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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 523 records · Page 29

Multispectral combination and display of ERTS-1 data

Standard NASA color composites combine the most relevant 3 bands from the 4 MSS bands available. An alternate approach is to extract the principal components of the data by a linear transformation of the 4 bands. This approach leads to a low dimensionality representation of ERTS-1 data with the least degradation, in the mean square sense, of the radiometric accuracy. The technique has been applied with success to ERTS-1 MSS data for several geographic areas in California. For all examples considered the mean square representation error is less than one percent. By combining this dimensionality reduction which our previous results on image enhancement for visual display, color composites are obtained which contain and display most of the information provided by the ERTS-1 sensors.

Algazi, V. R.↗

An ellipsoidal representation of human hand anthropometry

Anthropometric data concerning the heometry of the hand's surface are presently modeled as a function of gross external hand measurements; an effort is made to evaluate the accuracy with which ellipsoids describe the geometry of the hand segments. Graphical comparisons indicate that differences between the ellipsoidal approximations and the breadth and depth measurements were greatest near the joints. On the bases of the present data, a set of overlapping ellipsoids could furnish a more accurate representation of hand geometry for adaptation to ellipsoid segment-geometry employing biomechanical models.

Buchholz, Bryan↗

Data reduction through optimized scalar quantization for more compact neural networks

Raw data generation for several existing and planned large physics experiments now exceeds TB/s rates, generating untenable data sets in very little time. Those data often demonstrate high dimensionality while containing limited information. Meanwhile, Machine Learning algorithms are now becoming an essential part of data processing and data analysis. Those algorithms can be used offline for post processing and post data analysis, or they can be used online for real time processing providing ultra low latency experiment monitoring. Both use cases would benefit from data throughput reduction while preserving relevant information: one by reducing the offline storage requirements by several orders of magnitude and the other by allowing ultra fast online inferencing with low complexity Machine Learning models. Moreover, reducing the data source throughput also reduces material cost, power and data management requirements. In this work we demonstrate optimized nonuniform scalar quantization for data source reduction. This data reduction allows lower dimensional representations while preserving the relevant information of the data, thus enabling high accuracy Tiny Machine Learning classifier models for online fast inferences. We demonstrate this approach with an initial proof of concept targeting the CookieBox, an array of electron spectrometers used for angular streaking, that was developed for LCLS-II as an online beam diagnostic tool. We used the Lloyd-Max algorithm with the CookieBox dataset to design an optimized nonuniform scalar quantizer. Optimized quantization lets us reduce input data volume by 69% with no significant impact on inference accuracy. When we tolerate a 2% loss on inference accuracy, we achieved 81% of input data reduction. Finally, the change from a 7-bit to a 3-bit input data quantization reduces our neural network size by 38%.

97 MATHEMATICS AND COMPUTING↗

Graphical Planning Of Spacecraft Missions

Mission Planning Graphical Tool (MPGT) computer program provides analysts with graphical representations of spacecraft and environmental data used in planning missions. Designed to be generic software tool configured to analyze any specified Earth-orbiting spacecraft mission. Data presented as series of overlays on top of two-dimensional or three-dimensional projection of Earth. Includes spacecraft-orbit tracks, ground-station-antenna masks, solar and lunar ephemerides, and coverage by Tracking Data and Relay Satellite System (TDRSS). From graphical representations, analyst determines such spacecraft-related constraints as communication coverage, infringement upon zones of interference, availability of sunlight, and visibility of targets to instruments.

Jeletic, J. F.↗

Attributes of GRB Pulses: Analysis of BATSE TTE Data

Our extensive program of modeling GRB profiles is aimed at elucidating the physical processes responsible for the burst itself, as well as possible extrinsic phenomena (e.g. time dilation) as discussed in another paper in this Symposium (Norris et al., "GRB PROFILES AS COSMIC PROBES"). We have developed special methods to extract the wealth of short time-scale information contained in the BATSE time-tag event (TTE) data. Our algorithm yields a piecewise-constant representation of the light curve -- using only the raw photon arrival times, and based on Bayesian change-point methods. This representation in effect lets the data determine the bin size and location, and avoids unwanted effects due to arbitrary choices of the bin parameters. We have determined widths, separations, and amplitudes of pulses contained in the bursts, without invoking a specific pulse model. The effect of cosmic time dilation can be easily seen in a direct plot of amplitude vs. time scale for individual pulses, without the need to lump the data into a small number of brightness classes. We are also performing noise equalization on these data (to reduce a well-known bias of pulse width as a function of signal-to-noise ratio), as well as fits of parametric pulse-shape models -- including explicit energy dependence of the pulse parameters. Such refinements are expected to improve the quality and physical significance of these results.

