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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Analysis of Thematic Mapper data for studying the suspended matter distribution in the coastal area of the German Bight (North Sea)

Thematic Mapper data were analyzed with respect to its capability for mapping the complex structure and dynamics of suspended matter distribution in the coastal area of the German Bight (North Sea). Three independent pieces of information were found by factor analysis of all seven TM channels: suspended matter concentration, atmospheric scattering, and sea surface temperature. For the required atmospheric correction, the signal-to-noise ratios of Channels 5 and 7 have to be improved by averaging over 25 x 25 pixels, which also makes it possible to monitor the aerosol optical depth and aerosol type over cloud-free water surfaces. Near-surface suspended matter concentrations may be detected with an accuracy of factor less than 2 by using an algorithm derived from radiative transfer model calculation. The patchiness of suspended matter and its relation to underwater topography was analyzed with autocorrelation and cross-correlation.

Doerffer, R.↗
NASA NTRS2003

Accuracy Evaluation of Electron-Probe Microanalysis as Applied to Semiconductors and Silicates

An evaluation of precision and accuracy will be presented for representative semiconductor and silicate compositions. The accuracy of electron-probe analysis depends on high precision measurements and instrumental calibration, as well as correction algorithms and fundamental parameter data sets. A critical assessment of correction algorithms and mass absorption coefficient data sets can be made using the alpha factor technique. Alpha factor analysis can be used to identify systematic errors in data sets and also of microprobe standards used for calibration.

Carpenter, Paul↗
NASA NTRS1983

Aubrites and diogenites - Trace element clues to their origin

A typically igneous siderophile element pattern emerges from an RNAA analysis of 25 aubrite and nine diogenite samples for 13-29 siderophile, volatile, and lithophile trace elements, although it is noted that abundances are about 10 times higher in the case of aubrites. Se is also surprisingly abundant in aubrites. Factor analysis shows several parallel groupings for aubrites and diogenites. Several element pairs that differ greatly in volatility correlate closely in aubrites, in approximately C1-chondrite proportions, suggesting that aubrites originated by igneous processes in their parent body.

Wolf, R.↗
NASA NTRS1979

The effects of context on multidimensional spatial cognitive models

Spatial cognitive models obtained by multidimensional scaling represent cognitive structure by defining alternatives as points in a coordinate space based on relevant dimensions such that interstimulus dissimilarities perceived by the individual correspond to distances between the respective alternatives. The dependence of spatial models on the context of the judgments required of the individual was investigated. Context, which is defined as a perceptual interpretation and cognitive understanding of a judgment situation, was analyzed and classified with respect to five characteristics: physical environment, social environment, task definition, individual perspective, and temporal setting. Four experiments designed to produce changes in the characteristics of context and to test the effects of these changes upon individual cognitive spaces are described with focus on experiment design, objectives, statistical analysis, results, and conclusions. The hypothesis is advanced that an individual can be characterized as having a master cognitive space for a set of alternatives. When the context changes, the individual appears to change the dimension weights to give a new spatial configuration. Factor analysis was used in the interpretation and labeling of cognitive space dimensions.

Dupnick, E. G.↗
NASA NTRS1988

Group interaction and flight crew performance

The application of human-factors analysis to the performance of aircraft-operation tasks by the crew as a group is discussed in an introductory review and illustrated with anecdotal material. Topics addressed include the function of a group in the operational environment, the classification of group performance factors (input, process, and output parameters), input variables and the flight crew process, and the effect of process variables on performance. Consideration is given to aviation safety issues, techniques for altering group norms, ways of increasing crew effort and coordination, and the optimization of group composition.

