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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15

Rapid Development of Gossamer Propulsion for NASA Inner Solar System Science Missions

Over a two and one-half year period dating from 2003 through 2005, NASA s In-Space Propulsion Program matured solar sail technology from laboratory components to full systems, demonstrated in as relevant a space environment as could feasibly be simulated on the ground. This paper describes the challenges identified; as well as the approaches taken toward solving a broad set of issues spanning material science, manufacturing technology, and interplanetary trajectory optimization. Revolutionary advances in system structural predictive analysis and characterization testing occurred. Also addressed are the remaining technology challenges that might be resolved with further ground technology research, geared toward reducing technical risks associated with future space validation and science missions.

Young, Roy M.↗

Vibration Analysis of the Space Shuttle External Tank Cable Tray Flight Data with and without PAL Ramp

External Tank Cable Tray vibration data for three successive Space Shuttle flights were analyzed to assess response to buffet and the effect of removal of the Protuberance Air Loads (PAL) ramp. Waveform integration, spectral analysis, cross-correlation analysis and wavelet analysis were employed to estimate vibration modes and temporal development of vibration motion from a sparse array of accelerometers and an on-board system that acquired 16 channels of data for approximately the first two minutes of each flight. The flight data indicated that PAL ramp removal had minimal effect on the fluctuating loads on the cable tray. The measured vibration frequencies and modes agreed well with predicted structural response.

Walker, B. E.↗

Vibration Analysis of the Space Shuttle External Tank Cable Tray Flight Data With and Without PAL Ramp

External Tank Cable Tray vibration data for three successive Space Shuttle flights were analyzed to assess response to buffet and the effect of removal of the Protuberance Air Loads (PAL) ramp. Waveform integration, spectral analysis, cross-correlation analysis and wavelet analysis were employed to estimate vibration modes and temporal development of vibration motion from a sparse array of accelerometers and an on-board system that acquired 16 channels of data for approximately the first 2 min of each flight. The flight data indicated that PAL ramp removal had minimal effect on the fluctuating loads on the cable tray. The measured vibration frequencies and modes agreed well with predicted structural response.

Walker, Bruce E.↗

Objectives and Progress on Ground Vibration Testing for the Ares Launch Vehicles

NASA has conducted dynamic tests on each of its major launch vehicles during the past 45 years. Each test has provided invaluable data to correlate and correct analytical models used to predict structural responses to differing dynamics for these vehicles. With both Saturn V and Space Shuttle, hardware changes were also required to the flight vehicles to ensure crew and vehicle safety. The Ares I IVGVT will undoubtedly provide similar valuable test data to support successful flights of the Constellation Program. The IVGVT will provide test determined natural frequencies, mode shapes and damping for the Ares I. This data will be used to support controls analysis by providing this test data to reduce uncertainty in the models. The value of this testing has been proven by past launch vehicle successes and failures. Performing dynamic testing on the Ares vehicles will provide confidence that the launch vehicles will be safe and successful in their missions. In addition, IVGVT will provide the following benefits for the Ares rockets: a) IVGVT data along with Ares development flights like Ares I-X, Ares I-Y, Ares I-X Prime, and Orion-1 or others will reduce the risk to the Orion-2 crew. IVGVT will permit anchoring the various analytical and operational models used in so many different aspects of Ares operations. b) IVGVT data will permit better understanding of the structural and GN&C margins of the spacecraft and may permit mass savings or expanded day-of-launch opportunities or fewer constraints to launch. c) Undoubtedly IVGVT will uncover some of the "unknown unknowns" so often seen in developing, launching, and flying new spacecraft vehicles and data from IVGVT may help prevent a loss of vehicle or crew. d) IVGVT also will be the first time Ares I flight-like hardware is transported, handled, rotated, mated, stacked, and integrated. e) Furthermore, handling and stacking the IVGVT launch vehicle stacks will be an opportunity to understand certain aspects of vehicle operability much better (for example, handling procedures, touch-labor time to accomplish tasks, access at interfaces, access to stage mating bolts, access to avionics boxes, access to the Interstage, GSE functionality, and many other important aspects of Ares I operability). All of these results will provide for better vehicle safety and better stewardship of national resources as NASA begins its next phase of human space exploration.

