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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Effects of Short- and Long-Duration Space Flight on Neuromuscular Function

The Functional Task Tests (FTT) is an interdisciplinary study designed to correlate the changes in functional tasks (such as emergency egress, ladder climbing, and hatch opening) with changes in neuromuscular, cardiovascular, and sensorimotor function. One aspect of the FTT, the neuromuscular function test, is used to investigate the neuromuscular component underlying changes in the ability of astronauts to perform functional tasks (representative of critical mission tasks) safely and quickly after flight. PURPOSE: To describe neuromuscular function after short- and long-duration space flight. METHODS: To date, 5 crewmembers on short-duration (10- to 15-day) missions and 3 on long-duration missions have participated. Crewmembers were assessed 30 days before flight, on landing day (short-duration subjects only) and 1, 6, and 30 days after landing. The interpolated twitch technique, which utilizes a combination of maximal voluntary contractions and electrically evoked contractions, was used to assess the maximal voluntary isometric force (MIF) and central activation capacity of the knee extensors. Leg-press and bench-press devices were used to assess MIF and maximal dynamic power of the lower and upper body respectively. Specifically, power was measured during concentric-only ballistic throws of the leg-press sled and bench-press bar loaded to 40% and 30% of MIF respectively. RESULTS: Data are currently being collected from both Shuttle and ISS crewmembers. Emerging data indicate that measures of knee extensor muscle function are decreased with long-duration flight. DISCUSSION: The relationships between flight duration, neural drive, and muscle performance are of particular interest. Ongoing research will add to the current sample size and will focus on defining changes in muscle performance measures after long-duration space flight.

Buxton, Roxanne E.↗
NASA NTRS2012

Arctic Tundra Vegetation Functional Types Based on Photosynthetic Physiology and Optical Properties

Climate change in tundra regions may alter vegetation species composition and ecosystem carbon balance. Remote sensing provides critical tools for monitoring these changes as optical signals provide a way to scale from plot measurements to regional patterns. Gas exchange measurements of pure patches of key vegetation functional types (lichens, mosses, and vascular plants) in sedge tundra at Barrow AK, show three significantly different values of light use efficiency (LUE) with values of 0.013+/-0.001, 0.0018+/-0.0002, and 0.0012 0.0001 mol C/mol absorbed quanta for vascular plants, mosses and lichens, respectively. Further, discriminant analysis of patch reflectance identifies five spectral bands that can separate each vegetation functional type as well as nongreen material (bare soil, standing water, and dead leaves). These results were tested along a 100 m transect where midsummer spectral reflectance and vegetation coverage were measured at one meter intervals. Area-averaged canopy LUE estimated from coverage fractions of the three functional types varied widely, even over short distances. Patch-level statistical discriminant functions applied to in situ hyperspectral reflectance successfully unmixed cover fractions of the vegetation functional types. These functions, developed from the tram data, were applied to 30 m spatial resolution Earth Observing-1 Hyperion imaging spectrometer data to examine regional variability in distribution of the vegetation functional types and from those distributions, the variability of LUE. Across the landscape, there was a fivefold variation in tundra LUE that was correlated to a spectral vegetation index developed to detect vegetation chlorophyll content.

Huemmrich, Karl F.↗
NASA NTRS2012

First-and Second-Order Displacement Transfer Functions for Structural Shape Calculations Using Analytically Predicted Surface Strains

New first- and second-order displacement transfer functions have been developed for deformed shape calculations of nonuniform cross-sectional beam structures such as aircraft wings. The displacement transfer functions are expressed explicitly in terms of beam geometrical parameters and surface strains (uniaxial bending strains) obtained at equally spaced strain stations along the surface of the beam structure. By inputting the measured or analytically calculated surface strains into the displacement transfer functions, one could calculate local slopes, deflections, and cross-sectional twist angles of the nonuniform beam structure for mapping the overall structural deformed shapes for visual display. The accuracy of deformed shape calculations by the first- and second-order displacement transfer functions are determined by comparing these values to the analytically predicted values obtained from finite element analyses. This comparison shows that the new displacement transfer functions could quite accurately calculate the deformed shapes of tapered cantilever tubular beams with different tapered angles. The accuracy of the present displacement transfer functions also are compared to those of the previously developed displacement transfer functions.