Foushee, H. Clayton↗
NASA NTRS2003

The Effect of Mission Location on Mission Costs and Equivalent System Mass

Equivalent System Mass (ESM) is used by the Advanced Life Support (ALS) community to quantify mission costs of technologies for space applications (Drysdale et al, 1999, Levri et al, 2000). Mass is used as a cost measure because the mass of an object determines propulsion (acceleration) cost (i.e. amount of fuel needed), and costs relating to propulsion dominate mission cost. Mission location drives mission cost because acceleration is typically required to initiate and complete a change in location. Total mission costs may be reduced by minimizing the mass of materials that must be propelled to each distinct location. In order to minimize fuel requirements for missions beyond low-Earth orbit (LEO), the hardware and astronauts may not all go to the same location. For example, on a Lunar or Mars mission, some of the hardware or astronauts may stay in orbit while the rest of the hardware and astronauts descend to the planetary surface. In addition, there may be disposal of waste or used hardware at various mission locations to avoid propulsion of mass that is no longer needed in the mission. This paper demonstrates how using location factors in the calculation of ESM can account for the effects of various acceleration events and can improve the accuracy and value of the ESM metric to mission planners. Even a mission with one location can benefit from location factor analysis if the alternative technologies under consideration consume resources at different rates. For example, a mission that regenerates resources will have a relatively constant mass compared to one that uses consumables and vents/discards mass along the way. This paper shows examples of how location factors can affect ESM calculations and how the inclusion of location factors can change the relative value of technologies being considered for development.

Fisher, John W.↗
NASA NTRS2011

Kennedy Space Center Orion Processing Team Planning for Ground Operations

Topics in this presentation are: Constellation Ares I/Orion/Ground Ops Elements Orion Ground Operations Flow Orion Operations Planning Process and Toolset Overview, including: 1 Orion Concept of Operations by Phase 2 Ops Analysis Capabilities Overview 3 Operations Planning Evolution 4 Functional Flow Block Diagrams 5 Operations Timeline Development 6 Discrete Event Simulation (DES) Modeling 7 Ground Operations Planning Document Database (GOPDb) Using Operations Planning Tools for Operability Improvements includes: 1 Kaizen/Lean Events 2 Mockups 3 Human Factors Analysis

Letchworth, Gary↗
NASA NTRS2017

Similarity Assessment of Land Surface Model Outputs in the North American Land Data Assimilation System

Multimodel ensembles are often used to produce ensemble mean estimates that tend to have increased simulation skill over any individual model output. If multimodel outputs are too similar, an individual LSM would add little additional information to the multimodel ensemble, whereas if the models are too dissimilar, it may be indicative of systematic errors in their formulations or configurations. The article presents a formal similarity assessment of the North American Land Data Assimilation System (NLDAS) multimodel ensemble outputs to assess their utility to the ensemble, using a confirmatory factor analysis. Outputs from four NLDAS Phase 2 models currently running in operations at NOAA/NCEP and four new/ upgraded models that are under consideration for the next phase of NLDAS are employed in this study. The results show that the runoff estimates from the LSMs were most dissimilar whereas the models showed greater similarity for root zone soil moisture, snow water equivalent, and terrestrial water storage. Generally, the NLDAS operational models showed weaker association with the common factor of the ensemble and the newer versions of the LSMs showed stronger association with the common factor, with the model similarity increasing at longer time scales. Trade-offs between the similarity metrics and accuracy measures indicated that the NLDAS operational models demonstrate a larger span in the similarity-accuracy space compared to the new LSMs. The results of the article indicate that simultaneous consideration of model similarity and accuracy at the relevant time scales is necessary in the development of multimodel ensemble.

land surface models↗
NASA NTRS1992

Validation of astronaut psychological select-in criteria

An optional astronaut selection strategy would select-in individuals on the basis of personality attributes associated with superior performance. Method: A test battery, the Astronaut Personal Characteristics Inventory (ASTROPCI) was developed which assesses positive and negative components of achievement, motivation, and interpersonal orientations and skills. The battery was administered to one hundred three astronaut candidates and sixty-six current U.S. Shuttle astronauts. To determine performance, a series of conceptual areas related to space flight performance were defined. Astronauts rated their peers on each of these dimensions. Ratings were obtained on all eighty-four current astronauts (excluding those selected in 1990). In addition to peer ratings, supervisor assessments of the same dimensions were obtained for each astronaut. Results: Cluster and factor analysis techniques were employed to isolate subgroups of astronauts. Those astronauts with both high achievement needs and interpersonal skills were most often rated among the top five by their peers and least often rated among the lowest five. A number of scales discriminated between astronauts rated high and low on one or more performance dimensions. Conclusions: The results parallel findings from the personality assessment of individuals in other demanding professions, including aircraft pilots and research scientists, suggesting that personality factors are significant determinants to performance in the space environment.