Norris, J. P.↗

On-the-fly Doppler broadening of unresolved resonance region cross sections

In this paper, two methods for computing temperature-dependent unresolved resonance region cross sections on-the-fly within continuous-energy Monte Carlo neutron transport simulations are presented. The first method calculates Doppler broadened cross sections directly from zero-temperature average resonance parameters. In a simulation, at each event that requires cross section values, a realization of unresolved resonance parameters is generated about the desired energy and temperature-dependent single-level Breit-Wigner resonance cross sections are computed directly via the analytical Ψ-x Doppler integrals. The second method relies on the generation of equiprobable cross section magnitude bands on an energy-temperature mesh. Within a simulation, the bands are sampled and interpolated in energy and temperature to obtain cross section values on-the-fly. Both of the methods, as well as their underlying calculation procedures, are verified numerically in extensive code-to-code comparisons. Energy-dependent pointwise cross sections calculated with the newly-implemented procedures are shown to be in excellent agreement with those calculated by a widely-used nuclear data processing code. Relative differences at or below 0.1% are observed. Integral criticality benchmark results computed with the proposed methods are shown to reproduce those computed with a state-of-the-art processed nuclear data library very well. In simulations of fast spectrum systems which are highly-sensitive to the representation of cross section data in the unresolved region, k-eigenvalue and neutron flux spectra differences of <10 pcm and <1.0% are observed, respectively. The direct method is demonstrated to be well-suited to the calculation of reference solutions — against which results obtained with a discretized representation may be assessed — as a result of its treatment of the energy, temperature, and cross section magnitude variables as continuous. Also, because there is no pre-processed data to store (only temperature-independent average resonance parameters) the direct method is very memory-efficient. Typically, only a few kB of memory are needed to store all required unresolved region data for a single nuclide. However, depending on the details of a particular simulation, performing URR cross section calculations on-the-fly can significantly increase simulation times. Alternatively, the method of interpolating equiprobable probability bands is demonstrated to produce results that are as accurate as the direct reference solutions, to within arbitrary precision, with high computational efficiency in terms of memory requirements and simulation time. Analyses of a fast spectrum system show that interpolation on a coarse energy-temperature mesh can be used to reproduce reference k-eigenvalue results obtained with cross sections calculated continuously in energy and directly at an exact temperature to within <10 pcm. Probability band data on a mesh encompassing the range of temperatures relevant to reactor analysis usually require around 100 kB of memory per nuclide. Finally, relative to the case in which probability table data generated at a single, desired temperature are used, minor increases in simulation times are observed when probability band interpolation is employed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Stochastic Stability of Sampled Data Systems with a Jump Linear Controller

In this paper an equivalence between the stochastic stability of a sampled-data system and its associated discrete-time representation is established. The sampled-data system consists of a deterministic, linear, time-invariant, continuous-time plant and a stochastic, linear, time-invariant, discrete-time, jump linear controller. The jump linear controller models computer systems and communication networks that are subject to stochastic upsets or disruptions. This sampled-data model has been used in the analysis and design of fault-tolerant systems and computer-control systems with random communication delays without taking into account the inter-sample response. This paper shows that the known equivalence between the stability of a deterministic sampled-data system and the associated discrete-time representation holds even in a stochastic framework.

