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At least 253 records · Page 14

Visible Motion Blur

A method of measuring motion blur is disclosed comprising obtaining a moving edge temporal profile r(sub 1)(k) of an image of a high-contrast moving edge, calculating the masked local contrast m(sub1)(k) for r(sub 1)(k) and the masked local contrast m(sub 2)(k) for an ideal step edge waveform r(sub 2)(k) with the same amplitude as r(sub 1)(k), and calculating the measure or motion blur Psi as a difference function, The masked local contrasts are calculated using a set of convolution kernels scaled to simulate the performance of the human visual system, and Psi is measured in units of just-noticeable differences.

Watson, Andrew B.↗

Robust Multigrid Smoothers for Three Dimensional Elliptic Equations with Strong Anisotropies

We discuss the behavior of several plane relaxation methods as multigrid smoothers for the solution of a discrete anisotropic elliptic model problem on cell-centered grids. The methods compared are plane Jacobi with damping, plane Jacobi with partial damping, plane Gauss-Seidel, plane zebra Gauss-Seidel, and line Gauss-Seidel. Based on numerical experiments and local mode analysis, we compare the smoothing factor of the different methods in the presence of strong anisotropies. A four-color Gauss-Seidel method is found to have the best numerical and architectural properties of the methods considered in the present work. Although alternating direction plane relaxation schemes are simpler and more robust than other approaches, they are not currently used in industrial and production codes because they require the solution of a two-dimensional problem for each plane in each direction. We verify the theoretical predictions of Thole and Trottenberg that an exact solution of each plane is not necessary and that a single two-dimensional multigrid cycle gives the same result as an exact solution, in much less execution time. Parallelization of the two-dimensional multigrid cycles, the kernel of the three-dimensional implicit solver, is also discussed. Alternating-plane smoothers are found to be highly efficient multigrid smoothers for anisotropic elliptic problems.

Llorente, Ignacio M.↗

Reliable Ignition of LOX-LCH4 Propellants

No cryogenic Reaction Control System (RCS) has ever flown in space. Cryogenic propellants are baselined by HLS and CLPS partners and are the key use case for future ISRU manufactured propellants. A reliable LOX/LCH 4 RCS is an enabling technology for human Lunar and Mars exploration. In previous thermal vacuum (<275 F, <10 torr) testing at NASA GRC Plum Brook, the team uncovered anomalous LOX/LCH4 engine ignition phenomena where flame kernels quenched at these ultra cold hardware temperatures, leading to many pulses where the engines would not light. In 2022, the project was able to recreate the no light condition with an upgraded Frost-Mint test stand at JSC. This project implemented test stand improvements and procured propellants and follow on engine components for a hot fire campaign beginning in November 2024 which will attempt to ignite the RCS engine at ultra cold vacuum conditions by modifying the engine mixture ratio. New modeling techniques were implemented to account for past no lights and are an enabling method to make lunar surface go no go predictions based on hardware conditions. This was enabled by significant improvements to the Frost Mint system, which reduced moisture build up and leaks, increased propellant availability, leading to more attempts at thermal vacuum hot-fires.

Propulsion↗

Reduced-Order Modeling: Cooperative Research and Development at the NASA Langley Research Center

Cooperative research and development activities at the NASA Langley Research Center (LaRC) involving reduced-order modeling (ROM) techniques are presented. Emphasis is given to reduced-order methods and analyses based on Volterra series representations, although some recent results using Proper Orthogonal Deco in position (POD) are discussed as well. Results are reported for a variety of computational and experimental nonlinear systems to provide clear examples of the use of reduced-order models, particularly within the field of computational aeroelasticity. The need for and the relative performance (speed, accuracy, and robustness) of reduced-order modeling strategies is documented. The development of unsteady aerodynamic state-space models directly from computational fluid dynamics analyses is presented in addition to analytical and experimental identifications of Volterra kernels. Finally, future directions for this research activity are summarized.

