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At least 1,099 records · Page 61

Classification of multifrequency multilook synthetic aperture radar data

A technique for segmentation of multifrequency multilook intensity synthetic aperture radar (SAR) data into regions of homogeneous and similar backscatter characteristics is presented. Two statistical models, one for the multifrequency multilook SAR intensities and the other for the distribution of the region labels, are combined to obtain the a posteriori probability distribution function of the region labels given the multifrequency speckled intensities. As the maximization of the posterior distribution is computationally intensive, a suboptimal technique for region labeling is proposed. Several examples using both simulated and real multifrequency multilook imagery are given to illustrate the performance of the algorithm.

Rignot, Eric↗

Evaluation of the Sensitivity of the Amazonian Diurnal Cycle to Convective Intensity in Reanalyses

Model parameterizations of tropical deep convection are unable to reproduce the observed diurnal and spatial variability of convection in the Amazon, which contributes to climatological biases in the water cycle and energy budget. Convective intensity regimes are defined using percentiles of daily minimum 3-hourly averaged outgoing longwave radiation (OLR) from Clouds and the Earth's Radiant Energy System (CERES). This study compares the observed spatial variability of convective diurnal cycle statistics for each regime to MERRA-2 and ERA-Interim (ERA) reanalysis data sets. Composite diurnal cycle statistics are computed for daytime hours (06:00-21:00 local time) in the wet season (December-January-February). MERRA-2 matches observations more closely than ERA for domain averaged composite diurnal statistics-specifically precipitation. However, ERA reproduces mesoscale features of OLR and precipitation phase associated with topography and the propagation of the coastal squall line. Both reanalysis models are shown to underestimate extreme convection.

Itterly, Kyle F.↗

Comparison of Space Launch System Aerodynamic Surface Pressure Measurements from Experimental Testing and CFD

A comparison of surface pressure coefficient measurements obtained using pressure-sensitive paint (PSP) measurements with predictions from the computational fluid dynamics (CFD) code FUN3D is presented for the NASA SLS Block 1B crew vehicle. Overall, the flow features over the SLS configuration were captured by both the PSP data and CFD data at freestream Mach numbers (M(sub ∞)) of 0.8 and 1.3. Overall, the flow features over the SLS are captured by the PSP data but the intensities of large pressure gradients are less intense than what was predicted by the CFD data. Several examples of this observation are given including the flow interaction at the booster nose cone edge, core body, and forward booster attachment hardware at M(sub ∞) = 0.8.

FUN3D↗

LiDAR-Based Map Relative Localization Performance Analysis for Landing on Europa

This paper presents preliminary simulations andanalyses done to assess the feasibility of performing Map RelativeLocalization (MRL) with the Europa Lander LiDAR beingdeveloped for the Europa Lander Pre-Phase A concept. MapRelative Localization is the process of determining the horizontalposition of a lander with respect to an onboard, a-priori map,by comparing the map to sensor observations of the terrain duringdeorbit, descent, and landing (DDL). Although kilometerscaleposition knowledge is commonly available during DDL,landing in hazard-rich environments requires position errors of100 m or less. Prior knowledge in the case of Europa Landerwill be visual and topographic maps collected by the upcomingEuropa Clipper mission. The Mars 2020 Lander Vision System(LVS) uses images from a camera to localize with respect tovisual maps. This technology, as well as a 3D imaging LiDAR indevelopment for hazard detection, is currently baselined for theEuropa Lander Pre-Phase A concept. This paper investigatesthe potential use of the hazard detection LiDAR to performMRL with respect to a 3D digital elevation model (DEM)provided by the Europa Clipper mission, as an alternative orbackup solution to passive optical MRL. Compared to passiveoptical MRL, one advantage of LiDAR-based localization isthat it is insensitive to lighting conditions, potentially relaxingrequirements on synchronizing map acquisition and landingtime of day. To analyze LiDAR based MRL performance,six representative terrains are synthetically up-sampled fromGalileo-derived maps of Europa to a resolution of 0.5 m/pxand covering an area of 4 km by 4 km. These maps are usedas ground-truth to generate simulated noisy a-priori onboardtopographic maps expected from Europa Clipper as well assimulated LiDAR DEMs generated at an altitude of 5 km duringEuropa Lander DDL. The simulated LiDAR DEM is matchedagainst the simulated map via 2D normalized cross-correlation,exploiting the accurately known spacecraft attitude to avoidthe need for more computationally intensive algorithms such asIterative Closest Point (ICP). Two sources of measurement errorare identified for analysis: 1) additive Gaussian noise in therange measurements from the Europa Lander LiDAR and theEuropa Clipper derived maps and 2) errors in the LiDAR DEMinduced by errors in the Europa Lander state estimate which isused to de-warp the LiDAR scan data into a DEM format. Weassess the effect of each of these types of errors independently onmatching performance as well as the overall performance whenall types of error are introduced. Additionally, we present theresult of a sensitivity study to terrain frequency content.

