by virtue of its insensitivity to certain neutron-source parameters like plutonium isotopics. In this article, we investigate the usefulness of unfolded neutron spectra obtained from organic-scintillator data for verifying a particular treaty-relevant warhead attribute: the presence of high-explosive and neutron-reflecting materials. Toward this end, several improvements on current unfolding capabilities are demonstrated: deuterated detectors are shown to have superior response-matrix condition to that of standard hydrogen-base scintintillators; a novel data-discretization scheme is proposed which removes important detector nonlinearities; and a technique is described for re-parameterizing the unfolding problem in order to constrain the parameter space of solutions sought, sidestepping the inverse problem altogether. These improvements are demonstrated with trial measurements and verified using accelerator-based time-of-flight calculation of reference spectra. Then, a demonstration is presented in which the elemental compositions of low-Z neutron-attenuating materials are estimated to within 10%. These techniques could have direct application in verifying the presence of high-explosive materials in a neutron-emitting test item, as well as other for treaty verification challenges.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2013

Effects of Systematic and Random Errors on the Retrieval of Particle Microphysical Properties from Multiwavelength Lidar Measurements Using Inversion with Regularization

In this work we study the effects of systematic and random errors on the inversion of multiwavelength (MW) lidar data using the well-known regularization technique to obtain vertically resolved aerosol microphysical properties. The software implementation used here was developed at the Physics Instrumentation Center (PIC) in Troitsk (Russia) in conjunction with the NASA/Goddard Space Flight Center. Its applicability to Raman lidar systems based on backscattering measurements at three wavelengths (355, 532 and 1064 nm) and extinction measurements at two wavelengths (355 and 532 nm) has been demonstrated widely. The systematic error sensitivity is quantified by first determining the retrieved parameters for a given set of optical input data consistent with three different sets of aerosol physical parameters. Then each optical input is perturbed by varying amounts and the inversion is repeated. Using bimodal aerosol size distributions, we find a generally linear dependence of the retrieved errors in the microphysical properties on the induced systematic errors in the optical data. For the retrievals of effective radius, number/surface/volume concentrations and fine-mode radius and volume, we find that these results are not significantly affected by the range of the constraints used in inversions. But significant sensitivity was found to the allowed range of the imaginary part of the particle refractive index. Our results also indicate that there exists an additive property for the deviations induced by the biases present in the individual optical data. This property permits the results here to be used to predict deviations in retrieved parameters when multiple input optical data are biased simultaneously as well as to study the influence of random errors on the retrievals. The above results are applied to questions regarding lidar design, in particular for the spaceborne multiwavelength lidar under consideration for the upcoming ACE mission.

vertical profiles↗
DOE OSTI2019

Earthquake Locations

The location of an earthquake is a classic inverse problem. Arrival times of various seismic phases are combined with the location of the instrument to form the data vector. The inverse operator is applied in an iterative manor until the solution converges and the resultant solution is the hypocentral location of the earthquake in space and time. In this presentation, I will present how seismologists obtain local earthquake hypocenters. I will present how the generalized inverse operator is built using the simple distance = rate x time equation and how the inverse operator is used in an iterative manor to converge on the hypocenter of the earthquake. Once an earthquake location is determined, seismologists can then use the location to infer other information about the medium through which the waves traveled. One possible application of the earthquake locations is a branch of seismology known as tomography. In tomography, source and station locations are used to compute the travel times of seismic phases and these phases are then inverted to obtain a velocity model of the medium. Seismic tomography can be applied in both 2-D and 3-D settings and in this presentation, I will present examples from both. The first example comes from a technique known as ambient noise tomography. Rayleigh waves are obtained by cross correlating the background noise between two stations. Because we know the interstation distance between the two stations and the arrival times of the Rayleigh waves, we can use tomography to build a group velocity map of the study region. I will present results from a study of the Eastern Tennessee Seismic Zone using the EarthScope’s Transportable Array together with different seismic networks in the region, figure 1. The second example uses P and S-waves from 412 earthquakes which occurred during the 1994 Draney Peak swarm to calculate a 3-D velocity model of the area. Preliminary results show a strong velocity contrast at a depth of about 4 km where the majority of the earthquakes occur, figure 2.

58 GEOSCIENCES↗
NASA NTRS2001

Aerosol Profile Retrievals from Integrated Dual Wavelengths Space Lidar ESSP3-CENA and Spectral Radiance MODIS Data

The ESSP3-CENA space mission (formally PICASSO-CENA) will provide continues global observations with a two wavelength lidar. The attenuated backscattering coefficients measured by the lidar, have valuable information about the vertical distribution of aerosol particles and their sizes. However the information cannot be mapped into unique aerosol physical properties. Infinite number of physical solutions with different attenuations through the atmosphere can reconstruct the same two wavelength backscattered profile measured from space. Spectral radiance measured by MODIS simultaneously with the ESSP3 data can constrain the problem and resolve this ambiguity to a large extent. Sensitivity study shows that inversion of the integrated MODIS+ESSP3 data can derive the vertical profiles of the fine and coarse modes mixed in the same atmospheric column in the presence of moderate calibration uncertainties and electronic noise (approx. 10%). We shall present the sensitivity study and results from application of the technique to measurements in the SAFARI-2000 and SHADE experiments.

