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At least 127 records · Page 7

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.↗

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.↗

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↗

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.↗

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↗

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↗

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.↗

Effects of size, geometry, and testing temperature on additively manufactured Ti-6Al-4V titanium alloy

This article presents a comprehensive study concerning size and geometry effect on the ambient and high-temperature mechanical behavior of additively manufactured laser powder bed fusion Ti-6Al-4V alloy. Key mechanical property metrics are presented, including strain hardening rate, yield strength, and Young’s modulus as a function of thickness and testing temperature (ambient, 250 °C, and 450 °C). Here, the effect of specimen size on manufacturing-induced microstructural feature formation is demonstrated and discussed. A detailed analysis regarding Young’s modulus, yield strength, and strain hardening rate variation at elevated temperatures is also presented. Size effect and temperature-sensitive deformation mechanisms are linked to the underlying microstructural deformation mechanisms activated at respective temperatures. Counter-intuitively, this study determined that irrespective of the geometry, strain hardening rates increased as temperature increased. An in-depth microstructural examination is presented to explain the stated observation. The texture of Interrupted tensile test samples examined for ambient, 250 °C, and 450 °C post-yield was observed to be unchanged, indicating the strain hardening behavior was not texture dependent. Schmid factor analysis, coupled with experimental findings from previous work, was implemented to generate a hypothesis. This hypothesis suggests that the drop in critical resolved shear stress for basal and pyramidal slip systems, as temperature increases, paired with the high dislocation density of laser powder bed fusion Ti-6Al-4V, leads to dislocation entanglement and results in increased strain hardening at elevated temperatures.

36 MATERIALS SCIENCE↗

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↗

Implications of a Pervasive Climate Model Bias for Low‐Cloud Feedback

Abstract How low clouds respond to warming constitutes a key uncertainty for climate projections. Here we observationally constrain low‐cloud feedback through a controlling factor analysis based on ridge regression. We find a moderately positive global low‐cloud feedback (0.45 W , 90% range 0.18–0.72 W ), about twice the mean value (0.22 W ) of 16 models from the Coupled Model Intercomparison Project. We link this discrepancy to a pervasive model mean‐state bias: models underestimate the low‐cloud response to warming because (a) they systematically underestimate present‐day tropical marine low‐cloud amount, and (b) the low‐cloud sensitivity to warming is proportional to this present‐day low‐cloud amount. Our results hence highlight the importance of reducing model biases in both the mean state of clouds and their sensitivity to environmental factors for accurate climate change projections.

58 GEOSCIENCES↗

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↗

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↗

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.↗

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↗

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.↗

Investigating the impacts of solid phase extraction on dissolved organic matter optical signatures and the pairing with high‐resolution mass spectrometry data across a freshwater stream network

Abstract Advancing our understanding of dissolved organic matter (DOM) chemistry in aquatic systems necessitates the integration of data streams from multiple analytical platforms. Some measurements require pretreatment with solid phase extraction (SPE), while others are performed directly on whole water samples. Evidence has suggested that SPE will be biased against select DOM fractions, leading to concerns over the ability to establish data linkages across platforms with variable needs for SPE pretreatment, such as those from optical measurements and those that provide high‐resolution molecular information. Here, we directly addressed this concern by assessing the impact of SPE on DOM optical properties through excitation–emission matrices with parallel factor analysis (PARAFAC) for 47 samples across a stream network within a single watershed reflective of variable DOM sources. PARAFAC data was further paired with molecular information obtained by Fourier transform ion cyclotron resonance mass spectrometry (FTICR‐MS). A comparison of PARAFAC models first revealed no systematic qualitative differences in major components between whole water DOM and DOM isolated by SPE (SPE‐DOM); however, quantitative biases against select components were observed. Further linkages with FTICR‐MS data revealed that the molecular fingerprint associated with each PARAFAC component was consistent between the whole water DOM and SPE‐DOM. Our results suggest that bulk scale linkages across these analytical platforms could be inferred irrespective of the observed quantitative biases resulting from SPE for samples within this example watershed. This work represents a key step toward the systematic evaluation of linkages between optical and high‐resolution mass spectrometry datasets in freshwater lotic environments.

59 BASIC BIOLOGICAL SCIENCES↗

Temporal evolution of Pu and Cs sediment contamination in a seasonally stratified pond

There remains a lack of knowledge regarding ecosystem transfer, transport processes, and mechanisms, which influence the long-term mobility of Pu-239 and Cs-137 in natural environments. Monitoring the distribution and migration of trace radioisotopes as ecosystem tracers has the potential to provide insight into the underlying mechanisms of geochemical cycles. This study investigated the distribution of anthropogenic radionuclides Pu-239 and Cs-137 along with total organic carbon, iron, and trace element in contaminated sediments of Pond B at the Savannah River Site (SRS). Pond B received reactor cooling water from 1961 to 1964, and trace amounts of Pu-239 and Cs-137 during operations. Our study collected sediment cores to determine concentrations of Pu-239, Cs-137, and major and minor elements in solid phase, pore water and an electrochemical method was used on wet cores to determine dissolved elemental concentrations. More than 50 years after deposition, Pu-239 and Cs-137 in sediments are primarily located in the upper 5 cm in area where deposition of particulate-bound contaminants was prevalent and located between 5 and 10 cm in areas of high sedimentation, showing a limited migration of Pu-239 and Cs-137. A Factor analysis demonstrated different sediment facies across the pond resulting in a range of geochemical processes controlling accumulation of Pu and Cs. Highest concentrations appear to be controlled by particulate input from the influent canal, dominated by clay, silt, and sand minerals bearing Fe. Elevated Pu-239 in the sediments were observed in areas with high organic matter and higher deposition rate relative to the Pond B system near the outlet indicating strong association of Pu with OM and particulates. Therefore, organic matter cycling likely plays a role in Pu redistribution between sediment and overlying pond water, and deposition in organic rich sediments accumulating near the outlet. Though Pu appears to have been distributed throughout the pond, Cs-137 concentrations remained the highest near the influent canal.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Sub-Sampled Imaging for STEM: Maximising Image Speed, Resolution and Precision Through Reconstruction Parameter Refinement

Sub-sampling during image acquisition in scanning transmission electron microscopy (STEM) has been shown to provide a means to increase the overall speed of acquisition while at the same time providing an efficient means to control the dose, dose rate and dose overlap delivered to the sample. In this paper, we discuss specifically the parameters used to reconstruct sub-sampled images and highlight their effect on inpainting using the beta-process factor analysis (BPFA) methodology. The selection of the main control parameters can have a significant effect on the resolution, precision and sensitivity of the final inpainted images, and here we demonstrate a method by which these parameters can be optimised for any image in STEM. As part of this paper, we also provide a link to open source code and a tutorial on its use, whereby these parameters can be tested for any datasets. When coupled with the hardware necessary to rapidly sub-sample images in STEM, this approach can have significant implications for imaging beam sensitive materials and dynamic processes.

47 OTHER INSTRUMENTATION↗