Ko, William L.↗
NASA NTRS2012

Improved Displacement Transfer Functions for Structure Deformed Shape Predictions Using Discretely Distributed Surface Strains

In the formulations of earlier Displacement Transfer Functions for structure shape predictions, the surface strain distributions, along a strain-sensing line, were represented with piecewise linear functions. To improve the shape-prediction accuracies, Improved Displacement Transfer Functions were formulated using piecewise nonlinear strain representations. Through discretization of an embedded beam (depth-wise cross section of a structure along a strain-sensing line) into multiple small domains, piecewise nonlinear functions were used to describe the surface strain distributions along the discretized embedded beam. Such piecewise approach enabled the piecewise integrations of the embedded beam curvature equations to yield slope and deflection equations in recursive forms. The resulting Improved Displacement Transfer Functions, written in summation forms, were expressed in terms of beam geometrical parameters and surface strains along the strain-sensing line. By feeding the surface strains into the Improved Displacement Transfer Functions, structural deflections could be calculated at multiple points for mapping out the overall structural deformed shapes for visual display. The shape-prediction accuracies of the Improved Displacement Transfer Functions were then examined in view of finite-element-calculated deflections using different tapered cantilever tubular beams. It was found that by using the piecewise nonlinear strain representations, the shape-prediction accuracies could be greatly improved, especially for highly-tapered cantilever tubular beams.

Ko, William L.↗
NASA NTRS2013

Controlled, Site-Specific Functionalization of Carbon Nanotubes with Diazonium Salts

This work uses existing technologies to prepare a crossbar architecture of nano tubes, wherein one nanotube is fixed to a substrate, and a second nanotube is suspended a finite distance above. Both nano tubes can be individually addressed electrically. Application of opposite potentials to the two tubes causes the top tube to deform and to essentially come into contact with the lower tube. Contact here refers not to actual, physical contact, but rather within an infinitesimally small distance referred to as van der Walls contact, in which the entities may influence each other on a molecular and electronic scale. First, the top tube is physically deformed, leading to a potentially higher chemical reactivity at the point of deformation, based on current understanding of the effects of curvature strain on reactivity. This feature would allow selective functionalization at the junction via reaction with diazonium salts. Secondly, higher potential is achieved at the point of "cross" between the tubes. In a pending patent application, a method is claimed for directed self-assembly of molecular components onto the surface of metal or conductive materials by application of potential to the metal or conductive surface. In another pending patent application, a method is claimed for attaching molecules to the surface of nanotubes via the use of reactive diazonium salts. In the present invention, the directed functionalization of the crossed-nanotube junctions by applying a potential to the ends of the nanotubes in the presence of reactive diazonium slats, or other reactive molecular species is claimed. The diazonium salts are directed by the potential existing at the junction to react with the surface of the nanotube, thus placing functional molecular components at the junctions. The crossed nano tubes therefore provide a method of directly addressing the functionalized molecules, which have been shown to function as molecular switches, molecular wires, and in other capacities and uses. Site-specific functionalization may enable the use of nanotubes in molecular electronic applications because device functionality is critical at the cross points.

Tour, James M.↗
NASA NTRS2015

The Effects of Long Duration Bed Rest as a Spaceflight Analogue on Resting State Sensorimotor Network Functional Connectivity and Neurocognitive Performance

