Finite-element-analysis model and preliminary ground testing of controls-structures interaction evolutionary model reflector

Results of two different nonlinear finite element analyses and preliminary test results for the final design of the Controls-Structures Interaction Evolutionary Model are presented. Load-deflection data bases are generalized from analysis and testing of the 16-foot diameter, dish shaped reflector. Natural frequencies and mode shapes are obtained from vibrational analysis. Experimental and analytical results show similar trends; however, future test hardware modifications and finite element model refinement would be necessary to obtain better correlation. The two nonlinear analysis procedures are both adequate techniques for the analysis of prestressed structures with complex geometries

Static and Dynamic Model Update of an Inflatable/Rigidizable Torus Structure

The present work addresses the development of an experimental and computational procedure for validating finite element models. A torus structure, part of an inflatable/rigidizable Hexapod, is used to demonstrate the approach. Because of fabrication, materials, and geometric uncertainties, a statistical approach combined with optimization is used to modify key model parameters. Static test results are used to update stiffness parameters and dynamic test results are used to update the mass distribution. Updated parameters are computed using gradient and non-gradient based optimization algorithms. Results show significant improvements in model predictions after parameters are updated. Lessons learned in the areas of test procedures, modeling approaches, and uncertainties quantification are presented

Evaluation of Two Crew Module Boilerplate Tests Using Newly Developed Calibration Metrics

The paper discusses a application of multi-dimensional calibration metrics to evaluate pressure data from water drop tests of the Max Launch Abort System (MLAS) crew module boilerplate. Specifically, three metrics are discussed: 1) a metric to assess the probability of enveloping the measured data with the model, 2) a multi-dimensional orthogonality metric to assess model adequacy between test and analysis, and 3) a prediction error metric to conduct sensor placement to minimize pressure prediction errors. Data from similar (nearly repeated) capsule drop tests shows significant variability in the measured pressure responses. When compared to expected variability using model predictions, it is demonstrated that the measured variability cannot be explained by the model under the current uncertainty assumptions

On the Application of a Response Surface Technique to Analyze Roll-over Stability of Capsules with Airbags Using LS-Dyna

As NASA moves towards developing technologies needed to implement its new Exploration program, studies conducted for Apollo in the 1960's to understand the rollover stability of capsules landing are being revisited. Although rigid body kinematics analyses of the roll-over behavior of capsules on impact provided critical insight to the Apollo problem, extensive ground test programs were also used. For the new Orion spacecraft being developed to implement today's Exploration program, new air-bag designs have improved sufficiently for NASA to consider their use to mitigate landing loads to ensure crew safety and to enable re-usability of the capsule. Simple kinematics models provide only limited understanding of the behavior of these air bag systems, and more sophisticated tools must be used. In particular, NASA and its contractors are using the LS-Dyna nonlinear simulation code for impact response predictions of the full Orion vehicle with air bags by leveraging the extensive air bag prediction work previously done by the automotive industry. However, even in today's computational environment, these analyses are still high-dimensional, time consuming, and computationally intensive. To alleviate the computational burden, this paper presents an approach that uses deterministic sampling techniques and an adaptive response surface method to not only use existing LS-Dyna solutions but also to interpolate from LS-Dyna solutions to predict the stability boundaries for a capsule on airbags. Results for the stability boundary in terms of impact velocities, capsule attitude, impact plane orientation, and impact surface friction are discussed

DMAPS, A Database of Micro-Environmental Air Pollution Sources

In order for any database of indoor air pollution source data to be most useful, it was decided that it should meet several goals: 1) It should be useful to users with a wide range of interests, including researchers, architects, policy makers, manufacturers, builders, designers, and modelers. 2) It should be as widely accessible as possible. This has been a major consideration in determining the best combination of relational database management system and computer hardware to accomplish this goal. 3) It must be able to satisfy a broad range of needs. For example, some users may be interested only in bibliographic information, whereas others may wish to use the retrieved data to analyze specific indoor air pollution problems. 4) The system must be "user friendly"; i.e., uncomplicated and undaunting to operate. This allows the data to be accessible to persons whose training is in areas other than in the use of computers. 5) Since it is anticipated that the amount of emission rate data will grow rapidly in the near future, the database must be easy to update and modify. Easy data entry also helps to minimize entry errors, another important consideration. With these design goals in mind, a database containing source specific data from research articles has been compiled, along with controlling computer programs which will allow for quick and easy access to this indoor air pollution data. This database system has been titled dMAPS, the database of Micro-environmental Air Pollution Sources. The remainder of this paper describes dMAPS' function, design, and methods.Master of Science in Public Healt

