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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Crystal growth of compound semiconductors in a low-gravity environment (InGaAs crystals) (M-22)

Compound semiconductor crystals, such as gallium arsenide and indium phosphide crystals, have many interesting properties that silicon crystals lack, and they are expected to be used as materials for optic and/or electro-optic integrated devices. Generally speaking, alloy semiconductors, which consist of more than three elements, demonstrate new functions. For example, values of important parameters, such as lattice constant and emission wavelength, can be chosen independently. However, as it is easy for macroscopic and/or microscopic fluctuations of composition to occur in alloy semiconductor crystals, it is difficult to obtain crystals having homogeneous properties. Macroscopic change of composition in a crystal is caused by the segregation phenomenon. This phenomenon is due to a continuous change in the concentration of constituent elements at the solid-liquid interfacing during solidification. On Earth, attempts were made to obtain a crystal with homogeneous composition by maintaining a constant melt composition near the solid-liquid interface, through suppression of the convection flow of the melt by applying a magnetic field. However, the attempt was not completely successful. Convective flow does not occur in microgravity because the gravity in space is from four to six orders of magnitude less than that on Earth. In such a case, mass transfer in the melt is dominated by the diffusion phenomenon. So, if crystal growth is carried out at a rate that is higher than the rate of mass transfer due to this phenomenon, it is expected that crystals having a homogeneous composition will be obtained. In addition, it is also possible that microscopic composition fluctuations (striation) may disappear because microscopic fluctuations diminish in the absence of convection. We are going to grow a bulk-indium gallium arsenide (InGaAs) crystal using the gradient heating furnace (GHF) in the first material processing test (FMPT). The structure of the sample is shown where InGaAs polycrystals in a crucible are doubly sealed in two quartz tubes for safety. The GHF consists of two zones, namely, high temperature and low temperature zones, which results in a large temperature gradient at the interface. Crystal growth is performed by moving the furnace (i.e. the temperature profile) from the left to right at a definite rate. Thus, we will grow crystals both on Earth and in space under the same conditions. As previously described, it is possible to obtain good quality crystals which are homogeneous in composition both macroscopically and microscopically due to the lack of convection in space. We are planning to study the effects of convection on crystal growth from a melt by comparing and characterizing the properties of crystals grown on Earth with those grown in space.

Tatsumi, Masami↗
NASA NTRS1992

Analysis of crustal structure of Venus utilizing residual Line-of-Sight (LOS) gravity acceleration and surface topography data. A trial of global modeling of Venus gravity field using harmonic spline method

To construct Venus' gravity disturbance field (or gravity anomaly) with the spacecraft-observer line of site (LOS) acceleration perturbation data, both a global and a local approach can be used. The global approach, e.g., spherical harmonic coefficients, and the local approach, e.g., the integral operator method, based on geodetic techniques are generally not the same, so that they must be used separately for mapping long wavelength features and short wavelength features. Harmonic spline, as an interpolation and extrapolation technique, is intrinsically flexible to both global and local mapping of a potential field. Theoretically, it preserves the information of the potential field up to the bound by sampling theorem regardless of whether it is global or local mapping, and is never bothered with truncation errors. The improvement of harmonic spline methodology for global mapping is reported. New basis functions, a singular value decomposition (SVD) based modification to Parker & Shure's numerical procedure, and preliminary results are presented.

Fang, Ming↗
NASA NTRS1994

Method and system for pattern analysis using a coarse-coded neural network

A method and system for performing pattern analysis with a neural network coarse-coding a pattern to be analyzed so as to form a plurality of sub-patterns collectively defined by data. Each of the sub-patterns comprises sets of pattern data. The neural network includes a plurality fields, each field being associated with one of the sub-patterns so as to receive the sub-pattern data therefrom. Training and testing by the neural network then proceeds in the usual way, with one modification: the transfer function thresholds the value obtained from summing the weighted products of each field over all sub-patterns associated with each pattern being analyzed by the system.

