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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

The epoch state navigation filter

The formulation of a recursive maximum likelihood navigation system employing reference position and velocity vectors as state variables is presented. Convenient forms of the required variational equations of motion are developed together with an explicit form of the associated state transition matrix needed to refer measurement data from the measurement time to the epoch time. Computational advantages accrue from this design in that the usual forward extrapolation of the covariance matrix of estimation errors can be avoided without incurring unacceptable system errors. Simulation data for earth orbiting satellites are provided to substantiate this assertion.

Battin, R. H.↗
NASA NTRS1989

Passive navigation using image irradiance tracking

Rotorcraft operating at low altitudes require navigational schemes for locating the terrain and obstacles. Due to the covert nature of missions to be accomplished, a passive navigation scheme is desirable. This paper describes the development of a passive navigation scheme combining image sequences from a vehicle mounted camera with vehicle motion variables. Geometric properties of perspective projection together with an image irradiance tracking scheme at each pixel are used to determine the range to various objects within the field-of-view. Derivation of the numerical algorithm and simulation results are given. Other applications of the proposed approach include navigation for autonomous planetary rovers and telerobots.

Menon, P. K. A.↗
DOE OSTI2021

Navigating Transition-Metal Chemical Space: Artificial Intelligence for First-Principles Design

Conspectus The variability of chemical bonding in open-shell transition-metal complexes not only motivates their study as functional materials and catalysts but also challenges conventional computational modeling tools. Here, tailoring ligand chemistry can alter preferred spin or oxidation states as well as electronic structure properties and reactivity, creating vast regions of chemical space to explore when designing new materials atom by atom. Although first-principles density functional theory (DFT) remains the workhorse of computational chemistry in mechanism deduction and property prediction, it is of limited use here. DFT is both far too computationally costly for widespread exploration of transition-metal chemical space and also prone to inaccuracies that limit its predictive performance for localized d electrons in transition-metal complexes. These challenges starkly contrast with the well-trodden regions of small-organic-molecule chemical space, where the analytical forms of molecular mechanics force fields and semiempirical theories have for decades accelerated the discovery of new molecules, accurate DFT functional performance has been demonstrated, and gold-standard methods from correlated wavefunction theory can predict experimental results to chemical accuracy. The combined promise of transition-metal chemical space exploration and lack of established tools has mandated a distinct approach. In this Account, we outline the path we charted in exploration of transition-metal chemical space starting from the first machine learning (ML) models (i.e., artificial neural network and kernel ridge regression) and representations for the prediction of open-shell transition-metal complex properties. The distinct importance of the immediate coordination environment of the metal center as well as the lack of low-level methods to accurately predict structural properties in this coordination environment first motivated and then benefited from these ML models and representations. Once developed, the recipe for prediction of geometric, spin state, and redox potential properties was straightforwardly extended to a diverse range of other properties, including in catalysis, computational “feasibility”, and the gas separation properties of periodic metal–organic frameworks. Interpretation of selected features most important for model prediction revealed new ways to encapsulate design rules and confirmed that models were robustly mapping essential structure–property relationships. Encountering the special challenge of ensuring that good model performance could generalize to new discovery targets motivated investigation of how to best carry out model uncertainty quantification. Distance-based approaches, whether in model latent space or in carefully engineered feature space, provided intuitive measures of the domain of applicability. With all of these pieces together, ML can be harnessed as an engine to tackle the large-scale exploration of transition-metal chemical space needed to satisfy multiple objectives using efficient global optimization methods. In practical terms, bringing these artificial intelligence tools to bear on the problems of transition-metal chemical space exploration has resulted in ML-model assessments of large, multimillion compound spaces in minutes and validated new design leads in weeks instead of decades.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2004

Ionospheric Variability and Storms on Mars

The goal of this grant was to conduct the first-ever study of ionospheric variability on Mars. To do so, we used data from the Radio Science (RS) experiment onboard the Mars Global Surveyor (MGS) satellite. Dr. David Hinson of the RS team at Stanford University was a most helpful and valuable colleague throughout the studies we conducted. For the initial RS datasets available from the MGS mission, there were no severe storms caused by solar wind activity, so we concentrated on day-to-day effects. This turned out to be a wise approach since understanding "normal variability" had to be done before any claim could be made about "space weather" effects. Our approach was three-fold: (1) select a good dataset for characterization of ionosphere variability at Mars, one for which excellent terrestrial data were also available. This turned out to be the period 9-27 March 1999; (2) once the variability at Mars was described, develop and use a new photochemical model of the martian ionosphere to find the extent to which solar variability on those days caused or contributed to the observed patterns; (3) use the results from the above, together with additional datasets from the MGS/RS experiment, to describe some practical consequences that the martian ionosphere would have upon NASA s proposed navigation and communications systems for Mars. The results of these studies showed that: (a) solar variability is the dominant source of ionospheric variability at Mars (during periods of quiet solar wind), (b) that current models do a good job in portraying such effects at the height of the ionospheric peak electron density, and (c) that ionospheric structure on Mars can affect attempts at precise position-fixing at Mars should relatively high (GPS-like) frequencies not be used in a Mars communications and navigation system.