Work Creativity as a Dimension of Job Performance

To stay competitive, many employers are looking for creative and innovative employees to add value to their organization. However, current models of job performance overlook creative performance as an important criterion to measure in the workplace. The purpose of this dissertation is to conduct two separate but related studies on creative performance that aim to provide support that creative performance should be included in models of job performance, and ultimately included in performance evaluations in organizations. Study 1 is a meta-analysis on the relationship between creative performance and task performance, and the relationship between creative performance and organizational citizenship behavior (OCB). Overall, I found support for a medium to large corrected correlation for both the creative performance-task performance (ρ = .51) and creative performance-OCB (ρ = .49) relationships. Further, I also found that both rating-source and study location were significant moderators. Study 2 is a process model that includes creative performance alongside task performance and OCB as the outcome variables. I test a model in which both individual differences (specifically: conscientiousness, extraversion, proactive personality, and self-efficacy) and job characteristics (autonomy, feedback, and supervisor support) predict creative performance, task performance, and OCB through engagement as a mediator. In a sample of 299 employed individuals, I found that all the individual differences and job characteristics were positively correlated with all three performance criteria. I also looked at these relationships in a multiple regression framework and most of the individual differences and job characteristics still predicted the performance criteria. In the mediation analyses, I found support for engagement as a significant mediator of the individual differences-performance and job characteristics-performance relationships. Taken together, Study 1 and Study 2 support the notion that creative performance should be included in models of job performance. Implications for both researchers and practitioners alike are discussed

The Role of the Environment in the Individual Difference and Creativity Relationship

This study examined the relationship between several individual differences (openness to experience, conscientiousness, extraversion, creative self-efficacy, intrinsic motivation, and polychronicity) and creativity. It also examined how the organizational climate (support for creativity) moderated the relationship between the individual differences and creativity. All the individual differences except for polychronicity were positively correlated with creativity as well as support for creativity. Structural Equation Modeling (SEM) found that the individual differences explained 58% of the variance in creativity and that support for creativity moderated the relationship between conscientiousness and creativity and between extraversion and creativity. Because of noticed similarity between creativity and creative self-efficacy items, a factor analysis was done which confirmed some overlap. Implications of the findings of this paper are discussed

Closed loop pole placement and cost analysis.

http://archive.org/details/closedlooppolepl00reavNAN

Non-canonical interactions between plant proteins and lectins cause false positives in lectin blots

Lectins are proteins that specifically recognize and non-covalently bind to soluble carbohydrates or to the carbohydrate moieties of glycoproteins or glycolipids. Historically,lectin-blot analysis has been widely used as a tool for structural characterization of many mammalian glycoconjugates. In the present study, we demonstrate that the application of this technique to screen sugar moieties of plant proteins results in numerous false positives. Plants lack the enzyme machinery necessary to perform sialylation, however many bands appear upon probing of N. benthamiana L. leaf proteins with Maacia amurensis agglutinin (MAA) that recognizes specifically N-linked or core 2 O-linked glycans containing Neu5Ac/Gc-α2,3Galβ-1,4GlcNAc/Glc and O-linked glycans containing the trisaccharide Neu5Ac-3Galβ1-3GalNAc. The non-canonical binding is a direct result of sample preparation for SDS PAGE, because native proteins do not show an affinity to MAA-agarose resin. Moreover, inhibition with known hapten fails to prevent binding of MAA to plant proteins in lectin blots. We also provide evidence that interactions of a hydrophobic nature contribute, at least in part, to the non-specific binding, and that other lectins – Sambucus nigra agglutinin (SNA) and Vicia villosa agglutinin (VVA) – also bind non-specifically to plant proteins. In conclusion, lectin blot analysis of plant proteins should always be verified by probing the binding specificity with a known hapten inhibitor alongside appropriate mammalian glycoprotein controls. Alternatively, non-specific binding can be avoided if lectin affinity chromatography of the native plant proteins is performed prior to lectin blots analysis

Multi-Dimensional Calibration of Impact Dynamic Models

NASA Langley, under the Subsonic Rotary Wing Program, recently completed two helicopter tests in support of an in-house effort to study crashworthiness. As part of this effort, work is on-going to investigate model calibration approaches and calibration metrics for impact dynamics models. Model calibration of impact dynamics problems has traditionally assessed model adequacy by comparing time histories from analytical predictions to test at only a few critical locations. Although this approach provides for a direct measure of the model predictive capability, overall system behavior is only qualitatively assessed using full vehicle animations. In order to understand the spatial and temporal relationships of impact loads as they migrate throughout the structure, a more quantitative approach is needed. In this work impact shapes derived from simulated time history data are used to recommend sensor placement and to assess model adequacy using time based metrics and orthogonality multi-dimensional metrics. An approach for model calibration is presented that includes metric definitions, uncertainty bounds, parameter sensitivity, and numerical optimization to estimate parameters to reconcile test with analysis. The process is illustrated using simulated experiment data