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At least 829 records · Page 46

Utilizing Photogrammetry and Strain Gage Measurement to Characterize Pressurization of an Inflatable Module

This paper documents the integration of a large hatch penetration into an inflatable module. This paper also documents the comparison of analytical load predictions with measured results utilizing strain measurement. Strain was measured by utilizing photogrammetric measurement and through measurement obtained from strain gages mounted to selected clevises that interface with the structural webbings. Bench testing showed good correlation between strain measurement obtained from an extensometer and photogrammetric measurement especially after the fabric has transitioned through the low load/high strain region of the curve. Test results for the full-scale torus showed mixed results in the lower load and thus lower strain regions. Overall strain, and thus load, measured by strain gages and photogrammetry tracked fairly well with analytical predictions. Methods and areas of improvements are discussed.

Valle, Gerard D.↗

The Effects of Long Duration Head Down Tilt Bed Rest on Neurocognitive Performance: The Effects of Exercise Interventions

We are conducting ongoing experiments in which we are performing structural and functional magnetic resonance brain imaging to identify the relationships between changes in neurocognitive function and neural structural alterations following a six month International Space Station mission and following 70 days exposure to a spaceflight analog, head down tilt bedrest. Our central hypothesis is that measures of brain structure, function, and network integrity will change from pre to post intervention (spaceflight, bedrest). Moreover, we predict that these changes will correlate with indices of cognitive, sensory, and motor function in a neuroanatomically selective fashion. Our interdisciplinary approach utilizes cutting edge neuroimaging techniques and a broad ranging battery of sensory, motor, and cognitive assessments that will be conducted pre flight, during flight, and post flight to investigate potential neuroplastic and maladaptive brain changes in crewmembers following long-duration spaceflight. Success in this endeavor would 1) result in identification of the underlying neural mechanisms and operational risks of spaceflight-induced changes in behavior, and 2) identify whether a return to normative behavioral function following re-adaptation to Earth's gravitational environment is associated with a restitution of brain structure and function or instead is supported by substitution with compensatory brain processes. Our ongoing bed rest participants are also engaging in exercise studies directed by Dr. Lori Ploutz Snyder. In this presentation, I will briefly highlight the existing literature linking exercise and fitness to brain and behavioral functions. I will also overview the metrics from my study that could be investigated in relation to the exercise and control subgroups.

Seidler, R. D.↗

The Effects of Spaceflight and a Spaceflight Analog on Neurocognitive Perfonnance: Extent, Longevity, and Neural Bases

We are conducting ongoing experiments in which we are performing structural and functional magnetic resonance brain imaging to identify the relationships between changes in neurocognitive function and neural structural alterations following a six month International Space Station mission and following 70 days exposure to a spaceflight analog, head down tilt bedrest. Our central hypothesis is that measures of brain structure, function, and network integrity will change from pre to post intervention (spaceflight, bedrest). Moreover, we predict that these changes will correlate with indices of cognitive, sensory, and motor function in a neuroanatomically selective fashion. Our interdisciplinary approach utilizes cutting edge neuroimaging techniques and a broad ranging battery of sensory, motor, and cognitive assessments that will be conducted pre flight, during flight, and post flight to investigate potential neuroplastic and maladaptive brain changes in crewmembers following long-duration spaceflight. Success in this endeavor would 1) result in identification of the underlying neural mechanisms and operational risks of spaceflight-induced changes in behavior, and 2) identify whether a return to normative behavioral function following re-adaptation to Earth's gravitational environment is associated with a restitution of brain structure and function or instead is supported by substitution with compensatory brain processes. With the bedrest study, we will be able to determine the neural and neurocognitive effects of extended duration unloading, reduced sensory inputs, and increased cephalic fluid distribution. This will enable us to parse out the multiple mechanisms contributing to any spaceflight-induced neural structural and behavioral changes that we observe in the flight study. In this presentation I will discuss preliminary results from six participants who have undergone the bed rest protocol. These individuals show decrements in balance and functional mobility, and alterations in brain structure and function, in association with extended bed rest.