Mendillo, Michael↗
NASA NTRS1978

A stochastic analysis of terrain evaluation variables for path selection

A stochastic analysis was performed on the variables associated with the characteristics of the terrain encountered by a roving system with an autonomous navigation system. A laser rangefinder is employed to detect terrain features at ranges up to 75 m. Analytic expressions and a numerical scheme were developed to calculate the variance of data on these four variables: (1) body clearance, (2) in-path slope, (3) tilt slope, and (4) wheel deviation. The variance is due to noise in the range data. It was found that the standard deviation of these terrain variables is large enough to warrant the use of a safety margin to aid the roving vehicle in avoiding high risk areas.

Donohue, J. G.↗
DOE OSTI2024

Multivariate Bayesian Optimization of CoO Nanoparticles for CO 2 Hydrogenation Catalysis

The hydrogenation of CO 2 holds promise for transforming the production of renewable fuels and chemicals. However, the challenge lies in developing robust and selective catalysts for this process. Transition metal oxide catalysts, particularly cobalt oxide, have shown potential for CO 2 hydrogenation, with performance heavily reliant on crystal phase and morphology. Achieving precise control over these catalyst attributes through colloidal nanoparticle synthesis could pave the way for catalyst and process advancement. Yet, navigating the complexities of colloidal nanoparticle syntheses, governed by numerous input variables, poses a significant challenge in systematically controlling resultant catalyst features. We present a multivariate Bayesian optimization, coupled with a data-driven classifier, to map the synthetic design space for colloidal CoO nanoparticles and simultaneously optimize them for multiple catalytically relevant features within a target crystalline phase. The optimized experimental conditions yielded small, phase-pure rock salt CoO nanoparticles of uniform size and shape. These optimized nanoparticles were then supported on SiO 2 and assessed for thermocatalytic CO 2 hydrogenation against larger, polydisperse CoO nanoparticles on SiO 2 and a conventionally prepared catalyst. The optimized CoO/SiO 2 catalyst consistently exhibited higher activity and CH 4 selectivity (ca. 98%) across various pretreatment reduction temperatures as compared to the other catalysts. This remarkable performance was attributed to particle stability and consistent H* surface coverage, even after undergoing the highest temperature reduction, achieving a more stable catalytic species that resists sintering and carbon occlusion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1985

Evaluation of 16 measures of mental workload using a simulated flight task emphasizing mediational activity

As aircraft and other systems become more automated, a shift is occurring in human operator participation in these systems. This shift is away from manual control and toward activities that tap the higher mental functioning of human operators. Therefore, an experiment was performed in a moving-base flight simulator to assess mediational (cognitive) workload measurement. Specifically, 16 workload estimation techniques were evaluated as to their sensitivity and intrusion in a flight task emphasizing mediational behavior. Task loading, using navigation problems presented on a display, was treated as an independent variable, and workload-measure values were treated as dependent variables. Results indicate that two mediational task measures, two rating scale measures, time estimation, and two eye behavior measures were reliably sensitive to mediational loading. The time estimation measure did, however, intrude on mediational task performance. Several of the remaining measures were completely insensitive to mediational load.

Wierwille, W. W.↗
NASA NTRS1991

Using GOMS models and hypertext to create representations of medical procedures for online display

This study investigated two methods to improve organization and presentation of computer-based medical procedures. A literature review suggested that the GOMS (goals, operators, methods, and selecton rules) model can assist in rigorous task analysis, which can then help generate initial design ideas for the human-computer interface. GOMS model are hierarchical in nature, so this study also investigated the effect of hierarchical, hypertext interfaces. We used a 2 x 2 between subjects design, including the following independent variables: procedure organization - GOMS model based vs. medical-textbook based; navigation type - hierarchical vs. linear (booklike). After naive subjects studies the online procedures, measures were taken of their memory for the content and the organization of the procedures. This design was repeated for two medical procedures. For one procedure, subjects who studied GOMS-based and hierarchical procedures remembered more about the procedures than other subjects. The results for the other procedure were less clear. However, data for both procedures showed a 'GOMSification effect'. That is, when asked to do a free recall of a procedure, subjects who had studies a textbook procedure often recalled key information in a location inconsistent with the procedure they actually studied, but consistent with the GOMS-based procedure.