Gonzalez, Oscar R.↗

A detailed experimental and modeling comparison of molecular radiative heat loss in a spark-ignition engine

Radiative heat transfer has been chiefly considered negligible in internal combustion engines, except for Diesel engines where soot radiation was recognized as a significant radiative transfer source. Only more recently, detailed simulations have shown that molecular radiation can be substantial as well. In extension to this, molecular radiative heat transfer can reach detectable levels of about 5–10% of the total heat transfer in spark-ignited engines. The broadband radiative nature of the significant emitting molecules, carbon dioxide and water, makes it necessary to address whether radiative trapping plays a substantial role in either total heat loss or energy redistribution within the cylinder. An experimental setup that allows measurements of the infrared emissions at a 2-crank-angle-degree resolution was developed to determine the importance of radiative trapping by carbon dioxide and water. Measurements were conducted in the well-characterized and documented TCC-III engine at the University of Michigan. The engine operated on a stoichiometric propane/air mixture at a speed of 1,300 RPM. Large Eddy Simulations with added line-by-line photon Monte-Carlo simulations of the molecular radiation were an integral part of this study to plan and devise the measurements. Post-processing of the simulation data included an accurate representation of the experimental volume from where infrared signals are collected. Additionally, the experimental data were used for validation of the photon Monte-Carlo simulations. Joint analysis of experimental and simulated spectra allowed quantifying the significance of radiative trapping. Results show the significant role of radiative trapping when predicting radiative heat transfer in the TCC-III engine.

42 ENGINEERING↗

An Extensible, Interchangeable and Sharable Database Model for Improving Multidisciplinary Aircraft Design

Crucial to an efficient aircraft simulation-based design is a robust data modeling methodology for both recording the information and providing data transfer readily and reliably. To meet this goal, data modeling issues involved in the aircraft multidisciplinary design are first analyzed in this study. Next, an XML-based. extensible data object model for multidisciplinary aircraft design is constructed and implemented. The implementation of the model through aircraft databinding allows the design applications to access and manipulate any disciplinary data with a lightweight and easy-to-use API. In addition, language independent representation of aircraft disciplinary data in the model fosters interoperability amongst heterogeneous systems thereby facilitating data sharing and exchange between various design tools and systems.

Lin, Risheng↗

A flexible class of priors for orthonormal matrices with basis function-specific structure

Statistical modeling of high-dimensional matrix-valued data motivates the use of a low-rank representation that simultaneously summarizes key characteristics of the data and enables dimension reduction. Low-rank representations commonly factor the original data into the product of orthonormal basis functions and weights, where each basis function represents an independent feature of the data. However, the basis functions in these factorizations are typically computed using algorithmic methods that cannot quantify uncertainty or account for basis function correlation structure a priori. While there exist Bayesian methods that allow for a common correlation structure across basis functions, empirical examples motivate the need for basis function-specific dependence structure. We propose a prior distribution for orthonormal matrices that can explicitly model basis function-specific structure. The prior is used within a general probabilistic model for singular value decomposition to conduct posterior inference on the basis functions while accounting for measurement error and fixed effects. We discuss how the prior specification can be used for various scenarios and demonstrate favorable model properties through synthetic data examples. Finally, we apply our method to two-meter air temperature data from the Pacific Northwest, enhancing our understanding of the Earth system’s internal variability.

97 MATHEMATICS AND COMPUTING↗

Sensitivity of Middle Atmospheric Analyses to the Representation of Gravity-Wave Drag in the DAO's Data Assimilation System

The damping of mesoscale gravity waves has important effects on the global circulation, structure, and composition of the atmosphere. A number of assimilation and forecast experiments have been conducted to examine the sensitivity of meteorological analyses and forecasts to the representation of gravity wave impacts in a data assimilation system (DAS). The experiments were conducted with the Finite-Volume (FV) DAS developed at NASA's Data Assimilation Office (DAO), The main purpose of this research is to determine the optimal combination of wave number, phase speed, wavelength, etc. for representing gravity-wave drag (GWD) in FVDAS. The GWD included in FVDAS includes a spectrum of waves, as would be forced by topography and transient motions (e.g., convection) in the troposphere. The sensitivity experiments are performed by modifying several parameters, such as the number of waves allowed, their wavelength, the background stress amplitude, etc. The results show that the assimilated fields are very sensitive to the number of gravity waves represented in the system, especially at high latitudes of the middle and upper stratosphere and mesosphere in winter. The analyzed stratopause temperature varies by up to 10K when the GWD scheme is modified from a multiple-wave scheme (using a stationary wave and waves with phase speeds of 10, 20, 30 and 40 m/s in each direction) to a single, stationary wave. Insight into the reality of the various versions of the GWD can be obtained by examining the "Observation minus Forecast" residuals from the FVDAS.