Seidler, R. D.↗

Spaceflight Effects on Neurocognitive Performance: Extent, Longevity and Neural Bases

We are conducting ongoing experiments in which we are performing structural and functional magnetic resonance brain imaging to identify the relationships between changes in neurocognitive function and neural structural alterations following a six month International Space Station mission. Our central hypothesis is that measures of brain structure, function, and network integrity will change from pre to post spaceflight. Moreover, we predict that these changes will correlate with indices of cognitive, sensory, and motor function in a neuroanatomically selective fashion. Our interdisciplinary approach utilizes cutting edge neuroimaging techniques and a broad ranging battery of sensory, motor, and cognitive assessments that are conducted pre flight, during flight, and post flight to investigate potential neuroplastic and maladaptive brain changes in crewmembers following long-duration spaceflight. Success in this endeavor would 1) result in identification of the underlying neural mechanisms and operational risks of spaceflight-induced changes in behavior, and 2) identify whether a return to normative behavioral function following re-adaptation to Earth's gravitational environment is associated with a restitution of brain structure and function or instead is supported by substitution with compensatory brain processes. We have collected data on several crewmembers and preliminary findings will be presented. Eventual comparison to results from our parallel bed rest study will enable us to parse out the multiple mechanisms contributing to any spaceflight-induced neural structural and behavioral changes that we observe.

Seidler, R. D.↗

Effects of One Year of Spaceflight on Neurocognitive Function

It is known that spaceflight adversely affects human sensorimotor function. With interests in longer duration deep space missions it is important to understand microgravity dose-response relationships. NASA's One Year Mission project allows for comparison of the effects of one year in space with those seen in more typical six month missions to the International Space Station. In the Neuromapping project we are performing structural and functional magnetic resonance brain imaging to identify the relationships between changes in neurocognitive function and neural structural alterations following a six month International Space Station mission. Our central hypothesis is that measures of brain structure, function, and network integrity will change from pre- to post-spaceflight. Moreover, we predict that these changes will correlate with indices of cognitive, sensory, and motor function in a neuroanatomically selective fashion. Our interdisciplinary approach utilizes cutting edge neuroimaging techniques and a broad-ranging battery of sensory, motor, and cognitive assessments that are conducted pre-flight, during flight, and post-flight to investigate potential neuroplastic and maladaptive brain changes in crewmembers following long-duration spaceflight. With the one year mission we had one crewmember participate in all of the same measures pre-, per- and post-flight as in our ongoing study. During this presentation we will provide an overview of the magnitude of changes observed with our brain and behavioral assessments for the one year crewmember in comparison to participants that have completed our six month study to date.

Seidler, R. D.↗

Relationship of Cure Temperature to Mechanical, Physical, and Dielectric Performance of PDMS Glass Composite for Electric Motor Insulation

Achieving NASAs aggressive fuel burn and emission reduction for N-plus-3 aircraft will require hybrid electric propulsion system in which electric motors driven by either power generated from turbine or energy storage system will power the fan for propulsion. Motors designed for hybrid electric aircraft are expected to operate at medium to high voltages over long durations in a high altitude service environment. Such conditions have driven research toward the development of wire insulation with improved mechanical strength, thermal stability and increased breakdown voltage. The silicone class of materials has been considered for electric wire insulation due to its inherent thermal stability, dielectric strength and mechanical integrity. This paper evaluates the dependence of these properties on the cure conditions of a polydimethyl-siloxane (PDMS) elastomer; where both cure temperature and base-to-catalyst ratio were varied. The PDMS elastomer was evaluated as a bulk material and an impregnation matrix within a lightweight glass veil support. The E-glass support was selected for mechanical stiffness and dielectric strength. This work has shown a correlation between cure conditions and material physical properties. Tensile strength increased with cure temperature whereas breakdown voltage tended to be independent of process variations. The results will be used to direct material formulation based on specific insulation requirements.

