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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 19 records

Ocean feature recognition using genetic algorithms with fuzzy fitness functions (GA/F3)

A model for genetic algorithms with semantic nets is derived for which the relationships between concepts is depicted as a semantic net. An organism represents the manner in which objects in a scene are attached to concepts in the net. Predicates between object pairs are continuous valued truth functions in the form of an inverse exponential function (e sub beta lxl). 1:n relationships are combined via the fuzzy OR (Max (...)). Finally, predicates between pairs of concepts are resolved by taking the average of the combined predicate values of the objects attached to the concept at the tail of the arc representing the predicate in the semantic net. The method is illustrated by applying it to the identification of oceanic features in the North Atlantic.

Ankenbrandt, C. A.↗

A natural conservative flux difference splitting for the hyperbolic systems of gasdynamics

Gasdynamic hyperbolic systems are treated by a novel conservative flux difference splitting upwind method which is applicable to explicit or implicit and iterative or direct schemes, for marching in time or space with the Euler or compressible Navier-Stokes equations. The method is able to capture sharp shocks correctly by maintaining global conservation. The embedded characteristics formulation is cast in the volumetric internal energy primitive variable, which is effective for real as well as perfect gases. Higher order upwind formulae are constructed from the distribution of pieces of the simple internal flux difference splitting, and the method reverts to first order at the appropriate points in order not to violate the domain of dependence by differencing across discontinuities. At insignificant computational overhead, switching is done by simple algebraic extensions of the truth functions that determine upwind direction for the first order scheme.

Lombard, C. K.↗

On the fundamental structure of Galois switching functions

In connection with investigations conducted by Menger (1969), Benjauthrit and Reed (1976), and Pradhan (1978) two methods have been reported for deriving a unique Galois switching function from a given truth table description of the function. However, neither of the two methods appears satisfactory. One method often contains many redundant terms in its formulation, whereas the second method requires a great number of multiplications and additions. By some algebraic manipulations, an expanded formula is obtained which combines the best features of both methods. This formula makes it possible to compute the coefficients of the desired function more directly and probably with less effort. The conduction of calculations by means of the new formula is illustrated with the aid of examples.

Benjauthrit, B.↗

Misregistration's effects on classification and proportion estimation accuracy

The estimates of crop type and acreage are undertaken in the AgRISTARS program by registering multiple date acquisitions of small subareas of LANDSAT scenes (termed segments), and applying multispectral analysis to them. An important contribution to errors in classification and acreage estimates is misregistration between multiple acquisitions. The formula used to express this relationship is given and the operations applied are so shown in diagrams. The taking of a LANDSAT feature vector and the derivation of the brightness and greeness are illustrated. It is shown that for any given sensor IFOV geometry, typical populations of fields can be derived and histograms can be plotted of the number of fields against field size according to ground truth. As a function of the resolution element, the IFOV of the sensor can draw the proportion of pure pixels in a given crop. Because the thematic mapper has a smaller resolution, the proportion of pixels that are pure in any given area will be larger.

Juday, R. D.↗

Orbit Determination Toolbox

The Orbit Determination Toolbox is an orbit determination (OD) analysis tool based on MATLAB and Java that provides a flexible way to do early mission analysis. The toolbox is primarily intended for advanced mission analysis such as might be performed in concept exploration, proposal, early design phase, or rapid design center environments. The emphasis is on flexibility, but it has enough fidelity to produce credible results. Insight into all flight dynamics source code is provided. MATLAB is the primary user interface and is used for piecing together measurement and dynamic models. The Java Astrodynamics Toolbox is used as an engine for things that might be slow or inefficient in MATLAB, such as high-fidelity trajectory propagation, lunar and planetary ephemeris look-ups, precession, nutation, polar motion calculations, ephemeris file parsing, and the like. The primary analysis functions are sequential filter/smoother and batch least-squares commands that incorporate Monte-Carlo data simulation, linear covariance analysis, measurement processing, and plotting capabilities at the generic level. These functions have a user interface that is based on that of the MATLAB ODE suite. To perform a specific analysis, users write MATLAB functions that implement truth and design system models. The user provides his or her models as inputs to the filter commands. The software provides a capability to publish and subscribe to a software bus that is compliant with the NASA Goddard Mission Services Evolution Center (GMSEC) standards, to exchange data with other flight dynamics tools to simplify the flight dynamics design cycle. Using the publish and subscribe approach allows for analysts in a rapid design center environment to seamlessly incorporate changes in spacecraft and mission design into navigation analysis and vice versa.