Rose, R. M.↗
NASA NTRS2014

MARGInS: Model-Based Analysis of Realizable Goals in Systems

Under NASAs Constellation effort, the Exploration Technology Development Program funded research toward a system validation capability that applied machine learning and test-case generation techniques to the analysis of black-box system behavior. The behavior analysis capability scaled to spaces of hundreds of input parameters and tens of thousands of test cases. Aerospace systems at the vehicle level, especially those systems which contain some level of autonomy, are best described by hybrid and non-linear mathematics. Even simplified models of such systems need parameter dimensionalities in the hundreds or thousands of parameters in order to capture sufficient fidelity. The System Safety Assessments (such as those described in the SAE ARP 4761A Safety Assessment Process guidelines) for these systems are prone to errorinteractions between the vehicles subsystems are complex, and can display emergent behaviors. NASA captured this new analysis in the Model-based Analysis of Realizable Goals in Systems (MARGInS) tool and applied it to the Pad Abort 1 (PA-1) simulation as part of the independent validation and verification cycle before the PA-1 flight test in May of 2010. MARGInS evaluated the adherence of the high-fidelity simulation to its requirements, and deter- mined the margins to failure from the expected nominal input conditions. Following the PA-1 test, the capabilities within the MARGInS framework have been extended with sophisticated statistical and white-box test case generation techniques and applied to other NASA missions. The frame- work now includes a critical factors analysis that was applied to NASAs Orion simulation and design. NASAs Aeronautics Research Mission Directorate (ARMD) leveraged the existing MARGInS framework for work on aviation safety for civil transport vehicles and for research on autonomy issues. The NASA ARMD effort created a time series output prediction capability that has been used to characterize trajectories for a plane with an adaptive control system, and a safety boundary detection capability that has been applied to an air traffic control concept of operation for the Federal Aviation Administration. The statistical and machine- learning based techniques within MARGInS have been successfully combined with concolic execution to improve the coverage of a critical unit by driving system-level inputs. The use case driving the concolic execution and MARGInS integration was inspired by the Air France 447 disaster in which the loss of a critical functionality (the airspeed calculation from the pitot tubes) led to loss of the entire plane with the people aboard. To illustrate capabilities and limitations, we will highlight the analyses for the applications listed above. We will then discuss the future plans for MARGInS and its interfaces with other tools.

Validation↗
NASA NTRS1993

Objective determination of image end-members in spectral mixture analysis

Spectral mixture analysis was shown to be a powerful, multifaceted tool for analysis of multi- and hyper-spectral data. The essence of the first phase of the approach is to determine a set of image end-members that best account for the spectral variance in an image cube within a constrained, linear least squares mixing model. The selection of the image end-member is usually achieved using a priori knowledge and successive trial and error solutions to refine the total number and physical location of the end-members. However, in many situations a more objective method of determining these essential components is desired. The problem of image end-member determination was approached objectively by using the inherent variance of the data. Unlike purely statistical methods such as factor analysis, this approach derives solutions that conform to a physically realistic model.

Tompkins, Stefanie↗
NASA NTRS1993

Objective determination of image end-members in spectral mixture analysis of AVIRIS data

Spectral mixture analysis has been shown to be a powerful, multifaceted tool for analysis of multi- and hyper-spectral data. Applications of AVIRIS data have ranged from mapping soils and bedrock to ecosystem studies. During the first phase of the approach, a set of end-members are selected from an image cube (image end-members) that best account for its spectral variance within a constrained, linear least squares mixing model. These image end-members are usually selected using a priori knowledge and successive trial and error solutions to refine the total number and physical location of the end-members. However, in many situations a more objective method of determining these essential components is desired. We approach the problem of image end-member determination objectively by using the inherent variance of the data. Unlike purely statistical methods such as factor analysis, this approach derives solutions that conform to a physically realistic model.

Tompkins, Stefanie↗
NASA NTRS1994

Profile analysis of after-effects experienced during exposure to several virtual reality environments