insulation↗

Test and Analysis of Full-Scale 27.5-Foot-Diameter Stiffened Metallic Launch Vehicle Cylinders

The Shell Buckling Knockdown Factor Project (SBKF) was established with the goal of developing improved (i.e., less-conservative, more robust) shell buckling knockdown factors (KDFs) for modern launch-vehicle structures. To this end, SBKF has engaged in several activities to support the development, validation, and implementation of the new design factors, including subscale and full-scale structural testing. Tests on eight different subscale, 8-foot-diameter, integrally stiffened aluminum-lithium 2195 (Al-Li 2195) cylinders were conducted in order to obtain the majority of the required validation data. In addition, two full-scale, 27.5-foot-diameter, Al-Li 2195, integrally stiffened cylinders were tested to provide additional validation data and to determine structural scaling trends. Presented herein are the details of a recent analysis model development and test and analysis correlation effort on the full-scale test articles. The effects of selected modeling assumptions and approaches are discussed, and results from a modeling sensitivity study are presented. It was found that simplified finite element models, that assume nominal test article geometry and material properties, can predict the overall response characteristics well. However, several discrepancies in the test and analysis results were observed. A sensitivity study was performed to determine the effects of several modeling assumptions and address the observed discrepancies. The results from the study indicated that the evolution of local skin pocket buckling and the presence of residual stresses due to the manufacturing process can have a significant influence on the predicted buckling response of the cylinders considered.

Lovejoy, Andrew E.↗

Marginal protein stability drives subcellular proteome isoelectric point

There exists a positive correlation between the pH of subcellular compartments and the median isoelectric point (pI) for the associated proteomes. Proteins in the human lysosome—a highly acidic compartment in the cell—have a median pI of ∼6.5, whereas proteins in the more basic mitochondria have a median pI of ∼8.0. Proposed mechanisms reflect potential adaptations to pH. For example, enzyme active site general acid/base residue pKs are likely evolved to match environmental pH. However, such effects would be limited to a few residues on specific proteins, and might not affect the proteome at large. A protein model that considers residue burial upon folding recapitulates the correlation between proteome pI and environmental pH. This correlation can be fully described by a neutral evolution process; no functional selection is included in the model. Proteins in acidic environments incur a lower energetic penalty for burying acidic residues than basic residues, resulting in a net accumulation of acidic residues in the protein core. The inverse is true under alkaline conditions. The pI distributions of subcellular proteomes are likely not a direct result of functional adaptations to pH, but a molecular spandrel stemming from marginal stability.

Kaiser Loell↗

Novel Geochemistry Determined from High P-T Simulation Experiments of HFTS 2

A standard method in unconventional oil and gas production is the process of hydraulic fracturing followed by a shut-in period, during which the fracture fluid remains pressurized in the reservoir for up to three weeks before production begins. Despite this widely used process, very little is known about what occurs in the reservoir during this shut-in process. In order to properly delineate potential reservoir reactions that may occur during shut-in that would lead to corrosion and scaling events, experiments were conducted in high pressure, high temperature reactors to simulate conditions of the Wolfcamp Formation in the Delaware Basin. Experimental design allowed the assessment of the effect of proppant, microbiology, and time on the mineralogy and fluid chemistry in the reservoir. Results suggest the biggest impact on fluid chemistry and shale mineralogy during shut-in is time. Analyses demonstrate dissolution of the shale material, with maximum dissolved ions occurring after 7 days of the shut-in period. After 21 days, results suggest precipitation occurs. The Delaware Basin is demonstrated to be high in sulfate content, which further increases in the fluid due to dissolution reactions during shut-in. The pressure vessel experiments suggest there was no significant contribution to reactions from microbiology during the shut-in period. However, early production samples demonstrate a significant selection of the microorganism Caminicella, a genus of which has previously been correlated to corrosion and sulfide production. Results suggest shut-in conditions may provide high sulfate concentrations that could later be utilized by a shifted microbial community to drive potential well infrastructure failure. This is the first study to incorporate microbiology, mineralogy, and fluid chemistry to investigate the fundamental geochemical reactions that occur during shut-in and early phase production of the Delaware Basin. Results from this study can complement observations from the Hydraulic Fracture Test Site 2 observations.