Li, Shuhua↗

Preprocessing: Geocoding of AVIRIS data using navigation, engineering, DEM, and radar tracking system data

Remotely sensed data have geometric characteristics and representation which depend on the type of the acquisition system used. To correlate such data over large regions with other real world representation tools like conventional maps or Geographic Information System (GIS) for verification purposes, or for further treatment within different data sets, a coregistration has to be performed. In addition to the geometric characteristics of the sensor there are two other dominating factors which affect the geometry: the stability of the platform and the topography. There are two basic approaches for a geometric correction on a pixel-by-pixel basis: (1) A parametric approach using the location of the airplane and inertial navigation system data to simulate the observation geometry; and (2) a non-parametric approach using tie points or ground control points. It is well known that the non-parametric approach is not reliable enough for the unstable flight conditions of airborne systems, and is not satisfying in areas with significant topography, e.g. mountains and hills. The present work describes a parametric preprocessing procedure which corrects effects of flight line and attitude variation as well as topographic influences and is described in more detail by Meyer.

Meyer, Peter↗

Proprocessing: Geocoding of AVIRIS Data Using Navigation, Engineering, DEM, and Radar Tracking System Data

Remotely sensed data have geometric characteristics and representation which depend on the type of the acquisition system used. To correlate such data over large regions with other real world representation lools like conventional maps or Geographic Information Systems (GIS) for verification purposes, or for further treatment within different data sets, a coregistration has to be performed.

topography stability of the platform sensor flight↗

The Hybrid Toolkit

The Hybrid Toolkit facilitates moving research algorithms into a production environment by creating useful abstractions that separate analytics developers from the intricacies of the production data formats, data flows, and result representations. The toolkit also assists developers with activities such as creating analysis feature vectors, converting between data structures, and creating data pipelines.

Davis IV, WarrenL↗

Development of a Simulated Data Set for the SeaWiFS Mission

A realistic simulated data set is essential for mission readiness preparations and can potentially assist in all phases of ground support for a future mission. Such a data set was created for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), a global ocean color mission due for launch in 1997. This data set incorporates a representation of virtually every known aspect of the flight mission. Thus, it provides a high fidelity data set for testing most phases of the ground system, Including data processing, data transfers, calibration and validation, quality control, and mission operations. The data set is constructed for a seven-day period, March 25-31, 1994. Specific features of the data set: it includes Global Area Coverage (GAC), recorded Local Area Coverage (LAC), and real-time High Resolution Picture Transmission (HRFIT) data for the seven-day period; it includes a realistic orbit which is propagated using a Brouwer-Lyddane model with drag; the data correspond to a command schedule based on the orbit for this seven-day period; it includes total (at-satellite) radiances for ocean, land, clouds, and ice; it utilizes a high-resolution land/sea mask; it includes actual SeaWiFS spectral responses; it includes the actual sensor saturation responses; it is formatted according to current onboard data structures; and it includes corresponding telemetry (instrument and spacecraft) data. The methods are described and some examples of the output are given.

Gregg, Watson W.↗

A Global Land Cover Training Dataset From 1984 to 2020

State-of-the-art cloud computing platforms such as Google Earth Engine (GEE) enable regional-to-global land cover and land cover change mapping with machine learning algorithms. However, collection of high-quality training data, which is necessary for accurate land cover mapping, remains costly and labor-intensive. To address this need, we created a global database of nearly 2 million training units spanning the period from 1984 to 2020 for seven primary and nine secondary land cover classes. Our training data collection approach leveraged GEE and machine learning algorithms to ensure data quality and biogeographic representation. We sampled the spectral-temporal feature space from Landsat imagery to efficiently allocate training data across global ecoregions and incorporated publicly available and collaborator-provided datasets to our database. To reflect the underlying regional class distribution and post-disturbance landscapes, we strategically augmented the database. We used a machine learning-based cross-validation procedure to remove potentially mis-labeled training units. Our training database is relevant for a wide array of studies such as land cover change, agriculture, forestry, hydrology, urban development, among many others.

Radost Stanimirova↗