Gugerty, Leo↗
NASA NTRS2002

Present and future ephemerides: requirements and limitations

This paper discusses the various aspects of the planetary and lunar ephemerides at JPL. First, the question of the independent variable of the ephemerides is reviewed. Next, the paper mentions the navigational requirements of past missions and those expected in the future.

ephemerides navigation↗
NASA NTRS1982

Improved Magnetic-Field-Component Resolvers

New resolvers for vectorially summing outputs of aircraft-mounted magnetometers are lighter and more economical to fabricate than conventional electromagnetic resolvers. One resolver is based on potentiometric principles, the second uses polarization filters, and the third has variable-capacitance elements. Optical, capacitive and potentiometric devices have applications in aircraft navigation systems.

Garner, H. D.↗
NASA NTRS1972

Space Shuttle landing navigation using precision distance measuring equipment.

Precision distance measuring equipment (DME) aiding onboard inertial navigation can be used to meet the stringent landing navigation requirements of the Space Shuttle. The required accuracy is achieved by using a ten-state-variable Kalman filter to process the measured range and delta-range data from the DME. The DME transponders are required to meet the accuracy requirements: two are deployed under the final approach path and one is deployed to the side. Failure considerations require deployment of additional redundant transponders. Initialization of the landing navigation after hypersonic entry is accomplished using the transponders at the airport.

Widnall, W. S.↗
DOE OSTI2024

Monte Carlo Simulation with CAD Interface for Calculation of 3D Maps of Residual Dose (CRADA)

Objective: To develop an easy-to-use software application to predict and mitigate radiation effects in research environment, space instruments, nuclear plants and medical facilities and help nonproliferation and national security efforts. Tech-X will develop standalone software libraries and command-line tools for ( 1) translating CAD into tessellated surfaces and tetrahedral meshes in GDML (for Geant4 and MARS 15), ROOT (for MARS 15) and HDF5 (for compact representation and for the visualization) formats, (2) healing CAD geometries to make them suitable for Monte Carlo simulations; (3) creating uniform and variable Cartesian and cylindrical meshes for detailed scoring; and ( 4) efficient Monte Carlo navigation in CAD geometries. JLAB will finish automation of simulations of residual dose in CAD geometries and integrate Tech-X software into Geant4 and MARS15. Finally, Tech-X will develop a Graphical User Interface to set up and heal CAD geometries, create input files, run and visualize simulations for residual dose. This application will run on local desktops, local and remote clusters and supercomputers and will be made available through public clouds, such as Amazon Web Services.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2017

Online Multi-Modal Learning and Adaptive Information Trajectory Planning for Autonomous Exploration

In robotic information gathering missions, scientists are typically interested in understanding variables which require proxy measurements from specialized sensor suites to estimate. However, energy and time constraints limit how often these sensors can be used in a mission. Robots are also equipped with cheaper to use navigation sensors such as cameras. In this paper, we explore a challenging planning problem in which a robot is required to learn about a scientific variable of interest in an initially unknown environment by planning informative paths and deciding when and where to use its sensors. To tackle this we present two innovations: a Bayesian generative model framework to automatically learn correlations between expensive science sensors and cheaper to use navigation sensors online, and a sampling based approach to plan for multiple sensors while handling long horizons and budget constraints. Our approach does not grow in complexity with data and is anytime making it highly applicable to field robotics. We tested our approach extensively in simulation and validated it with real data collected during the 2014 Mojave Volatiles Prospector Mission. Our planning algorithm performs statistically significantly better than myopic approaches and at least as well as a coverage-based algorithm in an initially unknown environment while having added advantages of being able to exploit prior knowledge and handle other intricacies of the real world without further algorithmic modifications.

learning↗
NASA NTRSDate not supplied

Analysis of Improved Navigation Data for NASA Near Space Network (NSN) Direct-to-Earth (DTE) Ground Stations

Spacecraft navigation is a complex concept that requires a collaboration between network entities and constant corrective action to be successful in the highly variable environment. NASA’s Near Space Network (NSN), Direct-to-Earth (DTE) ground station team is constantly exploring methods to provide better service to NASA spacecraft, including providing radiometric tracking data, subject to cost constraints. Navigation teams, such as the Goddard Space Flight Center (GSFC) Flight Dynamics Facility (FDF), use the tracking data to perform orbit determination to assess where a spacecraft has been, identify where a spacecraft is now, and predict where a spacecraft will be in the future. As NASA plans for more missions beyond low Earth orbit (LEO), there is a need for improved navigation performance which can be directly achieved through improvements in the radiometric tracking data. NASA’s new DTE Ka-band antennas have finer autotrack angle resolution, and the availability of low-cost improved off-the-shelf ground station components, which are involved with producing navigation data. NASA formed a team to provide an assessment of the current NSN, DTE spacecraft navigation service (radiometric tracking) performance baseline with the end goal of defining needed future enhancements to meet the needs for spacecraft above LEO. The communications and navigation community is deriving new techniques in an effort to better service the navigation needs of spacecraft using ground station networks. This paper provides an overview Earth-orbit, direct-to-ground navigation techniques and performance, the development of specifications for new antennas, accuracy of data, spacecraft requirements, accuracy of orbit determination, history of challenges, and considerations for improvements. The discussions in this paper may assist ground station, spacecraft, and mission design teams advance navigation capabilities and more effectively meet requirements.