Gulliver, Djuna↗

Characterization of PMR polyimides - Correlation of ester impurities with composite properties

The presumed relationship of chemical impurities to final composite properties is the rationale for most chemical characterization studies. This study examines this relationship for PMR-polyimide resin. Ester/acid solutions of one monomer were aged at selected temperatures and chemical changes were monitored spectroscopically. At selected intervals, graphite fiber reinforced composite panels were fabricated. Changes in resin processing characteristics and composite properties were determined. The correlation of these data are discussed as are related characterization studies of PMR-polyimide resin.

Lauver, R. W.↗

Advanced Composites: Mechanical Properties and Hardware Programs for Selected Resin Matrix Materials

This design note presents typical mechanical properties tabulated from industrial and governmental agencies' test programs. All data are correlated to specific products and all of the best known products are presented. The data include six epoxies, eight polyimides and one polyquinoxaline matrix material. Bron and graphite are the fiber reinforcements. Included are forty-two summaries of advanced (resin matrix) composite programs in existence in the United States. It is concluded that the selection of appropriate matrices, the geometric manner in which the fibers are incorporated in the matrix and the durability of the bond between fiber and matrix establish the end properties of the composite material and the performance of the fabricated structure.

Welhart, E. K.↗

Local composition activity coefficient model for mixed-gas adsorption equilibria

Taking into consideration the adsorbate–adsorbent interactions, a novel activity coefficient model is derived from the non-random two-liquid theory for mixed-gas adsorption equilibria. In contrast with the conventional activity coefficient models developed for bulk liquids, the new model correctly predicts negative deviations from ideality for adsorbed phase mixtures including azeotropic behavior exhibited by selected gas-adsorbent systems. Here, the requiring a single binary interaction parameter per adsorbate–adsorbate pair, the model successfully correlates wide varieties of binary adsorption isotherm data and it should be a powerful engineering thermodynamic tool in correlating and predicting mixed-gas adsorption equilibria.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Oriented chiral water wires in artificial transmembrane channels

Aquaporins (AQPs) feature highly selective water transport through cell membranes, where the dipolar orientation of structured water wires spanning the AQP pore is of considerable importance for the selective translocation of water over ions. We recently discovered that water permeability through artificial water channels formed by stacked imidazole I-quartet superstructures increases when the channel water molecules are highly organized. Correlating water structure with molecular transport is essential for understanding the underlying mechanisms of (fast) water translocation and channel selectivity. Chirality adds another factor enabling unique dipolar oriented water structures. We show that water molecules exhibit a dipolar oriented wire structure within chiral I-quartet water channels both in the solid state and embedded in supported lipid bilayer membranes (SLBs). X-ray single-crystal structures show that crystallographic water wires exhibit dipolar orientation, which is unique for chiral I-quartets. The integration of I-quartets into SLBs was monitored with a quartz crystal microbalance with dissipation, quantizing the amount of channel water molecules. Nonlinear sum-frequency generation vibrational spectroscopy demonstrates the first experimental observation of dipolar oriented water structures within artificial water channels inserted in bilayer membranes. Confirmation of the ordered confined water is obtained via molecular simulations, which provide quantitative measures of hydrogen bond strength, connectivity, and the stability of their dipolar alignment in a membrane environment. Together, uncovering the interplay between the dipolar aligned water structure and water transport through the self-assembled I-quartets is critical to understanding the behavior of natural membrane channels and will accelerate the systematic discovery for developing artificial water channels for water desalting.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Correlated Materials Characterization via Multimodal Chemical and Functional Imaging