Trawny, Nikolas↗

Development of a phonon-based sampling method for thermal neutron scattering data

Simulations of reactor systems require access to accurate nuclear data. For many systems, thermal neutron scattering data can have large effects on the eigenvalue and neutron flux distributions. Inelastic thermal neutron scattering can excite or de-excite vibrational, rotational, and translational modes in a material, so thermal scattering evaluations are often obtained by summing over the number of phonons created/destroyed by a scattering event. In recent years, the thermal scattering cross sections and angular distributions have greatly improved in accuracy, but the format in which this data is delivered to simulation codes has remained virtually unchanged. Thermal scattering data is typically either compiled into large tables and sorted by incoming neutron energy, outgoing neutron energy, scattering angle, and material temperature, or represented as cumulative distribution functions of momentum exchange or energy exchange. Either method can be quite memory intensive when fine bins are used. In an effort to decrease the amount of space that processed thermal scattering data requires, an alternate format is proposed. The phonon-based sampling method introduced here can sample the number of phonons excited for each collision, the change in neutron energy, and the scattering angle while avoiding pre-computed angular bins and limiting the amount of data that is dependent on incoming energy. Through this method, the generation and storage of large interpolation tables is avoided, which could have benefits in both memory storage and accuracy. While the initial implementation of this method is slower than current alternatives, it is significantly more resistant to grid coarseness errors and has good potential for improvement. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

End-to-end online performance data capture and analysis for scientific workflows

With the increased prevalence of employing workflows for scientific computing and a push towards exascale computing, it has become paramount that we are able to analyze characteristics of scientific applications to better understand their impact on the underlying infrastructure and vice-versa. Such analysis can help drive the design, development, and optimization of these next generation systems and solutions. Here, we present the architecture, integrated with existing well-established and newly developed tools, to collect online performance statistics of workflow executions from various, heterogeneous sources and publish them in a distributed database (Elasticsearch). Using this architecture, we are able to correlate online workflow performance data, with data from the underlying infrastructure, and present them in a useful and intuitive way via an online dashboard. We have validated our approach by executing two classes of real-world workflows, both under normal and anomalous conditions. The first is an I/O-intensive genome analysis workflow; the second, a CPU- and memory-intensive material science workflow. Based on the data collected in Elasticsearch, we are able to demonstrate that we can correctly identify anomalies that we injected. The resulting end-to-end data collection of workflow performance data is an important resource of training data for automated machine learning analysis.

97 MATHEMATICS AND COMPUTING↗

Energy-consumption and carbon-emission analysis of vehicle and component manufacturing.