networks↗
NASA NTRS2005

GLOBAL REFERENCE ATMOSPHERIC MODELS FOR AEROASSIST APPLICATIONS

Aeroassist is a broad category of advanced transportation technology encompassing aerocapture, aerobraking, aeroentry, precision landing, hazard detection and avoidance, and aerogravity assist. The eight destinations in the Solar System with sufficient atmosphere to enable aeroassist technology are Venus, Earth, Mars, Jupiter, Saturn, Uranus, Neptune, and Saturn's moon Titan. Engineering-level atmospheric models for five of these targets - Earth, Mars, Titan, Neptune, and Venus - have been developed at NASA's Marshall Space Flight Center. These models are useful as tools in mission planning and systems analysis studies associated with aeroassist applications. The series of models is collectively named the Global Reference Atmospheric Model or GRAM series. An important capability of all the models in the GRAM series is their ability to simulate quasi-random perturbations for Monte Carlo analysis in developing guidance, navigation and control algorithms, for aerothermal design, and for other applications sensitive to atmospheric variability. Recent example applications are discussed.

Duvall, Aleta↗
NASA NTRS2004

GRACE KBR and Accelerometer Data Reduction and Calibration

The Gravity Recovery and Climate Experiment (GRACE), launched on March 17, 2002, represents the state-of-the-art in geodetic observations of the static and time varying components of the Earth's geopotential field. The fundamental measurement used to observe gravity is the inter-satellite range and range rate between two coplanar, low altitude satellites obtained from a K-band ranging (KBR) system. In addition to the K-band ranging system, each satellite possess a Super-STAR Accelerometer, a GPS receiver/antenna package, Star Cameras and a Laser Retro Reflector (LRR) to complete the compliment of science instruments. The GRACE project has now released two years of Level 1B data derived from the science instruments and sensors. An integral component of our time variable gravity research is the reduction, calibration and analyses of these Level 1B data. In particular we have analyzed several months of K-band ranging (KBR1B), accelerometry (ACC1B) and GPS navigation (GNAV1B) data. Accelerometer calibration and KBR data reduction methodology and results will be presented. We discuss the impact of these analyses on the recovery of time variable gravity.

Rowlands, David D.↗
NASA NTRS1973

A guidance and navigation system for continuous low-thrust vehicles

A midcourse guidance and navigation system for continuous low thrust vehicles was developed. The equinoctial elements are the state variables. Uncertainties are modelled statistically by random vector and stochastic processes. The motion of the vehicle and the measurements are described by nonlinear stochastic differential and difference equations respectively. A minimum time trajectory is defined; equations of motion and measurements are linearized about this trajectory. An exponential cost criterion is constructed and a linear feedback quidance law is derived. An extended Kalman filter is used for state estimation. A short mission using this system is simulated. It is indicated that this system is efficient for short missions, but longer missions require accurate trajectory and ground based measurements.

Jack-Chingtse, C.↗
NASA NTRS1992

Evaluation of microwave landing system approaches in a wide-body transport simulator

The objective of this study was to determine the suitability of flying complex curved approaches using the microwave landing system (MLS) with a wide-body transport aircraft. Fifty pilots in crews of two participated in the evaluation using a fixed-base simulator that emulated an MD-11 aircraft. Five approaches, consisting of one straight-in approach and four curved approaches, were flown by the pilots using a flight director. The test variables include the following: (1) manual and autothrottles; (2) wind direction; and (3) type of navigation display. The navigation display was either a map or a horizontal situation indicator (HSI). A complex wind that changed direction and speed with altitude, and included moderate turbulence, was used. Visibility conditions were Cat 1 or better. Subjective test data included pilot responses to questionnaires and pilot comments. Objective performance data included tracking accuracy, position error at decision height, and control activity. Results of the evaluation indicate that flying curved MLS approaches with a wide-body transport aircraft is operationally acceptable, depending upon the length of the final straight segment and the complexity of the approach.

Summers, L. G.↗