Spirkovska, Liljana↗
NASA NTRS1997

A Combined MG II/CA II Survey of Stellar Magnetic Activity in the Solar Neighborhood

We use nearly contemporaneus low-resolution IUE observations of Mg II h + k emission and Mount Wilson Observatory Ca II H + K S indices for 33 pairs of observations of lower main sequence stars to formulate a relationship that will permit accurate predictions of S values as a function of (B - V) color and Mg II h + k flux. The resulting relationship is useful because it will extend the set of solar neighborhood stars for which a uniform estimate of chromospheric activity is available to include stars that are not observable from Mount Wilson as well as providing additional estimates of activity levels for stars that are on the Mount Wilson HK Project observing list.

Wicklund, B. M.↗
NASA NTRS2006

Wearable Wireless Telemetry System for Implantable Bio-MEMS Sensors

In this paper, a telemetry and contact-less powering system consisting of an implantable bio-MEMS sensor with a miniature printed square spiral chip antenna and an external wearable garment with printed loop antenna is investigated. The wearable garment pick-up antenna and the implantable chip antenna are in close proximity to each other and hence couple inductively through their near-fields and behave as the primary and the secondary circuits of a transformer, respectively. The numerical and experimental results are graphically presented, and include the design parameter values as a function of the geometry, the relative RF magnetic near-field intensity as a function of the distance and angle, and the current density on the strip conductors, for the implantable chip antenna.

Simons, Rainee N.↗
NASA NTRS2011

Space-Time Data fusion for Remote Sensing Applications

NASA has been collecting massive amounts of remote sensing data about Earth's systems for more than a decade. Missions are selected to be complementary in quantities measured, retrieval techniques, and sampling characteristics, so these datasets are highly synergistic. To fully exploit this, a rigorous methodology for combining data with heterogeneous sampling characteristics is required. For scientific purposes, the methodology must also provide quantitative measures of uncertainty that propagate input-data uncertainty appropriately. We view this as a statistical inference problem. The true but notdirectly- observed quantities form a vector-valued field continuous in space and time. Our goal is to infer those true values or some function of them, and provide to uncertainty quantification for those inferences. We use a spatiotemporal statistical model that relates the unobserved quantities of interest at point-level to the spatially aggregated, observed data. We describe and illustrate our method using CO2 data from two NASA data sets.

carbon dioxide↗
NASA NTRS2017

Analysis of Convective Weather Impact on Pre-Departure Routing of Flights from Fort Worth Center to New York Center

In response to severe weather conditions, Traffic Managers specify flow constraints and reroutes to route air traffic around affected regions of airspace. Providing analysis and recommendations of available reroute options and associated airspace capacities would assist Traffic Managers in making more efficient decisions in response to convective weather. These recommendations can be developed by examining historical data to determine which previous reroute options were used in similar weather and traffic conditions. This paper describes the initial steps and methodology used towards this goal. The focus of this work is flights departing from Fort Worth Center destined for New York Center. Dominant routing structures used in the absence of convective weather are identified. A method to extract relevant features from the large volume of weather data available to quantify the impact of convective weather on this routing structure over a given time range is presented. Finally, a method of estimating flow rate capacity along commonly used routes during convective weather events is described. Results show that the flow rates drop exponentially as a function of the values of the proposed feature and that convective weather on the final third of the route was found to have a greater impact on the flow rate restriction than other portions of the route.

traffic flow management↗
NASA NTRS1992

Incomplete fuzzy data processing systems using artificial neural network

In this paper, the implementation of a fuzzy data processing system using an artificial neural network (ANN) is discussed. The binary representation of fuzzy data is assumed, where the universe of discourse is decartelized into n equal intervals. The value of a membership function is represented by a binary number. It is proposed that incomplete fuzzy data processing be performed in two stages. The first stage performs the 'retrieval' of incomplete fuzzy data, and the second stage performs the desired operation on the retrieval data. The method of incomplete fuzzy data retrieval is proposed based on the linear approximation of missing values of the membership function. The ANN implementation of the proposed system is presented. The system was computationally verified and showed a relatively small total error.