A model is presented for calculating the environmental burdens of the part manufacturing and vehicle assembly (VMA) stage of the vehicle life cycle. The approach is bottom-up, with a special focus on energy consumption and CO{sub 2} emissions. The model is applied to both conventional and advanced vehicles, the latter of which include aluminum-intensive, hybrid electric, plug-in hybrid electric and all-electric vehicles. An important component of the model, a weight-based distribution function of materials and associated transformation processes (casting, stamping, etc.), is developed from the United States Council for Automotive Research Generic Vehicle Life Cycle Inventory Study. As the approach is bottom-up, numerous transformation process data and plant operational data were extracted from the literature for use in representing the many operations included in the model. When the model was applied to conventional vehicles, reliable estimates of cumulative energy consumption (34 GJ/vehicle) and CO{sub 2} emission (2 tonnes/vehicle) were computed for the VMA life-cycle stage. The numerous data sets taken from the literature permitted the development of some statistics on model results. Because the model explicitly includes a greater coverage of relevant manufacturing processes than many earlier studies, our energy estimates are on the higher end of previously published values. Limitations of the model are also discussed. Because the material compositions of conventional vehicles within specific classes (cars, light duty trucks, etc.) are sensibly constant on a percent-by-weight basis, the model can be reduced to a simple linear form for each class dependent only on vehicle weight. For advanced vehicles, the material/transformation process distribution developed above needs to be adjusted for different materials and components. This is particularly so for aluminum-intensive and electric-drive vehicles. In fact, because of their comparatively high manufacturing energy, batteries required for an electric vehicle can significantly add to the energy burden of the VMA stage. Overall, for conventional vehicles, energy use and CO{sub 2} emissions from the VMA stage are about 4% of their total life-cycle values. They are expected to be somewhat higher for advanced vehicles.

36 MATERIALS SCIENCE↗

Inversion of coherent surface scattering images via deep learning network

Coherent surface scattering imaging is a powerful tool for imaging a surface/interface of a thin nanostructure deposited on an opaque substrate. A mathematical conversion of an object image from a scattering pattern is essential for coherent surface scattering imaging to visualize structures of specimens. It has been achieved by using phase retrieval algorithms requiring oversampling in scattering patterns and employing alternating projection approaches. It is a computationally challenging and time-consuming process. In this paper, we demonstrate CSSI-NN, which is a deep learning neural network model to predict images of objects from scattering intensities in coherent surface scattering imaging. This model allowing for the instant outcome from scattering patterns would be tremendously beneficial not only for effective experiments but also for data analysis of phase retrieval.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Lagged Diffusivity Method for Computing Total Variation Regularized Fluid Flow

There is a great deal of recent work using optical flow methods for analyzing the dynamics of fluids, and much attention has been paid to developing regularization schemes for variational approaches that are consistent with the physics of fluid flow. In this work we show that using total variation to regularize two different kinds of optical flow functionals leads to very good flow field reconstructions for the kinds of dynamical structures that appear in fluid flow. The first optical flow functional is the classical component-based conservation of intensity, and the second approach is to reconstruct the potential of the flow, rather than the flow components. In the two cases, total variation regularization corresponds to imposing different scientific priors on the solution, which we compute using a variation of the Lagged Diffusivity Fixed Point Iteration. Numerical details are presented, and the results are demonstrated on synthetic data and on a data-driven oceanic flow model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

LST and supporting technology

In order to realize the LST objectives of high angular resolution, extended wavelength coverage and faint object detection, the performance of the instruments must be matched to that of the telescope. To insure that adequate technology is available by 1976, an intensive SR & T program has been initiated which builds on previous work and is coordinated with work in other agencies. The primary areas of concern are detectors, on-board computers, and ultraviolet optical components. In the last area grating work is being emphasized. The on-board computer will be necessary to allow pre-processing of raw data and enable detector operation in a pulse counting mode. For detectors, the SEC Vidicon development will be continued but the use of solid-state arrays in the electron bombarded mode and channel plate detectors are being seriously considered. One challenging problem is to provide 2 K cooling to permit ultra-sensitive IR observations to be made.