Long duration spaceflight has been associated with detrimental alterations in human sensorimotor systems and neurocognitive performance. Prolonged exposure to a head-down tilt position during long duration bed rest can resemble several effects of the microgravity environment such as reduced sensory inputs, body unloading and increased cephalic fluid distribution. The question of whether microgravity affects other central nervous system functions such as brain functional connectivity and its relationship with neurocognitive performance is largely unknown, but of potential importance to the health and performance of astronauts both during and post-flight. The aims of the present study are 1) to identify changes in sensorimotor resting state functional connectivity that occur with extended bed rest exposure, and to characterize their recovery time course; 2) to evaluate how these neural changes correlate with neurocognitive performance. Resting-state functional magnetic resonance imaging (rsfMRI) data were collected from 17 male participants. The data were acquired through the NASA bed rest facility, located at the University of Texas Medical Branch (Galveston, TX). Participants remained in bed with their heads tilted down six degrees below their feet for 70 consecutive days. RsfMRI data were obtained at seven time points: 7 and 12 days before bed rest; 7, 50, and 65 days during bed rest; and 7 and 12 days after bed rest. Functional connectivity magnetic resonance imaging (fcMRI) analysis was performed to measure the connectivity of sensorimotor networks in the brain before, during, and post-bed rest. We found a decrease in left putamen connectivity with the pre- and post-central gyri from pre bed rest to the last day in bed rest. In addition, vestibular cortex connectivity with the posterior cingulate cortex decreased from pre to post bed rest. Furthermore, connectivity between cerebellar right superior posterior fissure and other cerebellar regions decreased from pre bed rest to the last day in bed rest. In contrast, connectivity within the default mode network remained stable over the course of bed rest. We also utilized a battery of behavioral measures including spatial working memory tasks and measures of functional mobility and balance. These behavioral measurements were collected before, during, and after bed rest. We will report the preliminary findings of correlations observed between brain functional connectivity and behavioral performance changes. Our results suggest that sensorimotor brain networks exhibit decoupling with extended periods of reduced usage. The findings from this study could aid in the understanding and future design of targeted countermeasures to alleviate the detrimental health and neurocognitive effects of long-duration spaceflight.

Cassady, K.↗
NASA NTRS2016

Simple Test Functions in Meshless Local Petrov-Galerkin Methods

Two meshless local Petrov-Galerkin (MLPG) methods based on two different trial functions but that use a simple linear test function were developed for beam and column problems. These methods used generalized moving least squares (GMLS) and radial basis (RB) interpolation functions as trial functions. These two methods were tested on various patch test problems. Both methods passed the patch tests successfully. Then the methods were applied to various beam vibration problems and problems involving Euler and Beck's columns. Both methods yielded accurate solutions for all problems studied. The simple linear test function offers considerable savings in computing efforts as the domain integrals involved in the weak form are avoided. The two methods based on this simple linear test function method produced accurate results for frequencies and buckling loads. Of the two methods studied, the method with radial basis trial functions is very attractive as the method is simple, accurate, and robust.

Raju, Ivatury S.↗
NASA NTRS2017

Kepler Planet Detection Metrics: Window and One-Sigma Depth Functions for Data Release 25

This document describes the window and one-sigma depth functions relevant to the Transiting Planet Search (TPS) algorithm in the Kepler pipeline (Jenkins 2002; Jenkins et al. 2017). The window function specifies the fraction of unique orbital ephemeris epochs over which three transits are observable as a function of orbital period. In this context, the epoch and orbital period, together, comprise the ephemeris of an orbiting companion, and ephemerides with the same period are considered equivalent if their epochs differ by an integer multiple of the period. The one-sigma depth function specifies the depth of a signal (in ppm) for a given light curve that results in a one-sigma detection of a transit signature as a function of orbital period when averaged over all unique orbital ephemerides. These planet detection metrics quantify the ability of TPS to detect a transiting planet signature on a star-by-star basis. They are uniquely applicable to a specific Kepler data release, since they are dependent on the details of the light curves searched and the functionality of the TPS algorithm used to perform the search. This document describes the window and one-sigma depth functions relevant to Kepler Data Release 25 (DR25), where the data were processed (Thompson et al. 2016) and searched (Twicken et al. 2016) with the SOC 9.3 pipeline. In Section 4, we describe significant differences from those reported in Kepler Data Release 24 (Burke Seader 2016) and document our verification method.