Patyra, Marek J.↗
NASA NTRS2008

Calculations for Calibration of a Mass Spectrometer

A computer program performs calculations to calibrate a quadrupole mass spectrometer in an instrumentation system for identifying trace amounts of organic chemicals in air. In the operation of the mass spectrometer, the mass-to-charge ratio (m/z) of ions being counted at a given instant of time is a function of the instantaneous value of a repeating ramp voltage waveform applied to electrodes. The count rate as a function of time can be converted to an m/z spectrum (equivalent to a mass spectrum for singly charged ions), provided that a calibration of m/z is available. The present computer program can perform the calibration in either or both of two ways: (1) Following a data-based approach, it can utilize the count-rate peaks and the times thereof measured when fed with air containing known organic compounds. (2) It can utilize a theoretical proportionality between the instantaneous m/z and the instantaneous value of an oscillating applied voltage. The program can also estimate the error of the calibration performed by the data-based approach. If calibrations are performed in both ways, then the results can be compared to obtain further estimates of errors.

Lee, Seungwon↗
NASA NTRS1979

The effect of errors in the assignment of the transmission functions on the accuracy of the thermal sounding of the atmosphere

In order to test the error of calculation in assumed values of the transmission function for Soviet and American radiometers sounding the atmosphere thermally from orbiting satellites, the assumptions of the transmission calculation is varied with respect to atmospheric CO2 content, transmission frequency, and atmospheric absorption. The error arising from variations of the assumptions from the standard basic model is calculated.

Timofeyev, Y. M.↗
NASA NTRS1990

Low-energy plasma in Neptune's magnetosphere

Plasma data from the region of Neptune's magnetosphere between L = 6.5 and L = 13.5 are analyzed. Selecting only spectra where both light and heavy ions are present, density and temperature profiles are derived under the assumption that the ions are H(+) and N(+). These results are used to calculate the total flux shell content (for a shell of unit width in L), N, of each ion in this region. Values of N derived from inbound and outbound data are similar, indicating the plasma distribution functions are isotropic. Average values of NL2 are 3 x 10 to the 32nd for H(+) and 1 x 10 to the 32nd for N(+). Profiles of NL2 for both H(+) and N(+) increase outwards, suggesting that Triton is the probable source of both these plasma components. Evidence is presented for significant inbound-outbound asymmetries in the plasma morphology.

Richardson, John D.↗
NASA NTRS2004

Efficient Evaluation Functions for Multi-Rover Systems

Evolutionary computation can be a powerful tool in cresting a control policy for a single agent receiving local continuous input. This paper extends single-agent evolutionary computation to multi-agent systems, where a collection of agents strives to maximize a global fitness evaluation function that rates the performance of the entire system. This problem is solved in a distributed manner, where each agent evolves its own population of neural networks that are used as the control policies for the agent. Each agent evolves its population using its own agent-specific fitness evaluation function. We propose to create these agent-specific evaluation functions using the theory of collectives to avoid the coordination problem where each agent evolves a population that maximizes its own fitness function, yet the system has a whole achieves low values of the global fitness function. Instead we will ensure that each fitness evaluation function is both "aligned" with the global evaluation function and is "learnable," i.e., the agents can readily see how their behavior affects their evaluation function. We then show how these agent-specific evaluation functions outperform global evaluation methods by up to 600% in a domain where a set of rovers attempt to maximize the amount of information observed while navigating through a simulated environment.

Agogino, Adrian↗
NASA NTRS2016

Operational Implementation of a Pc Uncertainty Construct for Conjunction Assessment Risk Analysis

Earlier this year the NASA Conjunction Assessment and Risk Analysis (CARA) project presented the theoretical and algorithmic aspects of a method to include the uncertainties in the calculation inputs when computing the probability of collision (Pc) between two space objects, principally uncertainties in the covariances and the hard-body radius. The output of this calculation approach is to produce rather than a single Pc value an entire probability density function that will represent the range of possible Pc values given the uncertainties in the inputs and bring CA risk analysis methodologies more in line with modern risk management theory. The present study provides results from the exercise of this method against an extended dataset of satellite conjunctions in order to determine the effect of its use on the evaluation of conjunction assessment (CA) event risk posture. The effects are found to be considerable: a good number of events are downgraded from or upgraded to a serious risk designation on the basis of consideration of the Pc uncertainty. The findings counsel the integration of the developed methods into NASA CA operations.