Kaufman, Yoram↗
DOE OSTI2017

Joint synthetic aperture radar plus ground moving target indicator from single-channel radar using compressive sensing

The various embodiments presented herein relate to utilizing an operational single-channel radar to collect and process synthetic aperture radar (SAR) and ground moving target indicator (GMTI) imagery from a same set of radar returns. In an embodiment, data is collected by randomly staggering a slow-time pulse repetition interval (PRI) over a SAR aperture such that a number of transmitted pulses in the SAR aperture is preserved with respect to standard SAR, but many of the pulses are spaced very closely enabling movers (e.g., targets) to be resolved, wherein a relative velocity of the movers places them outside of the SAR ground patch. The various embodiments of image reconstruction can be based on compressed sensing inversion from undersampled data, which can be solved efficiently using such techniques as Bregman iteration. The various embodiments enable high-quality SAR reconstruction, and high-quality GMTI reconstruction from the same set of radar returns.

47 OTHER INSTRUMENTATION↗
NASA NTRS2001

Simultaneous Retrieval of Temperature, Water Vapor and Ozone Atmospheric Profiles from IASI: Compression, De-noising, First Guess Retrieval and Inversion Algorithms

A fast temperature water vapor and ozone atmospheric profile retrieval algorithm is developed for the high spectral resolution Infrared Atmospheric Sounding Interferometer (IASI) space-borne instrument. Compression and de-noising of IASI observations are performed using Principal Component Analysis. This preprocessing methodology also allows, for a fast pattern recognition in a climatological data set to obtain a first guess. Then, a neural network using first guess information is developed to retrieve simultaneously temperature, water vapor and ozone atmospheric profiles. The performance of the resulting fast and accurate inverse model is evaluated with a large diversified data set of radiosondes atmospheres including rare events.

Aires, F.↗
NASA NTRS1987

Measurement of differential proton spectra onboard the Space Shuttle using a thermoluminescent dosimetry system

An experimental technique that permits the extraction of orbit-averaged, differential energy spectra of trapped radiation belt protons using simple passive detectors is described. An inversion technique is used for the data analysis. The basic principle of the described system is measurement of the energy deposited in six thermoluminescent (TLD) detector assemblies behind various spherical absorbers. The technique has been applied to a detector assembly flown on four Shuttle flights. Although severe restraints were placed on the flight package, the differential energy spectra derived from these measurements are in good agreement with analytical results using a modified trapped proton environment model. The technique shows good promise for measuring the spectra in low inclination orbits where the flux of high energy galactic cosmic rays protons is small. Modifications to the detector assembly to improve the accuracy and to extend the range of the system to higher energies are suggested.

STS-51J Shuttle Project↗
NASA NTRS1979

Modeling of terrain gradient for stochastically spaced rows of a measurement matrix

Terrain gradients are employed to evaluate passable regions for unmanned martian roving vehicle. Range data matrix is displaced randomly row wise at the shallow elevation angles near the skyline. The magnitude of the measurement noise in the elevation angles can approach that of the spacing of the same angle. By using a variable incremental data spacing scanning scheme, one can estimate this signal noise ratio. It is found that the error in slope estimate at far distance becomes large for a given elevation angle error. Evaluation of the in-path slopes can be expressed in terms of the inverse of the range slopes. This is because of the fact that the elevation angle is considered as a random variable while the range data are relatively less noisy. An error analysis is performed and it is found that the change of slope is a nonlinear function of the error in elevation angle.

Mediavilla, R.↗
DOE OSTI2022

Manifold Learning-Based Polynomial Chaos Expansions for High-Dimensional Surrogate Models

In this work we introduce a manifold learning-based method for uncertainty quantification (UQ) in systems describing complex spatiotemporal processes. Our first objective is to identify the embedding of a set of high-dimensional data representing quantities of interest of the computational or analytical model. For this purpose, we employ Grassmannian diffusion maps, a two-step nonlinear dimension reduction technique which allows us to reduce the dimensionality of the data and identify meaningful geometric descriptions in a parsimonious and inexpensive manner. Polynomial chaos expansion is then used to construct a mapping between the stochastic input parameters and the diffusion coordinates of the reduced space. An adaptive clustering technique is proposed to identify an optimal number of clusters of points in the latent space. The similarity of points allows us to construct a number of geometric harmonic emulators which are finally utilized as a set of inexpensive pretrained models to perform an inverse map of realizations of latent features to the ambient space and thus perform accurate out-of-sample predictions. Thus, the proposed method acts as an encoder-decoder system which is able to automatically handle very high-dimensional data while simultaneously operating successfully in the small-data regime. The method is demonstrated on two benchmark problems and on a system of advection-diffusion-reaction equations which model a first-order chemical reaction between two species. In all test cases, the proposed method is able to achieve highly accurate approximations which ultimately lead to the significant acceleration of UQ tasks.