Planet Detection Metrics↗
NASA NTRS2017

Comparison of Two Bioinformatics Tools Used to Characterize the Microbial Diversity and Predictive Functional Attributes of Microbial Mats from Lake Obersee, Antarctica

In this study, using NextGen sequencing of the collective 16S rRNA genes obtained from two sets of samples collected from Lake Obersee, Antarctica, we compared and contrasted two bioinformatics tools, PICRUSt and Tax4Fun. We then developed an R script to assess the taxonomic and predictive functional profiles of the microbial communities within the samples. Taxa such as Pseudoxanthomonas, Planctomycetaceae, Cyanobacteria Subsection III, Nitrosomonadaceae, Leptothrix, and Rhodobacter were exclusively identified by Tax4Fun that uses SILVA database; whereas PICRUSt that uses Greengenes database uniquely identified Pirellulaceae, Gemmatimonadetes A1-B1, Pseudanabaena, Salinibacterium and Sinibacteraceae. Predictive functional profiling of the microbial communities using Tax4Fun and PICRUSt separately revealed common metabolic capabilities, while also showing specific functional IDs not shared between the two approaches. Combining these functional predictions using a customized R script revealed a more inclusive metabolic profile, such as hydrolases, oxidoreductases, transferases; enzymes involved in carbohydrate and amino acid metabolisms; and membrane transport proteins known for nutrient uptake from the surrounding environment. Our results present the first molecular-phylogenetic characterization and predictive functional profiles of the microbial mat communities in Lake Obersee, while demonstrating the efficacy of combining both the taxonomic assignment information and functional IDs using the R script created in this study for a more streamlined evaluation of predictive functional profiles of microbial communities.

Hyunmin Koo↗
NASA NTRS2019

Experimentally-Derived Bidirectional Reflectance Distribution Function Data in Support of the Orbital Debris Program Office

The NASA Orbital Debris Program Office (ODPO) has used various optical assets to acquire photometric data of Earth-orbiting objects to define the orbital debris environment. To better characterize and model optical data acquired from ground-based telescopes, the Optical Measurements Center (OMC) at NASA Johnson Space Center emulates illumination conditions seen in space by using equipment and techniques that parallel telescopic observations and source-target-sensor orientations. One of the OMC goals is to improve the size calculation used for optical data by developing an optical-based Size Estimation Model. The current size estimation requires applying a Lambertian phase function, a set albedo value, and range to the observed magnitude. The first step to improving the sampled brightness of laboratory targets is to remove aspect-angle dependencies. Then, the volume of possible object viewing angles is sampled at 21 combinations of azimuth and zenith angles for each solar phase angle. Finally, the acquired images are input into an image processing program that generates approximations for the object’s Bidirectional Reflectance Distribution Function (BRDF) and phase function. The BRDF is a radiometric concept that identifies an object’s material composition by matching a BRDF approximated with photometric data collected by ground-based telescopes with a BRDF generated experimentally from a known object in the laboratory. This paper discusses the validation of experimental BRDF and phase function approximations produced in the OMC and how the findings will be incorporated into ODPO models. A Lambertian sphere is imaged and the subsequent experimental functions are scrutinized to confirm that they correspond to an object that has an isotropic luminance. With the image processing algorithm validated, test objects with varying optical properties are then imaged to confirm that the produced photometric functions are both unique and repeatable. Once the validation is complete, the OMC will be used to evaluate a subset of fragments from a hypervelocity impact test of a mock-up satellite and assess the appropriate phase function and size estimates using BRDF measurements for a large volume of targets composed of various shapes, sizes, and materials.

Orbital Debris Program Office (ODPO)↗
NASA NTRS2019

A Comparative Study on Computation of Cumulative Distribution Function in Predicting Time of Failure of Engineering Systems