Carpenter, James R.↗

Experiments at SRT Using the NOAA CrIS/ATMS Proxy Data Set

The objectives of the talk are: (1) Assess the performance of NGAS Version-1.5.03.00 CrIS/ATMS retrieval algorithm as delivered by LaRC, modified to include the MW and IR tuning coefficients and new CrIS noise model (a) Percent acceptance (b) RMS and mean differences of T(p) vs. ECMWF truth as a function of % yield (2) Compare performance of NGAS retrieval algorithm with an AIRS Science Team Version-6 like retrieval algorithm modified at Sounder Research Team (SRT) for CrIS/ATMS

Susskind, Joel↗

A Convolutional Neural Network for Enhancement of Multi-Scale Localization in Granular Metallic Representative Unit Cells

A convolutional neural network was used to enhance the localization of strain and stress for a generalized method of cells model of a metallic microstructure. Enhanced shear strains, measured in terms of the linear regression coefficients as a function of ground truth strains, were improved from inaccurate and uncorrelated (slope=0.003, Rsq=0.000) to accurate and well correlated (slope=0.890, Rsq=0.882) relative to ground truth (slope=1.0, Rsq=1.0). In applying the convolutional neural network, a convolutional stride of 1.0 (padding=’same’) was only modestly effective while strides of 2 or 3 were more effective yet at higher cost. Additional convolutional layers were generally more expensive than additional dense layers, often with limited benefit. The accuracy of enhanced localized shear strains and stress is expected to yield benefits for damage progression models, especially in the context of hierarchical multi-scale methods where the generalized method of cells is applied at the intermediate scale.

Machine Learning↗

Lunar Terrain Vehicle (LTV) Remote Teleoperation Studies Under Four Lunar Communication Latencies

Remotely operating a lunar rover from Earth while subject to an Earth-Moon time delay of multiple seconds could result in a dangerous state where the roving vehicle is either damaged or lost, thereby potentially compromising an entire mission or series of missions. Providing the right capabilities to the remote operator to manage inherent communication latencies will be important for remote driving to be successful. NASA conducted two studies to investigate the average speed and number of kilometers per day that an operator on Earth could teleoperate a notional Artemis unpressurized rover with minimal remote operator capabilities under 0- and 4-second communication delays (April 2023 study) and 6- and 8-second delays (August 2023 study). A primary goal of these studies was to understand if an Artemis Lunar Terrain Vehicle (LTV) could cover 6 kilometers (km) in 24 hours when operated remotely. During the April 2023 evaluation, eight test operators used an in-house simulation of the lunar surface South Pole to teleoperate a NASA government reference LTV. Each operator received approximately 30 minutes of remote driving familiarization/training prior to their test run. Operators viewed the surrounding terrain via a single, rover mast-mounted, high-resolution camera with pan/tilt/zoom capabilities; continuous communication was provided throughout all testing. In the August 2023 evaluation, remote operators received approximately 3 hours of familiarization training in each latency, and the simulation environment provided remote operators with an operator-selected rate limiter to enable finer sensitivity in the hand controller and a predictive circle function to better assist operators with predicting the path the vehicle could take. All test operators were able to successfully navigate and drive through six different types of terrain and five planned traverse scenarios using natural lighting under all communication delays. Results for average speeds for each communication delay, computed by averaging the data from all test conditions for that latency and all operators, are shown in the table below. The average speed data was then used to derive the total time needed to cover 6 km, 8 km, and 20 km (distances relevant to LTV-SYS071 and -029 requirements). Remote operators drove slower and used the brake more frequently when subject to a communication latency as opposed to no communication latency. Subjective workload assessments revealed that while operating in a latency the overall workload significantly increased when compared to a 0-s delay with mental demand, frustration, and performance being the primary contributing factors. Driving strategies in the 0-s delay did not vary significantly among subjects; however, in the 4-s delay condition, three different driving strategies were identified. In the 6-s and 8-s latency conditions the operator’s use of the cruise control to maintain speed was more apparent. Additionally, over the course of the August study, the operator took advantage of the predictive circle indicator on the navigation display and over 95% of the operator’s navigation used the mast camera 180-degree panning function for ground truthing in terms of boulders and craters. Operators started to define more specific parameters in driving strategies for general operations. This consisted of setting the vehicle into a low-speed cruise mode of approximately 11.5 kph and noticing driving performance of the vehicle seemed to be much harder at slower speeds 0.4–0.8 kph; however, the vehicle was more responsive at speeds of 2.9–3.6 kph. Regardless of communication delay, operators used both the horizontal translation rails and the vehicle fenders as guides to predict a path for the vehicle through heavily concentrated terrain features. Test operators acknowledged that the teleoperations training for this study was substantially less than what an actual LTV remote operator will ultimately receive. They estimated a minimum of 20 to 100 hours spread across multiple days and weeks (e.g., strategies included immersion training over a 3-day period, to a short 8-week starter program) would be needed to get an operator ~ 60% proficient (i.e., able to complete a subset of remote driving tasks), to a yearlong program for full proficiency in remote driving tasks under all terrain types and natural lighting conditions. Remotely operating a vehicle on another planetary body while subject to communication latency is a complex task. Speed, distance covered, time spent driving, time spent navigating, brake usage and rock contacts are all affected by operator workload, driving strategies, workstation ergonomics and training. These studies provided a “first-look” answer to a potential system requirement (namely if a remote operator could cover a given distance in a given amount of time); however, considerable general knowledge was gained to begin to understand what it will take to make a successful lunar rover teleoperator.