Multimodal chemical imaging simultaneously offers high-resolution chemical and physical information with nanoscale and, in select cases, atomic resolution. By coupling modalities that collect physical and chemical information, we can address scientific problems in biological systems, battery and fuel cell research, catalysis, pharmaceuticals, photovoltaics, medicine, and many others. The combined systems enable the local correlation of material properties with chemical makeup, making fundamental questions of how chemistry and structure drive functionality approachable. In this Review, we present recent progress and offer a perspective for chemical imaging used to characterize a variety of samples by a number of platforms. Specifically, we present cases of infrared and Raman spectroscopies combined with scanning probe microscopy; optical microscopy and mass spectrometry; nonlinear optical microscopy; and, finally, ion, electron, and probe microscopies with mass spectrometry. As a result, we also discuss the challenges associated with the use of data originated by the combinatorial hardware, analysis, and machine learning as well as processing tools necessary for the interpretation of multidimensional data acquired from multimodal studies.

36 MATERIALS SCIENCE↗

Sensor selection and tool wear prediction with data‐driven models for precision machining

Abstract Estimation of tool wear in precision machining is vital in the traditional subtractive machining industry to reduce processing cost, improve manufacturing efficiency and product quality. In this vein, fusion of time and frequency‐domain features of commonly sensed signals can provide an early indication of tool wear and improve its prediction accuracy for prognostics and health management. This paper presents a data‐driven methodology and a complete tool chain for the inference of precision machining tool wear from fused machine measurements, such as cutting force, power, audio and vibration signals, and quantify the usefulness of each measurement. Indicators of tool wear are extracted from time‐domain signal statistics, frequency‐domain analysis, and time‐frequency domain analysis. Correlation coefficients between the extracted features (indicators) and the tool wear are used to select the most informative features. Principal Component Analysis and Partial Least‐Squares are used to reduce the dimensionality of the feature space. Regression models, including linear regression, support vector regression, Decision tree regression, neural network regression and Gaussian process regression, are used to predict the tool wear using data from a Haas milling machine performing spiral boss face milling. The performance of the regression models based on subsets of sensors validates the preliminary estimates about the saliency of the sensors. The experimental results show that the proposed methods can predict the machine tool wear precisely, with readily available sensor measurements. Neural network and Gaussian process regression were able to achieve good estimates of tool wear at different machine operating conditions. The most informative signal in predicting tool wear was shown to be the vibration signal. Time‐frequency domain features were the most informative features among the combination of features of three domains. In addition, using partial least squares components extracted from the original features of signals led to higher prediction accuracy.

Han, Seulki↗

On the ultrafast charge migration and subsequent charge directed reactivity in Cl⋯N halogen-bonded clusters following vertical ionization

In this article, we have presented ultrafast charge transfer dynamics through halogen bonds following vertical ionization of representative halogen bonded clusters. Subsequent hole directed reactivity of the radical cations of halogen bonded clusters is also discussed. Furthermore, we have examined effect of the halogen bond strength on the electron-electron correlation- and relaxation-driven charge migration in halogen bonded complexes. For this study, we have selected A-Cl (A represents F, OH, CN, NH{sub 2}, CF{sub 3}, and COOH substituents) molecules paired with NH{sub 3} (referred as ACl:NH{sub 3} complex): these complexes exhibit halogen bonds. To the best of our knowledge, this is the first report on purely electron correlation- and relaxation-driven ultrafast (attosecond) charge migration dynamics through halogen bonds. Both density functional theory and complete active space self-consistent field theory with 6-31 + G(d, p) basis set are employed for this work. Upon vertical ionization of NCCl⋯NH{sub 3} complex, the hole is predicted to migrate from the NH{sub 3}-end to the ClCN-end of the NCCl⋯NH{sub 3} complex in approximately 0.5 fs on the D{sub 0} cationic surface. This hole migration leads to structural rearrangement of the halogen bonded complex, yielding hydrogen bonding interaction stronger than the halogen bonding interaction on the same cationic surface. Other halogen bonded complexes, such as H{sub 2}NCl:NH{sub 3}, F{sub 3}CCl:NH{sub 3}, and HOOCCl:NH{sub 3}, exhibit similar charge migration following vertical ionization. On the contrary, FCl:NH{sub 3} and HOCl:NH{sub 3} complexes do not exhibit any charge migration following vertical ionization to the D{sub 0} cation state, pointing to interesting halogen bond strength-dependent charge migration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The LSST AGN Data Challenge: Selection Methods