Estimating accurate Time-of-Failure (ToF) of a system is key in making the decisions that impact operational safety and optimize cost. In this context, it is interesting to note that different approaches have been explored to tackle the problem of estimating ToF. The difference is in part characterized by different definitions of the hazard zones. The conventional definition for the cumulative distribution function (CDF) calculation is assumed to have well-defined hazard zones, that is, hazard zones defined as a function of the system state trajectory. An alternate method suggests the use of hazard zones defined as a function of the system state at time , instead of hazard zones defined as a function of system state up to and including time k (Acuna and Orchard 2018, 2017). This paper explores these differences and their impact on ToF estimation. Results for the conventional CDF definition indicated that, (i) the cumulative distribution function is always an increasing function of time, even when realizations of the degradation process are not monotonic, (ii) the sum of all probabilities is always 1 and does not need to be normalized, and (iii) all probabilities are positive and less than or equal to 1. Similar results are not observed for CDF calculation with hazard zones defined as a function only of the system state at time . Results for ToF estimation using Acuna's definition differ, suggesting that there is an underlying assumption of independence in the hazard zone definition. Therefore, we present an alternate definition of hazard zone which guarantees the properties of a well-defined CDF with a more straightforward ToF definition.

Hazard Zone↗
NASA NTRS2022

Further Development of a Function Generator Technique

Further features and properties of functions generated by generalization of the process originally uncovered to describe the evolution of pressure in a rigid volume due to outgassing or desorption are explored. Properties presented include development of a general Maclaurin series associated with these functions, a limitation in using integration by parts to produce asymptotic expansions, and a general description of an implicit Adams-Moulton method for numerical quadrature of transformed functions. These developments are then applied to develop and explore functions that solve the Sievert integral and the modified Bessel function of the first kind, order zero. Features of the error function and the incomplete lower gamma function are also considered.

Michael S. Woronowicz↗
NASA NTRSDate not supplied

Sampling Functions from Gaussian Processes and Structured Covariance Gaussian Networks

When learning aerodynamic models from data, it is critical to incorporate estimates of model uncertainty. This motivates the design of probabilistic aerodynamic databases which can be sampled to generate physically and statistically plausible aerodynamic models. In this talk we discuss how to sample deterministic functions from two different kinds of probabilistic models and demonstrate their use. First, Gaussian Process Regressors (GPRs) are a widely used probabilistic kernel-based model which can be thought of as Gaussian distributions over functions. GPRs are generally trained by maximizing the marginal likelihood of seeing the training data over the kernel parameter space. Sample functions are easily generated by drawing points from the Gaussian distribution at desired input points. However, when the points are not known ahead of time, the classical sampling approach is not possible since successive function samples will generate different function realizations. We present an approach for sampling consistent function evaluations from a GPR over multiple samples. Second, we describe a neural network architecture which learns a conditional Gaussian distribution by maximizing the marginal likelihood at each point in the input space. We then discuss and compare several options for generating sample functions which match this distribution. Finally, we demonstrate the use of these probabilistic aerodynamic models in an atmospheric reentry simulation.

Gaussian process regression↗
DOE OSTI2023

Elastic functional changepoint detection of climate impacts from localized sources

Detecting changepoints in functional data has become an important problem as interest in monitoring of climate phenomenon has increased, where the data is functional in nature. Here, the observed data often contains both amplitude (y-axis) and phase (x-axis) variability. If not accounted for properly, true changepoints may be undetected, and the estimated underlying mean change functions will be incorrect. In this article, an elastic functional changepoint method is developed which properly accounts for these types of variability. The method can detect amplitude and phase changepoints which current methods in the literature do not, as they focus solely on the amplitude changepoint. This method can easily be implemented using the functions directly or can be computed via functional principal component analysis to ease the computational burden. We apply the method and its nonelastic competitors to both simulated data and observed data to show its efficiency in handling data with phase variation with both amplitude and phase changepoints. We use the method to evaluate potential changes in stratospheric temperature due to the eruption of Mt. Pinatubo in the Philippines in June 1991. Using an epidemic changepoint model, we find evidence of a increase in stratospheric temperature during a period that contains the immediate aftermath of Mt. Pinatubo, with most detected changepoints occurring in the tropics as expected.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Exact constraints and appropriate norms in machine-learned exchange-correlation functionals

Machine learning techniques have received growing attention as an alternative strategy for developing general-purpose density functional approximations, augmenting the historically successful approach of human-designed functionals derived to obey mathematical constraints known for the exact exchange-correlation functional. More recently, efforts have been made to reconcile the two techniques, integrating machine learning and exact-constraint satisfaction. We continue this integrated approach, designing a deep neural network that exploits the exact constraint and appropriate norm philosophy to de-orbitalize the strongly constrained and appropriately normed (SCAN) functional. The deep neural network is trained to replicate the SCAN functional from only electron density and local derivative information, avoiding the use of the orbital-dependent kinetic energy density. The performance and transferability of the machine-learned functional are demonstrated for molecular and periodic systems.