LTV↗

Lunar Terrain Vehicle (LTV) Remote Teleoperation Studies Under Four Lunar Communication Latencies

Remotely operating a lunar rover from Earth while subject to an Earth-Moon time delay of multiple seconds could result in a dangerous state where the roving vehicle is either damaged or lost, thereby potentially compromising an entire mission or series of missions. Providing the right capabilities to the remote operator to manage inherent communication latencies will be important for remote driving to be successful. The National Aeronautics and Space Administration (NASA) conducted two studies to investigate the average speed and number of kilometers per day that an operator on Earth could teleoperate a notional Artemis unpressurized rover with minimal remote operator capabilities under 0- and 4-second communication delays (April 2023 study) and 6- and 8-second delays (August 2023 study). A primary goal of these studies was to understand if an Artemis Lunar Terrain Vehicle (LTV) could cover 6 kilometers (km) in 24 hours when operated remotely. During the April 2023 evaluation, eight test operators used an in-house simulation of the lunar surface South Pole to teleoperate a NASA government reference LTV. Each operator received approximately 30 minutes of remote driving familiarization/training prior to their test run. Operators viewed the surrounding terrain via a single, rover mast-mounted, high-resolution camera with pan/tilt/zoom capabilities; continuous communication was provided throughout all testing. In the August 2023 evaluation, remote operators received approximately 3 hours of familiarization training in each latency, and the simulation environment provided remote operators with an operator-selected rate limiter to enable finer sensitivity in the hand controller and a predictive circle function to better assist operators with predicting the path the vehicle could take. All test operators were able to successfully navigate and drive through six different types of terrain and five planned traverse scenarios using natural lighting under all communication delays. Results for average speeds for each communication delay, computed by averaging the data from all test conditions for that latency and all operators, are shown in the table below. The average speed data was then used to derive the total time needed to cover 6 km, 8 km, and 20 km. Remote operators drove slower and used the brake more frequently when subject to a communication latency as opposed to no communication latency. Subjective workload assessments revealed that while operating in a latency the overall workload significantly increased when compared to a 0-s delay with mental demand, frustration, and performance being the primary contributing factors. Driving strategies in the 0-s delay did not vary significantly among subjects; however, in the 4-s delay condition, three different driving strategies were identified. In the 6-s and 8-s latency conditions the operator’s use of the cruise control to maintain speed was more apparent. Additionally, over the course of the August study, the operator took advantage of the predictive circle indicator on the navigation display and over 95% of the operator’s navigation used the mast camera 180-degree panning function for ground truthing in terms of boulders and craters. Operators started to define more specific parameters in driving strategies for general operations. This consisted of setting the vehicle into a low-speed cruise mode of approximately 1–1.5 kph and noticing driving performance of the vehicle seemed to be much harder at slower speeds 0.4–0.8 kph; however, the vehicle was more responsive at speeds of 2.9–3.6 kph. Regardless of communication delay, operators used both the horizontal translation rails and the vehicle fenders as guides to predict a path for the vehicle through heavily concentrated terrain features. Test operators acknowledged that the teleoperations training for this study was substantially less than what an actual LTV remote operator will ultimately receive. They estimated a minimum of 20 to 100 hours spread across multiple days and weeks (e.g., strategies included immersion training over a 3-day period, to a short 8-week starter program) would be needed to get an operator ~ 60% proficient (i.e., able to complete a subset of remote driving tasks), to a yearlong program for full proficiency in remote driving tasks under all terrain types and natural lighting conditions. Remotely operating a vehicle on another planetary body while subject to communication latency is a complex task. Speed, distance covered, time spent driving, time spent navigating, brake usage and rock contacts are all affected by operator workload, driving strategies, workstation ergonomics and training. These studies provided a “firstlook” answer to a potential system requirement (namely if a remote operator could cover a given distance in a given amount of time); however, considerable general knowledge was gained to begin to understand what it will take to make a successful lunar rover teleoperator.