Silva, Walter A.↗

Common radiation analysis model for 75,000 pound thrust NERVA engine (1137400E)

The mathematical model and sources of radiation used for the radiation analysis and shielding activities in support of the design of the 1137400E version of the 75,000 lbs thrust NERVA engine are presented. The nuclear subsystem (NSS) and non-nuclear components are discussed. The geometrical model for the NSS is two dimensional as required for the DOT discrete ordinates computer code or for an azimuthally symetrical three dimensional Point Kernel or Monte Carlo code. The geometrical model for the non-nuclear components is three dimensional in the FASTER geometry format. This geometry routine is inherent in the ANSC versions of the QAD and GGG Point Kernal programs and the COHORT Monte Carlo program. Data are included pertaining to a pressure vessel surface radiation source data tape which has been used as the basis for starting ANSC analyses with the DASH code to bridge into the COHORT Monte Carlo code using the WANL supplied DOT angular flux leakage data. In addition to the model descriptions and sources of radiation, the methods of analyses are briefly described.

Warman, E. A.↗

Domain decomposition methods in aerodynamics

Compressible Euler equations are solved for two-dimensional problems by a preconditioned conjugate gradient-like technique. An approximate Riemann solver is used to compute the numerical fluxes to second order accuracy in space. Two ways to achieve parallelism are tested, one which makes use of parallelism inherent in triangular solves and the other which employs domain decomposition techniques. The vectorization/parallelism in triangular solves is realized by the use of a recording technique called wavefront ordering. This process involves the interpretation of the triangular matrix as a directed graph and the analysis of the data dependencies. It is noted that the factorization can also be done in parallel with the wave front ordering. The performances of two ways of partitioning the domain, strips and slabs, are compared. Results on Cray YMP are reported for an inviscid transonic test case. The performances of linear algebra kernels are also reported.

Venkatakrishnan, V.↗

FD-TD modeling of 2-D dielectric waveguides for propagation and scattering of femtosecond optical solitons

Experimentalists have produced all-optical switches capable of 100-fs responses. To adequately model such switches, nonlinear effects in optical materials (both instantaneous and dispersive) must be included. In principle, the behavior of electromagnetic fields in nonlinear dielectrics can be determined by solving Maxwell's equations subject to the assumption that the electric polarization has a nonlinear relation to the electric field. However, until our previous work, the resulting nonlinear Maxwell's equations have not been solved directly. Rather, approximations have been made that result in a class of generalized nonlinear Schrodinger equations (GNLSE) that solve only for the envelope of the optical pulses. In this paper, we present first-time calculations from the vector nonlinear Maxwell's equations of femtosecond soliton propagation and scattering, including carrier waves, in two-dimensional systems of dielectric waveguides exhibiting the Kerr and Raman quantum effects. We use the finite-difference time-domain (FD-TD) method in an extension of our 1-D work. There, in a fundamental innovation, we treated the linear and nonlinear convolutions for the electric polarization as new dependent variables. By differentiating these convolutions in the time domain, we derived an equivalent system of coupled, nonlinear second-order ODE's. These equations together with Maxwell's equations form the system that is solved to determine the electromagnetic fields in inhomogeneous nonlinear dispersive media. Backstorage in time is limited to only that needed by the time-integration algorithm for the ODE's, rather than that needed to store the time-history of the kernel functions of the convolutions (1000-10,000 time steps). Thus, a 2-D nonlinear optics model from Maxwell's equations is now feasible.

Joseph, Rose↗

IKOS: Sound Static Program Analysis

IKOS (Inference Kernel for Open Static Analyzers) is a static analyzer for C/C++ based on the theory of Abstract Interpretation. It can detect or prove the absence of runtime errors (e.g, buffer overflows, integer overflows, null pointer dereferences, etc.) in the source code. IKOS uses Abstract Interpretation techniques to compute an over-approximation of all the reachable states of the program, thus it cannot miss a bug. In this talk, I will give an overview of the tool, then show how to apply it to a large software. I will present ikos-view, a web interface to examine the analysis results. I will discuss about methods to improve the analysis, such as adding code annotations, modeling library functions, and avoiding specific code patterns.

Arthaud, Maxime↗

Inclusion of the second Umkehr in the conventional Umkehr retrieval analysis as a means of improving ozone retrievals in the upper stratosphere

The Umkehr method for retrieving the gross features of the vertical ozone distribution requires measurements of the ratio of zenith-sky radiances at two wavelengths in the near-UV region while the solar zenith angle (SZA) changes from 60 to 90 degrees. A Brewer spectrophotometer was used for taking such measurements extending the SZA range down to 96 degrees. Analyzed data from the Spring of 1991 imply that observations at twilight are of great significance in improving ozone retrievals in the upper stratosphere. Judged by the variance reduction for Umkehr layers 9 to 12 (25-30 percent for layer 11) and the increase in separation and amplitude of the averaging kernels for the relevant layers, the ozone retrievals in the upper stratosphere are shown to be in better agreement with climatological means.