42 ENGINEERING↗
DOE OSTI2025

Characterization of DESI fiber assignment incompleteness effect on 2-point clustering and mitigation methods for DR1 analysis

We present an in-depth analysis of the fiber assignment incompleteness in the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1). This incompleteness is caused by the restricted mobility of the robotic fiber positioner in the DESI focal plane, which limits the number of galaxies that can be observed at the same time, especially at small angular separations. As a result, the observed clustering amplitude is suppressed in a scale-dependent manner, which, if not addressed, can severely impact the inference of cosmological parameters. We discuss the methods adopted for simulating fiber assignment on mocks and data. In particular, we introduce the fast fiber assignment (FFA) emulator, which was employed to obtain the power spectrum covariance adopted for the DR1 full-shape analysis. We present the mitigation techniques, organised in two classes: measurement stage and model stage. We then use high fidelity mocks as a reference to quantify both the accuracy of the FFA emulator and the effectiveness of the different measurement-stage mitigation techniques. This complements the studies conducted in a parallel paper for the model-stage techniques, namely the θ-cut approach. We find that pairwise inverse probability (PIP) weights with angular upweighting recover the “true” clustering in all the cases considered, in both Fourier and configuration space. Notably, we present the first ever power spectrum measurement with PIP weights from real data.

cosmological simulations↗
NASA NTRS1989

Surface grid generation for flowfield applications using B-spline surfaces

The adequate discretization of the flowfield domain in structured grid techniques depends on the body surface, the zones, and the interior grid. Attention is presently given to the problem of obtaining a versatile surface-definition and grid-generation technique; a general surface grid-generation technique is presented which develops three-dimensional patches from point data. The grid is generated on a two-dimensional field on the basis of either a direct or inverse interpolation procedure. It is then mapped onto physical space to yield the surface grid.

Atwood, Christopher A.↗
NASA NTRS1990

Calibration of long term satellite ozone data sets using the space shuttle

Trends in atmospheric ozone continue to be an environmental concern. Drifts in satellite observations are the major obstacle in the detection of changes in global ozone over the long term. Careful re-analysis of satellite ozone data along with groundbased observations have more or less corroborated photochemical models which predict ozone depletion. However, there remains the margin of error in the observations that is as large as the trend itself. The National Plan for Stratospheric Monitoring calls for monitoring global ozone for at lease the next ten years employing the NOAA polar orbiting satellites. Ozone observations will be made with the Solar Backscatter Ultraviolet Spectral Radiometer Mod 2 (SBUV/2) which ia a refinement of the SBUV instrument flying on NASA's Nimbus-7 satellite. The first instrument in the operational series began taking data from the NOAA-9 spacecraft in February 1985. A second instrument was launched on NOAA-11 in September 1988. Both continue to operate. Earlier attempts to calibrate satellite data relied on comparisons with ground based observations. However, differences in instrumental techniques severely complicated these efforts. This problem will be over come by regular flights, about once per year, of the Shuttle Solar Backscatter Ultraviolet radiometer (SSBUV). The data from the SSBUV instrument will be compared with nearly coincident data taken by the NOAA satellite instruments. This procedure will permit a direct calibration transfer in space, since the two instruments observe the same qualities thereby bypassing the inversion algorithm which converts the observations to ozone amounts.

Hilsenrath, Ernest↗
DOE OSTI2026

Extracting $B_s\to D_s^*\ellν_\ell$ form factors

Semileptonic $B_{(s)}$ decays are of great phenomenological interest because they allow to determine e.g. CKM matrix elements or test lepton flavor universality. Taking advantage of already existing lattice data, we demonstrate the analysis steps to extract the four form factors describing exclusive semileptonic $B_s\to D_s^*\ellν_\ell$ decays using the narrow width approximation. Our data are based on RBC/UKQCD's set of 2+1 flavor gauge field ensembles with Shamir domain-wall fermion and Iwasaki gauge field action featuring inverse lattice spacings of $a^{-1}=$1.785, 2.383, and 2.785 GeV as well as pion masses between 268 and 433 MeV. Light, strange and charm quarks are simulated using domain-wall fermions, whereas bottom quarks are generated with the relativistic heavy quark (RHQ) action.

Boushmelev, Anastasia [Siegen U.] (ORCID:000000033↗