LTV↗

Correlation function studies for snow and ice

The random medium model is used to characterize snow and ice fields in the interpretation of active and passive microwave remote sensing data. A correlation function is used to describe the random permittivity fluctuations with the associated mean and variance and correlation lengths; and several samples are investigated to determine typical correlation functions for snow and ice. It is shown that correlation functions are extracted directly from appropriate ground truth data, and an exponential correlation function is observed for snow and ice with lengths corresponding to the actual size of ice particles or air bubbles. Thus, given that a medium has spatially stationary statistics and a small medium, the random medium model can interpret remote sensing data where theoretical parameters correspond to actual physical parameters of the terrain.

Vallese, F.↗

Ground Testing of the MISSE-16 Materials

The harsh space environment imposes very stringent requirements upon spacecraft materials, especially those located on exterior surfaces of space objects in low Earth orbit (LEO). As humankind moves from space exploration to space commercialization, these materials may have to last for 15–20 years without considerable degradation of their optical, electrical, mechanical, and thermal properties. Operational requirements dictate that these materials continue to function according to expectations. Hence, we must understand the effects of the space environment on materials currently in use as well as on untested materials. For the years, the Materials International Space Station Experiment Flight Facility (MISSE-FF) have flown many different materials to investigate the effect of LEO space weather exposure on the performance and durability of materials and devices. The MISSE-16 scientific team members plan to launch fifteen different novel and well-characterized spacecraft-relevant materials to the LEO environment for a duration of six months during the MISSE-16 mission. Changes in spectral reflectivity will be measured throughout the mission as the samples are exposed to the space environment. The same chemical damage the produces changes in optical reflectance also causes changes in numerous other physical properties such as electrical conductivity, mechanical strength, and chemical reactivity. Correlation of the changes in each of these properties as a function of radiation type, flux, and fluence allows various material properties to be inferred from one experimentally tractable measurement: color change. Flying identical test fixtures on the ram, zenith, and wake positions of the MISSE-FF, collecting spectrally resolved images of the materials, and concomitantly measuring the ambient space environment allows deconvolution of the material effects which occur as a result of exposure to neutral atomic oxygen (AO), unfiltered solar ultraviolet (UV) radiation, and electrons. The flight experiment will function as a ground truth reference for our team’s ongoing laboratory-based space weather-material interactions experiments. Comparison of the MISSE-16 data with extensive testing of “flight-duplicate” samples under simulated space weather conditions will enable development of chemical models for prediction of material degradation. This paper discusses preliminary results from the ground test campaign including measurements of UV/VIS/IR reflectance spectra, bidirectional reflectance distribution function (BRDF), surface potential decay, and surface morphology under electron and AO exposure.

Elena A. Plis↗

An analysis of mesoscale VAS retrievals using statistical structure functions

Mesoscale sounding data from a truth rawinsonde network and a VAS from March 6-7, 1982 are statistically studied. The parameters of temperature, geopotential height, and mixing ratio at 850, 700, 500, 300, and 200 mb levels, and thickness and precipitable water are examined. The VAS retrieval gradients derived from a physical algorithm and from a regression technique are analyzed; the analysis reveals that both techniques have similar error characteristics and capabilities for calculating gradients of mesoscale temperature and geopotential height. Ground-truth rawinsonde data and VAS retrievals are compared; it is observed that VAS data describes weaker gradients than rawinsonde data.

Fuelberg, H. E.↗

Geodetic analysis of Skylab altimetry preliminary data - SL/2 EREP pass 9

The author has identified the following significant results. The analysis was based on a time series intrinsic relationship between the satellite ephemeris, altimeter measured ranges, and the corresponding a priori values of subsatellite geoidal heights. Using sequential least squares processing with parameter weighting, the objective was to recover (1) the absolute geoidal heights of the subsatellite points, and (2) the associated altimeter calibration constant(s). Preliminary results from Skylab altimetry are given, using various combinations of orbit ephemeris and altimeter ranges as computed differently by NASA/JSC and NASA/Wallops. The influences of orbit accuracy, weighting functions, and a priori ground truth are described, based on the various combination solutions. It is shown that to deduce geoidal height by merely subtracting the height of the satellite from the altimeter range is inadmissible. The results of such direct subtraction can be very misleading if the orbit used is computed from data that included altimeter data used as height constraints. In view of the current state of knowledge, the use of geodetic ground truth samples as control benchmarks appears indispensable for the recovery of absolute geoidal heights with correct scale.