Gioulgkidis, Konstantinos↗

Radiometric Characterization of IKONOS Multispectral Imagery

A radiometric characterization of Space Imaging's IKONOS 4-m multispectral imagery has been performed by a NASA funded team from the John C. Stennis Space Center (SSC), the University of Arizona Remote Sensing Group (UARSG), and South Dakota State University (SDSU). Both intrinsic radiometry and the effects of Space Imaging processing on radiometry were investigated. Relative radiometry was examined with uniform Antarctic and Saharan sites. Absolute radiometric calibration was performed using reflectance-based vicarious calibration methods on several uniform sites imaged by IKONOS, coincident with ground-based surface and atmospheric measurements. Ground-based data and the IKONOS spectral response function served as input to radiative transfer codes to generate a Top-of-Atmosphere radiance estimate. Calibration coefficients derived from each vicarious calibration were combined to generate an IKONOS radiometric gain coefficient for each multispectral band assuming a linear response over the full dynamic range of the instrument. These calibration coefficients were made available to Space Imaging, which subsequently adopted them by updating its initial set of calibration coefficients. IKONOS imagery procured through the NASA Scientific Data Purchase program is processed with or without a Modulation Transfer Function Compensation kernel. The radiometric effects of this kernel on various scene types was also investigated. All imagery characterized was procured through the NASA Scientific Data Purchase program.

Pagnutti, Mary↗

Multiple Kernel Learning for Heterogeneous Anomaly Detection: Algorithm and Aviation Safety Case Study

The world-wide aviation system is one of the most complex dynamical systems ever developed and is generating data at an extremely rapid rate. Most modern commercial aircraft record several hundred flight parameters including information from the guidance, navigation, and control systems, the avionics and propulsion systems, and the pilot inputs into the aircraft. These parameters may be continuous measurements or binary or categorical measurements recorded in one second intervals for the duration of the flight. Currently, most approaches to aviation safety are reactive, meaning that they are designed to react to an aviation safety incident or accident. In this paper, we discuss a novel approach based on the theory of multiple kernel learning to detect potential safety anomalies in very large data bases of discrete and continuous data from world-wide operations of commercial fleets. We pose a general anomaly detection problem which includes both discrete and continuous data streams, where we assume that the discrete streams have a causal influence on the continuous streams. We also assume that atypical sequence of events in the discrete streams can lead to off-nominal system performance. We discuss the application domain, novel algorithms, and also discuss results on real-world data sets. Our algorithm uncovers operationally significant events in high dimensional data streams in the aviation industry which are not detectable using state of the art methods

Das, Santanu↗

Robust Trajectory Optimization for NRHO Rendezvous Using SPICE Kernel Relative Motion

In this paper, robust optimization is performed on trajectory correction maneuvers during the lunar lander return phase of an Artemis mission, treating the trajectory from one hour after low lunar orbit departure to arrival in the vicinity of the lunar Gateway as a relative motion problem. To enable rapid stochastic optimization techniques requiring many candidate trajectories, SPICE kernel relative motion as implemented by the Quadratic Interpolated State Transition (QIST) system is used as the underlying dynamics propagation. The optimization is performed with a genetic optimizer using linear covariance (LinCov) software in a simplified operational context, taking into account the availability of navigation sensors with varying measurement models, ranges, and accuracies. No numerical integration is used, since the relative motion around Gateway is fully characterized with the a priori computation of the QIST coefficients. Maneuver placements are computed to optimize the minimum 3σ delta-v of the trajectory, the position dispersion at a target point, and a convex combination of these two metrics. An order of magnitude runtime improvement is provided over legacy methods with less than 10% error introduced. All QIST results are shown to be in-family with legacy methods. The tradespace for optimal delta-v design is found to range from 77.0 to 93.9 m/s, while the range of optimal dispersion is between 1.4 and 11.7 km.