assessment↗
NASA NTRS1973

Analysis of temperature-dependent neutron transmission and self-indication measurements on tantalum at 2-keV neutron energy

The method of pseudo-resonance cross sections is used to analyze published temperature-dependent neutron transmission and self-indication measurements on tantalum in the unresolved region. In the energy region analyzed, 1825.0 to 2017.0 eV, a direct application of the pseudo-resonance approach using a customary average strength function will not provide effective cross sections which fit the measured cross section behavior. Rather a local value of the strength function is required, and a set of resonances which model the measured behavior of the effective cross sections is derived. This derived set of resonance parameters adequately represents the observed resonance hehavior in this local energy region. Similar analyses for the measurements in other unresolved energy regions are necessary to obtain local resonance parameters for improved reactor calculations. This study suggests that Doppler coefficients calculated by sampling from grand average statistical distributions over the entire unresolved resonance region can be in error, since significant local variations in the statistical distributions are not taken into consideration.

Semler, T. T.↗
NASA NTRS1994

Advanced timeline systems

The Mission Planning Division of the Mission Operations Laboratory at NASA's Marshall Space Flight Center is responsible for scheduling experiment activities for space missions controlled at MSFC. In order to draw statistically relevant conclusions, all experiments must be scheduled at least once and may have repeated performances during the mission. An experiment consists of a series of steps which, when performed, provide results pertinent to the experiment's functional objective. Since these experiments require a set of resources such as crew and power, the task of creating a timeline of experiment activities for the mission is one of resource constrained scheduling. For each experiment, a computer model with detailed information of the steps involved in running the experiment, including crew requirements, processing times, and resource requirements is created. These models are then loaded into the Experiment Scheduling Program (ESP) which attempts to create a schedule which satisfies all resource constraints. ESP uses a depth-first search technique to place each experiment into a time interval, and a scoring function to evaluate the schedule. The mission planners generate several schedules and choose one with a high value of the scoring function to send through the approval process. The process of approving a mission timeline can take several months. Each timeline must meet the requirements of the scientists, the crew, and various engineering departments as well as enforce all resource restrictions. No single objective is considered in creating a timeline. The experiment scheduling problem is: given a set of experiments, place each experiment along the mission timeline so that all resource requirements and temporal constraints are met and the timeline is acceptable to all who must approve it. Much work has been done on multicriteria decision making (MCDM). When there are two criteria, schedules which perform well with respect to one criterion will often perform poorly with respect to the other. One schedule dominates another if it performs strictly better on one criterion, and no worse on the other. Clearly, dominated schedules are undesireable. A nondominated schedule can be generated by some sort of optimization problem. Generally there are two approaches: the first is a hierarchical approach while the second requires optimizing a weighting or scoring function.

Bulfin, R. L.↗
NASA NTRS1992

Membership generation using multilayer neural network

There has been intensive research in neural network applications to pattern recognition problems. Particularly, the back-propagation network has attracted many researchers because of its outstanding performance in pattern recognition applications. In this section, we describe a new method to generate membership functions from training data using a multilayer neural network. The basic idea behind the approach is as follows. The output values of a sigmoid activation function of a neuron bear remarkable resemblance to membership values. Therefore, we can regard the sigmoid activation values as the membership values in fuzzy set theory. Thus, in order to generate class membership values, we first train a suitable multilayer network using a training algorithm such as the back-propagation algorithm. After the training procedure converges, the resulting network can be treated as a membership generation network, where the inputs are feature values and the outputs are membership values in the different classes. This method allows fairly complex membership functions to be generated because the network is highly nonlinear in general. Also, it is to be noted that the membership functions are generated from a classification point of view. For pattern recognition applications, this is highly desirable, although the membership values may not be indicative of the degree of typicality of a feature value in a particular class.

Kim, Jaeseok↗