Sobieski, S.↗

Electromagnetic ion cyclotron waves observed near the oxygen cyclotron frequency by ISEE 1 and 2

The first results of observations of ion cyclotron waves by the elliptically orbiting ISEE 1 and 2 pair of spacecraft are reported. The most intense waves (8 nT) were observed in the outer plasmasphere where convection drift velocities were largest and the Alfven velocity was a minimum. Wave polarization is predominantly left-handed with propagation almost parallel to the ambient magnetic field, and the spectral slot and polarization reversal predicted by cold plasma propagation theory are identified in the wave data. Computations of the experimental wave spectra during the passage through the plasmapause show that the spectral slots relate to the local plasma parameters, possibly suggesting an ion cyclotron wave growth source near the spacecraft. A regular wave packet structure seen over the first 30 min of the event is attributed to the modulation of this energy source by the Pc 5 waves seen at the same time.

Fraser, B. J.↗

Easy and Accessible Imaging Software

DATASTAR, Inc., of Picayune, Mississippi, has taken NASA s award-winning Earth Resources Laboratory Applications Software (ELAS) program and evolved it into a user-friendly desktop application and Internet service to perform processing, analysis, and manipulation of remotely sensed imagery data. NASA s Stennis Space Center developed ELAS in the early 1980s to process satellite and airborne sensor imagery data of the Earth s surface into readable and accessible information. Since then, ELAS information has been applied worldwide to determine soil content, rainfall levels, and numerous other variances of topographical information. However, end-users customarily had to depend on scientific or computer experts to provide the results, because the imaging processing system was intricate and labor intensive.

Source record↗

PIV and Rotational Raman-Based Temperature Measurements for CFD Validation in a Single Injector Cooling Flow

Film cooling is used in a wide variety of engineering applications for protection of surfaces from hot or combusting gases. The design of more efficient thin film cooling geometries/configurations could be facilitated by an ability to accurately model and predict the effectiveness of current designs using computational fluid dynamics (CFD) code predictions. Hence, a benchmark set of flow field property data were obtained for use in assessing current CFD capabilities and for development of better turbulence models. Both Particle Image Velocimetry (PIV) and spontaneous rotational Raman scattering (SRS) spectroscopy were used to acquire high quality, spatially-resolved measurements of the mean velocity, turbulence intensity and also the mean temperature and normalized root mean square (rms) temperatures in a single injector cooling flow arrangement. In addition to flowfield measurements, thermocouple measurements on the plate surface enabled estimates of the film effectiveness. Raman spectra in air were obtained across a matrix of radial and axial locations downstream from a 68.07 mm square nozzle blowing heated air over a range of temperatures and Mach numbers, across a 30.48 cm long plate equipped with a single injector cooling hole. In addition, both centerline streamwise 2-component PIV and cross-stream 3-component Stereo PIV data at 15 axial stations were collected in the same flows. The velocity and temperature data were then compared against Wind-US CFD code predictions for the same flow conditions. The results of this and planned follow-on studies will support NASA's development and assessment of turbulence models for heated flows.

Raman Scattering↗

PIV and Rotational Raman-Based Temperature Measurements for CFD Validation in a Single Injector Cooling Flow

Film cooling is used in a wide variety of engineering applications for protection of surfaces from hot or combusting gases. The design of more efficient thin film cooling geometries/configurations could be facilitated by an ability to accurately model and predict the effectiveness of current designs using computational fluid dynamics (CFD) code predictions. Hence, a benchmark set of flow field property data were obtained for use in assessing current CFD capabilities and for development of better turbulence models. Both Particle Image Velocimetry (PIV) and spontaneous rotational Raman scattering (SRS) spectroscopy were used to acquire high quality, spatially-resolved measurements of the mean velocity, turbulence intensity and also the mean temperature and normalized root mean square (rms) temperatures in a single injector cooling flow arrangement. In addition to flowfield measurements, thermocouple measurements on the plate surface enabled estimates of the film effectiveness. Raman spectra in air were obtained across a matrix of radial and axial locations downstream from a 68.07 mm square nozzle blowing heated air over a range of temperatures and Mach numbers, across a 30.48cm long plate equipped with a single injector cooling hole. In addition, both centerline streamwise 2-component PIV and cross-stream 3-component Stereo PIV data at 15 axial stations were collected in the same flows. The velocity and temperature data were then compared against Wind-US CFD code predictions for the same flow conditions. The results of this and planned follow-on studies will support NASA's development and assessment of turbulence models for heated flows.