Relative Motion↗

Using Machine-Learning Methods and Expert Prediction Probabilities to Forecast Solar Flares

It has long been known that studying connection between solar flares and properties of magnetic field in active regions is very important for understanding the flare physics and developing space weather forecasts. The Helioseismic and Magnetic Imager onboard the Solar Dynamics Observatory (SDO/HMI) obtains tremendous amounts of magnetic field data products. However the operational NOAA Space Weather Prediction Center (SWPC) forecasts of solar flares still represent prediction probabilities issued by the experts. In this research we investigate the possibilities to enhance the daily operational flare forecasts performed at the SWPC by developing a synergy of the expert predictions and physics-based criteria, and by employing machine-learning methods. Among the physics-based criteria we consider the descriptors of the Polarity Inversion Line (PIL) and Space weather HMI Active Region Patches (SHARP), and derive from them daily characteristics of the entire Sun. We also consider the daily descriptors of the GOES Soft X-Ray (SXR) 1-8 Angstroms flux such as the flare history of the previous days and averaged X-Ray flux. We estimate the effectiveness in separation of flaring and non-flaring cases for each characteristic, as well as for the expert prediction probabilities, and find that some PIL, SHARP and SXR descriptors are as effective as the expert prediction probabilities and should be considered to issue the flare forecast. Finally, we train and test several Machine-Learning classification algorithms (Support Vector Classifiers with various kernel functions, k-Nearest Neighbor Classifier, Random Forest Classifier, and Neural Networks) using the most effective descriptors and expert prediction probabilities, and compare the obtained predictions with the current SWPC forecasts.

Machine-Learning↗

Feasibility study, software design, layout and simulation of a two-dimensional fast Fourier transform machine for use in optical array interferometry

The NASA-Cornell Univ.-Worcester Polytechnic Institute Fast Fourier Transform (FFT) chip based on the architecture of the systolic FFT computation as presented by Boriakoff is implemented into an operating device design. The kernel of the system, a systolic inner product floating point processor, was designed to be assembled into a systolic network that would take incoming data streams in pipeline fashion and provide an FFT output at the same rate, word by word. It was thoroughly simulated for proper operation, and it has passed a comprehensive set of tests showing no operational errors. The black box specifications of the chip, which conform to the initial requirements of the design as specified by NASA, are given. The five subcells are described and their high level function description, logic diagrams, and simulation results are presented. Some modification of the Read Only Memory (ROM) design were made, since some errors were found in it. Because a four stage pipeline structure was used, simulating such a structure is more difficult than an ordinary structure. Simulation methods are discussed. Chip signal protocols and chip pinout are explained.

Boriakoff, Valentin↗

Linear Estimation of Particle Bulk Parameters from Multi-Wavelength Lidar Measurements

An algorithm for linear estimation of aerosol bulk properties such as particle volume, effective radius and complex refractive index from multiwavelength lidar measurements is presented. The approach uses the fact that the total aerosol concentration can well be approximated as a linear combination of aerosol characteristics measured by multiwavelength lidar. Therefore, the aerosol concentration can be estimated from lidar measurements without the need to derive the size distribution, which entails more sophisticated procedures. The definition of the coefficients required for the linear estimates is based on an expansion of the particle size distribution in terms of the measurement kernels. Once the coefficients are established, the approach permits fast retrieval of aerosol bulk properties when compared with the full regularization technique. In addition, the straightforward estimation of bulk properties stabilizes the inversion making it more resistant to noise in the optical data. Numerical tests demonstrate that for data sets containing three aerosol backscattering and two extinction coefficients (so called 3 + 2 ) the uncertainties in the retrieval of particle volume and surface area are below 45% when input data random uncertainties are below 20 %. Moreover, using linear estimates allows reliable retrievals even when the number of input data is reduced. To evaluate the approach, the results obtained using this technique are compared with those based on the previously developed full inversion scheme that relies on the regularization procedure. Both techniques were applied to the data measured by multiwavelength lidar at NASA/GSFC. The results obtained with both methods using the same observations are in good agreement. At the same time, the high speed of the retrieval using linear estimates makes the method preferable for generating aerosol information from extended lidar observations. To demonstrate the efficiency of the method, an extended time series of observations acquired in Turkey in May 2010 was processed using the linear estimates technique permitting, for what we believe to be the first time, temporal-height distributions of particle parameters.

linear estimation↗

Examination of Multiple Lithologies Within the Primitive Ordinary Chondrite NWA 5717