Abstract Development of the Rubin Observatory Legacy Survey of Space and Time (LSST) includes a series of Data Challenges (DCs) arranged by various LSST Scientific Collaborations that are taking place during the project's preoperational phase. The AGN Science Collaboration Data Challenge (AGNSC-DC) is a partial prototype of the expected LSST data on active galactic nuclei (AGNs), aimed at validating machine learning approaches for AGN selection and characterization in large surveys like LSST. The AGNSC-DC took place in 2021, focusing on accuracy, robustness, and scalability. The training and the blinded data sets were constructed to mimic the future LSST release catalogs using the data from the Sloan Digital Sky Survey Stripe 82 region and the XMM-Newton Large Scale Structure Survey region. Data features were divided into astrometry, photometry, color, morphology, redshift, and class label with the addition of variability features and images. We present the results of four submitted solutions to DCs using both classical and machine learning methods. We systematically test the performance of supervised models (support vector machine, random forest, extreme gradient boosting, artificial neural network, convolutional neural network) and unsupervised ones (deep embedding clustering) when applied to the problem of classifying/clustering sources as stars, galaxies, or AGNs. We obtained classification accuracy of 97.5% for supervised models and clustering accuracy of 96.0% for unsupervised ones and 95.0% with a classic approach for a blinded data set. We find that variability features significantly improve the accuracy of the trained models, and correlation analysis among different bands enables a fast and inexpensive first-order selection of quasar candidates.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Organic carbon content and turnover time in relation to pedogenic iron and aluminum in four temperate forest soils sampled in 2007

Soil organic carbon (SOC) can be stabilized via association with iron (Fe) and aluminum (Al) minerals. Fe and Al can be strong predictors of SOC storage and turnover in soils with relatively high extractable metals content and moderately acidic to circumneutral pH. Here we test whether pedogenic Fe and Al influence SOC content and turnover in soils with low Fe and Al content and acidic pH. In soils from four sites spanning three soil orders, we quantified the amount of Fe and Al in operationally-defined poorly crystalline and organically-complexed phases using selective chemical dissolution applied to the soil fraction containing mineral-associated carbon. We evaluated the correlations of Fe and Al concentrations, mean annual precipitation (MAP), mean annual temperature (MAT), and pH with SOC content and 14C-based turnover times. We found that poorly crystalline Fe and Al content predicted SOC turnover times (p < 0.0001) consistent with findings of previous studies, while organically-complexed Fe and Al content was a better predictor of SOC concentration (p < 0.0001). Greater site-level MAP (p < 0.0001) and colder site-level MAT (p < 0.0001) were correlated with longer SOC turnover times but were not correlated with SOC content. Our results suggest that poorly crystalline Fe and Al effectively slow the turnover of SOC in these acidic soils, even when their combined content in the soil is less than 2% by mass. However, in the strongly acidic Spodosol, organo-metal complexes tended to be less stable resulting in a more actively cycling mineral-associated SOC pool. We characterized mineralogy and carbon content in soils from four forested sites in the eastern deciduous forest zone that span three soil orders. Using selective chemical dissolution applied to the soil fraction containing mineral-associated carbon, we quantified the amount of Fe and Al in operationally-defined poorly crystalline and organically-complexed phases, and correlated these with previously published SOC content and 14C-based turnover times (McFarlane et al. 2013). This dataset comprises site characterization undertaken in 2007 (.png) and subsequent soil analyses (.csv containing C, Fe, Al, 14C-derived TurnoverTime) concluded in 2010.

54 ENVIRONMENTAL SCIENCES↗