Motion sickness symptoms are an unwanted by-product of exposure to virtual environments. This problem is not new and was reported in the early flight simulators and experiments on ego motions and vection. The cardinal symptom of motion sickness is, of course, vomiting, but this symptom is ordinarily preceded by a variety of other symptoms. In his classic studies of motion sickness conducted before and during World War II, G. R. Wendt introduced a three point scale to score motion sickness beyond a vomit/no vomit dichotomy. Later, Navy scientists developed a Motion Sickness Questionnaire (MSQ), originally for use in a slowly rotating room. In the last 20 years the MSQ has been used in a series of studies of air, sea, and space sickness. Only recently, however, has it been appreciated that symptom patterns in the MSQ are not uniform but vary with the way sickness is induced. In seasickness, for example, nausea is the most prominent symptom. In Navy simulators, however, the most common symptom is eye strain, especially when cathode ray tubes are employed in the simulation. The latter result was obtained in a survey of over 1,500 pilot exposures. Using this database, Essex scientists conducted a factor analysis of the MSQ. We found that signs and symptoms of motion sickness fell mainly into three clusters: 1) oculomotor disturbance, 2) nausea and related neurovegetative problems, and 3) disorientation, ataxia, and vertigo. We have since rescored the MSQ results obtained in Navy simulators in terms of these three components. We have also compared these and other profiles obtained from three different vitual reality systems to profiles obtained in sea sickness, space sickness, and alcohol intoxication. We will show examples of these various profiles and point out simularities and differences among them which indicate aspects of what might be called 'virtual-reality sickness'.

Kennedy, Robert S.↗
NASA NTRS2004

LASTRAC.3d: Transition Prediction in 3D Boundary Layers

Langley Stability and Transition Analysis Code (LASTRAC) is a general-purpose, physics-based transition prediction code released by NASA for laminar flow control studies and transition research. This paper describes the LASTRAC extension to general three-dimensional (3D) boundary layers such as finite swept wings, cones, or bodies at an angle of attack. The stability problem is formulated by using a body-fitted nonorthogonal curvilinear coordinate system constructed on the body surface. The nonorthogonal coordinate system offers a variety of marching paths and spanwise waveforms. In the extreme case of an infinite swept wing boundary layer, marching with a nonorthogonal coordinate produces identical solutions to those obtained with an orthogonal coordinate system using the earlier release of LASTRAC. Several methods to formulate the 3D parabolized stability equations (PSE) are discussed. A surface-marching procedure akin to that for 3D boundary layer equations may be used to solve the 3D parabolized disturbance equations. On the other hand, the local line-marching PSE method, formulated as an easy extension from its 2D counterpart and capable of handling the spanwise mean flow and disturbance variation, offers an alternative. A linear stability theory or parabolized stability equations based N-factor analysis carried out along the streamline direction with a fixed wavelength and downstream-varying spanwise direction constitutes an efficient engineering approach to study instability wave evolution in a 3D boundary layer. The surface-marching PSE method enables a consistent treatment of the disturbance evolution along both streamwise and spanwise directions but requires more stringent initial conditions. Both PSE methods and the traditional LST approach are implemented in the LASTRAC.3d code. Several test cases for tapered or finite swept wings and cones at an angle of attack are discussed.

Chang, Chau-Lyan↗
NASA NTRS2002

Estimating the Single-Trial Characteristics of Event-Related Responses: Evaluation of the MCERP Algorithm

Single-trial event-related responses collected during the course of an experiment are typically averaged before analysis resulting in a rather crude picture of event-related brain dynamics. It has been quite clear for some time that these responses exhibit trial-to-trial variability: however, the computational techniques necessary to deal with such responses in noisy conditions have not been available. To this end we have developed the multiple-component, event-related potential model (mcERP), which assumes that the each event-related response consists of a sum of multiple evoked components each described by a stereotypical waveshape. These waveshapes are allowed to vary in amplitude and onset latency from trial to trial, which allows us to capture, to first-order, the trial-dependent variations in event-related brain dynamics. We have constructed many sets of synthetic data designed to simulate intracortical recordings from a 15 channel, linear-array multielectrode implanted acutely in V1 of an awake-behaving macaque undergoing visual stimulation with a red light flash. This synthetic data was used to characterize the performance of the mcERP algorithm. First we quantified the degree to which such trial-to-trial variability aids in the identification of multiple components, and we demonstrate that amplitude variability is a more important factor in component separation than latency variability. Second, we quantified the behavior of the algorithm under two distinct signal-to-noise ratio (SNR) conditions: Gaussian noise independently present in each channel, and highly correlated (1/f distributed), far-field noise presented identically in each channel of the array. The mcERP algorithm was found to be robust to noise accurately identifying all component waveshapes and their associated single-trial characteristics down to SNR levels of -20dB for Gaussian noise and -7dB for 1/f far-field noise. Comparisons of the performance of this algorithm with factor analysis (FA) and independent component analysis (ICA) will be described by Knuth et al. (SFN abstracts, 2002). In addition, the advantages of application of mcERP to real data will be described by Shah et al, (these abstracts, 2002: SFN abstracts, 2002).

Knuth, K. H.↗