Northwest Africa 5717 is a primitive (subtype 3.05) ungrouped ordinary chondrite which contains two apparently distinct lithologies. In large cut meteorite slabs, the darker of these, lithology A, looks to host the second, much lighter in color, lithology B (upper left, Fig. 1). The nature of the boundary between the two is uncertain, ranging from abrupt to gradational and not always following particle boundaries. The distinction between the lithologies, beyond the obvious color differences, has been supported by a discrepancy in oxygen isotopes and an incongruity in the magnesium contents of chondrule olivine. Here, quantitative textural analysis and mineralogical methods have been used to investigate the two apparent lithologies within NWA 5717. Olivine grains contained in a thin section from NWA 7402, thought to be paired to 5717, were also measured to re-examine the distinct compositional range among the light and dark areas. Procedure: Particles from a high-resolution mosaic image of a roughly 13x15cm slice of NWA 5717 were traced in Adobe Photoshop. Due to the large size of the sample, visually representative regions of each lithology were chosen to be analyzed. The resulting layers of digitized particles were imported into ImageJ, which was used to measure their area, along with the axes, the angle from horizontal, and the centroid coordinates of ellipses fitted to each particle following the approach. Resulting 2D pixel areas were converted to spherical diameters employing the unfolding algorithm, which outputs a 3D particle size distribution based on digitized 2D size frequency data. Spatstat was used to create kernel density plots of the centroid coordinates for each region. X-ray compositional maps, microprobe analyses, and Mossbauer spectroscopy was conducted on a thin section of NWA 7402, tentatively paired to NWA 5717.

Cato, M. J.↗

Software unit testing in Ada environment

A validation procedure for the Ada binding of the Graphical Kernel System (GKS) is being developed. PRIOR Data Sciences is also producing a version of the GKS written in Ada. These major software engineering projects will provide an opportunity to demonstrate a sound approach for software testing in an Ada environment. The GKS/Ada validation capability will be a collection of test programs and data, and test management guidelines. These products will be used to assess the correctness, completeness, and efficiency of any GKS/Ada implementation. The GKS/Ada developers will be able to obtain the validation software for their own use. It is anticipated that this validation software will eventually be taken over by an independent standards body to provide objective assessments of GKS/Ada implementations, using an approach similar to the validation testing currently applied to Ada compilers. In the meantime, if requested, this validation software will be used to assess GKS/Ada products. The second project, implementation of GKS using the Ada language, is a conventional software engineering tasks. It represents a large body of Ada code and has some interesting testing problems associated with automatic testing of graphics routines. Here the normal test practices which include automated regression testing, independent quality assistance, test configuration management, and the application of software quality metrics will be employed. The software testing methods emphasize quality enhancement and automated procedures. Ada makes some aspects of testing easier, and introduces some concerns. These issues are addressed.

Warnock, Glenn↗

Using Ground Targets to Validate S-NPP VIIRS Day-Night Band Calibration

In this study, the observations from S-NPP VIIRS Day-Night band (DNB) and Moderate resolution bands (M bands) of Libya 4 and Dome C over the first four years of the mission are used to assess the DNB low gain calibration stability. The Sensor Data Records produced by NASA Land Product Evaluation and Algorithm Testing Element (PEATE) are acquired from nearly nadir overpasses for Libya 4 desert and Dome C snow surfaces. A kernel-driven bidirectional reflectance distribution function (BRDF) correction model is used for both Libya 4 and Dome C sites to correct the surface BRDF influence. At both sites, the simulated top-of-atmosphere (TOA) DNB reflectances based on SCIAMACHY spectral data are compared with Land PEATE TOA reflectances based on modulated Relative Spectral Response (RSR). In the Libya 4 site, the results indicate a decrease of 1.03% in Land PEATE TOA reflectance and a decrease of 1.01% in SCIAMACHY derived TOA reflectance over the period from April 2012 to January 2016. In the Dome C site, the decreases are 0.29% and 0.14%, respectively. The consistency between SCIAMACHY and Land PEATE data trends is good. The small difference between SCIAMACHY and Land PEATE derived TOA reflectances could be caused by changes in the surface targets, atmosphere status, and on-orbit calibration. The reflectances and radiances of Land PEATE DNB are also compared with matching M bands and the integral M bands based on M4, M5, and M7. The fitting trends of the DNB to integral M bands ratios indicate a 0.75% decrease at the Libya 4 site and a 1.89% decrease at the Dome C site. Part of the difference is due to an insufficient number of sampled bands available within the DNB wavelength range. The above results indicate that the Land PEATE VIIRS DNB product is accurate and stable. The methods used in this study can be used on other satellite instruments to provide quantitative assessments for calibration stability.

Chen, Xuexia↗