Artificial neural networks↗
DOE OSTI2023

The Predictive Power of Exact Constraints and Appropriate Norms in Density Functional Theory

Ground-state Kohn-Sham density functional theory provides, in principle, the exact ground-state energy and electronic spin densities of real interacting electrons in a static external potential. In practice, the exact density functional for the exchange-correlation (xc) energy must be approximated in a computationally efficient way. About 20 mathematical properties of the exact xc functional are known. In this work, we review and discuss these known constraints on the xc energy and hole. By analyzing a sequence of increasingly sophisticated density functional approximations (DFAs), we argue that (a) the satisfaction of more exact constraints and appropriate norms makes a functional more predictive over the immense space of many-electron systems and (b) fitting to bonded systems yields an interpolative DFA that may not extrapolate well to systems unlike those in the fitting set. We discuss both how the class of well-described systems has grown along with constraint satisfaction and the possibilities for future functional development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Hierarchical Self‐Assembly of Multidimensional Functional Materials from Sequence‐Defined Peptoids

Abstract Hierarchical self‐assembly represents a powerful strategy for the fabrication of functional materials across various length scales. However, achieving precise formation of functional hierarchical assemblies remains a significant challenge and requires a profound understanding of molecular assembly interactions. In this study, we present a molecular‐level understanding of the hierarchical assembly of sequence‐defined peptoids into multidimensional functional materials, including twisted nanotube bundles serving as a highly efficient artificial light harvesting system. By employing synchrotron‐based powder X‐ray diffraction and analyzing single crystal structures of model compounds, we elucidated the molecular packing and mechanisms underlying the assembly of peptoids into multidimensional nanostructures. Our findings demonstrate that incorporating aromatic functional groups, such as tetraphenyl ethylene (TPE), at the termini of assembling peptoid sequences promotes the formation of twisted bundles of nanotubes and nanosheets, thus enabling the creation of a highly efficient artificial light harvesting system. This research exemplifies the potential of leveraging sequence‐defined synthetic polymers to translate microscopic molecular structures into macroscopic assemblies. It holds promise for the development of functional materials with precisely controlled hierarchical structures and designed functions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Assessing the Performance of Exchange‐Correlation Density Functionals in Describing the Iron‐Catalyzed Ammonia Synthesis System

Density functional theory (DFT) has been widely employed for elucidating mechanistic aspects of heterogeneous catalysis. However, the accuracy of DFT calculations relies heavily on selecting an exchange-correlation (XC) functional that correctly describes the electronic structure of materials involved in the reactions. This study assesses the accuracy of several XC density functionals for modeling the iron-catalyzed ammonia synthesis system. In the assessment of functional accuracy, experimental references are compared to DFT-calculated values for the formation energy of gas-phase ammonia and nitrogen, bulk Fe/Fe-nitride (γ′-Fe 4 N) lattice constants and cohesive/formation energies, and nitrogen and ammonia binding energies on Fe(100), Fe(111), Fe(110), and γ′-Fe 4 N(111). It is observed that the experimental value for each of these descriptors is accurately modeled by at least one functional. RPBE alone provides reliable estimates for both the lattice constant and cohesive energy of Fe and γ′-Fe 4 N. Temperature-programmed desorption experiments led to estimates for N and NH 3 adsorption across several Fe-based facets that are best captured by RPBE. These results highlight the importance of choosing an appropriate XC functional that accurately describes experimental systems and offer insights into effectively modeling the interactions between nitrogen and ammonia on Fe-based surfaces.

adsorption↗