Wernet, Mark P.↗

PIV and Rotational Raman-Based Temperature Measurements for CFD Validation in a Single Injector Cooling Flow

Film cooling is used in a wide variety of engineering applications for protection of surfaces from hot or combusting gases. The design of more efficient thin film cooling geometries/configurations could be facilitated by an ability to accurately model and predict the effectiveness of current designs using computational fluid dynamics (CFD) code predictions. Hence, a benchmark set of flow field property data were obtained for use in assessing current CFD capabilities and for development of better turbulence models. Both Particle Image Velocimetry (PIV) and spontaneous rotational Raman scattering (SRS) spectroscopy were used to acquire high quality, spatially-resolved measurements of the mean velocity, turbulence intensity and also the mean temperature and normalized root mean square (rms) temperatures in a single injector cooling flow arrangement. In addition to flowfield measurements, thermocouple measurements on the plate surface enabled estimates of the film effectiveness. Raman spectra in air were obtained across a matrix of radial and axial locations downstream from a 68.07 mm square nozzle blowing heated air over a range of temperatures and Mach numbers, across a 30.48cm long plate equipped with a single injector cooling hole. In addition, both centerline streamwise 2-component PIV and cross-stream 3-component Stereo PIV data at 15 axial stations were collected in the same flows. The velocity and temperature data were then compared against Wind-US CFD code predictions for the same flow conditions. The results of this and planned follow-on studies will support NASA's development and assessment of turbulence models for heated flows.

Turbulence Modeling↗

Review of Solar Energetic Particle Models

Solar Energetic Particle (SEP) events are interesting from a scientific perspective as they are the product of a broad set of physical processes from the corona out through the extent of the heliosphere, and provide insight into processes of particle acceleration and transport that are widely applicable in astrophysics. From the operations perspective, SEP events pose a radiation hazard for aviation, electronics in space, and human space exploration, in particular for missions outside of the Earth’s protective magnetosphere including to the Moon and Mars. Thus, it is critical to improve the scientific understanding of SEP events and use this understanding to develop and improve SEP forecasting capabilities to support operations. Many SEP models exist or are in development using a wide variety of approaches and with differing goals. These include computationally intensive physics-based models, fast and light empirical models, machine learning-based models, and mixed-model approaches. The aim of this paper is to summarize all of the SEP models currently developed in the scientific community, including a description of model approach, inputs and outputs, free parameters, and any published validations or comparisons with data.

Kathryn Whitman↗

Mie Scattering Analysis

Mie scattering theory describes how light scatters on a particle cloud when the particle size is approximately the same as the wavelength of scattered light. Assuming the particles generated in an ejecta experiment are spherical, one goal of such experiments is to determine the particle radii distribution, which in theory can be done by measuring intensities of scattered light at several different angles. The purpose of this report is the present an assessment of how closely the analysis of Mie scattering data in practice rejects the theoretical possibilities.

97 MATHEMATICS AND COMPUTING↗

Scientific Literature Mining for Experiment Information in Materials Design

Scientific literature is a plethora of documents written in natural language, where the agglomeration of well-cogitated knowledge is inextricably intertwined. The large-scale knowledge source might have the great potential to derive valuable information when text mined and untangled. Typically, scientists obtain preliminary knowledge from research papers prior to beginning a new experiment. Researchers manually harvest experimental information, which is labor-intensive and error prone. To reduce manual effort and human errors, this project aims to build a system for data collection from literature that supplements other data sources so users can look up needed information while preparing experiments or analyzing results.

97 MATHEMATICS AND COMPUTING↗