Mourad, A. G.↗

Software for Simulation of Hyperspectral Images

A package of software generates simulated hyperspectral images for use in validating algorithms that generate estimates of Earth-surface spectral reflectance from hyperspectral images acquired by airborne and spaceborne instruments. This software is based on a direct simulation Monte Carlo approach for modeling three-dimensional atmospheric radiative transport as well as surfaces characterized by spatially inhomogeneous bidirectional reflectance distribution functions. In this approach, 'ground truth' is accurately known through input specification of surface and atmospheric properties, and it is practical to consider wide variations of these properties. The software can treat both land and ocean surfaces and the effects of finite clouds with surface shadowing. The spectral/spatial data cubes computed by use of this software can serve both as a substitute for and a supplement to field validation data.

Richtsmeier, Steven C.↗

Simulation of Hyperspectral Images

A software package generates simulated hyperspectral imagery for use in validating algorithms that generate estimates of Earth-surface spectral reflectance from hyperspectral images acquired by airborne and spaceborne instruments. This software is based on a direct simulation Monte Carlo approach for modeling three-dimensional atmospheric radiative transport, as well as reflections from surfaces characterized by spatially inhomogeneous bidirectional reflectance distribution functions. In this approach, "ground truth" is accurately known through input specification of surface and atmospheric properties, and it is practical to consider wide variations of these properties. The software can treat both land and ocean surfaces, as well as the effects of finite clouds with surface shadowing. The spectral/spatial data cubes computed by use of this software can serve both as a substitute for, and a supplement to, field validation data.

Richsmeier, Steven C.↗

Spacecraft Material Characterization Using Reflectance Spectra Extracted from RGB/IR Color Images

The space environment is detrimental to the exterior of the spacecraft and imposes stringent requirements on spacecraft materials. Space materials are often expected to perform for 15-20 years in the harsh space environment without significant degradation of their optical, electrical, mechanical and thermal properties. Further, as commercial activities increase in the space domain, development of predictive capability for material evolution is critical for agile adaption of novel materials. Therefore, it is very important to understand the effects of the space environments on the spacecraft materials. The Materials on the International Space Station Experiment Flight Facility (MISSE-FF) has flown numerous material samples to investigate the effect of LEO space weather exposure on the performance and durability of materials and devices. We are manifest on the MISSE-16 mission, scheduled to launch in June 2022, to fly fifteen novel and well-characterized materials in the LEO environment for a duration of six months. Changes in spectral reflectivity will be measured in real time throughout the mission with an RGB/IR camera. These time-resolved data will function as a "space-truth" reference for our team's ongoing laboratory-based space weather-material interaction experiments. Correlation of the MISSE-16 data with extensive ground testing of duplicate samples under simulated space weather conditions will enable development of fundamental chemical models for material degradation. This paper discusses preliminary results from the ground test campaign to collect the RGB/IR images for pristine and damaged materials and the development of machine learning algorithms to extract reflectance spectra from the color images.

Jainisha R. Shah↗

Spacecraft Material Characterization Using Reflectance Spectra Extracted from RGB/IR Color Images

The space environment is detrimental to the exterior of the spacecraft and imposes stringent requirements on spacecraft materials. Space materials are often expected to perform for 15-20 years in the harsh space environment without significant degradation of their optical, electrical, mechanical and thermal properties. Further, as commercial activities increase in the space domain, development of predictive capability for material evolution is critical for agile adaption of novel materials. Therefore, it is very important to understand the effects of the space environments on the spacecraft materials. The Materials on the International Space Station Experiment Flight Facility (MISSE-FF) has flown numerous material samples to investigate the effect of LEO space weather exposure on the performance and durability of materials and devices. We are manifest on the MISSE-16 mission, scheduled to launch in June 2022, to fly fifteen novel and well-characterized materials in the LEO environment for a duration of six months. Changes in spectral reflectivity will be measured in real time throughout the mission with an RGB/IR camera. These time-resolved data will function as a "space-truth" reference for our team's ongoing laboratory-based space weather-material interaction experiments. Correlation of the MISSE-16 data with extensive ground testing of duplicate samples under simulated space weather conditions will enable development of fundamental chemical models for material degradation. This paper discusses preliminary results from the ground test campaign to collect the RGB/IR images for pristine and damaged materials and the development of machine learning algorithms to extract reflectance spectra from the color images.

Jainisha R. Shah↗