Tuma, Margaret L.↗

Nondestructive Evaluation and Monitoring Results from COPV Accelerated Stress Rupture Testing, NASA White Sands Test Facility (WSTF)

Develop and demonstrate NDE techniques for real-time characterization of CPVs and, where possible, identification of NDE capable of assessing stress rupture related strength degradation and/or making vessel life predictions (structural health monitoring or periodic inspection modes). Secondary: Provide the COPV user and materials community with quality carbon/epoxy (C/Ep) COPV stress rupture progression rate data. Aid in modeling, manufacturing, and application of COPVs for NASA spacecraft.

Saulsberry Regor↗

A High Performance Computing Approach to Tree Cover Delineation in 1-m NAIP Imagery Using a Probabilistic Learning Framework

Tree cover delineation is a useful instrument in deriving Above Ground Biomass (AGB) density estimates from Very High Resolution (VHR) airborne imagery data. Numerous algorithms have been designed to address this problem, but most of them do not scale to these datasets, which are of the order of terabytes. In this paper, we present a semi-automated probabilistic framework for the segmentation and classification of 1-m National Agriculture Imagery Program (NAIP) for tree-cover delineation for the whole of Continental United States, using a High Performance Computing Architecture. Classification is performed using a multi-layer Feedforward Backpropagation Neural Network and segmentation is performed using a Statistical Region Merging algorithm. The results from the classification and segmentation algorithms are then consolidated into a structured prediction framework using a discriminative undirected probabilistic graphical model based on Conditional Random Field, which helps in capturing the higher order contextual dependencies between neighboring pixels. Once the final probability maps are generated, the framework is updated and re-trained by relabeling misclassified image patches. This leads to a significant improvement in the true positive rates and reduction in false positive rates. The tree cover maps were generated for the whole state of California, spanning a total of 11,095 NAIP tiles covering a total geographical area of 163,696 sq. miles. The framework produced true positive rates of around 88% for fragmented forests and 74% for urban tree cover areas, with false positive rates lower than 2% for both landscapes. Comparative studies with the National Land Cover Data (NLCD) algorithm and the LiDAR canopy height model (CHM) showed the effectiveness of our framework for generating accurate high-resolution tree-cover maps.

Segments↗

DeepSAT: A Deep Learning Approach to Tree-Cover Delineation in 1-m NAIP Imagery for the Continental United States

High resolution tree cover classification maps are needed to increase the accuracy of current land ecosystem and climate model outputs. Limited studies are in place that demonstrates the state-of-the-art in deriving very high resolution (VHR) tree cover products. In addition, most methods heavily rely on commercial softwares that are difficult to scale given the region of study (e.g. continents to globe). Complexities in present approaches relate to (a) scalability of the algorithm, (b) large image data processing (compute and memory intensive), (c) computational cost, (d) massively parallel architecture, and (e) machine learning automation. In addition, VHR satellite datasets are of the order of terabytes and features extracted from these datasets are of the order of petabytes. In our present study, we have acquired the National Agriculture Imagery Program (NAIP) dataset for the Continental United States at a spatial resolution of 1-m. This data comes as image tiles (a total of quarter million image scenes with ~60 million pixels) and has a total size of ~65 terabytes for a single acquisition. Features extracted from the entire dataset would amount to ~8-10 petabytes. In our proposed approach, we have implemented a novel semi-automated machine learning algorithm rooted on the principles of "deep learning" to delineate the percentage of tree cover. Using the NASA Earth Exchange (NEX) initiative, we have developed an end-to-end architecture by integrating a segmentation module based on Statistical Region Merging, a classification algorithm using Deep Belief Network and a structured prediction algorithm using Conditional Random Fields to integrate the results from the segmentation and classification modules to create per-pixel class labels. The training process is scaled up using the power of GPUs and the prediction is scaled to quarter million NAIP tiles spanning the whole of Continental United States using the NEX HPC supercomputing cluster. An initial pilot over the state of California spanning a total of 11,095 NAIP tiles covering a total geographical area of 163,696 sq. miles has produced true positive rates of around 88 percent for fragmented forests and 74 percent for urban tree cover areas, with false positive rates lower than 2 percent for both landscapes.

Imagery↗

WFIRST Integral Field Spectrograph Design and Operations Concept

One important aspect of the WFIRST coronagraphic instrument (CGI) technology demonstration is its ability to take high contrast spectra with an integral field spectrograph (IFS). Future missions such as LUVOIR and HabEx rely on IFS technologies for the spectral characterization of any objects they discover; spectral characterization is the core science of their exoplanet imaging instruments. The CGI IFS, being designed and built and Goddard Space Flight Center, has a spectral resolution of R50 and is designed to accommodate a 20% bandpass spanning 600-970nm. The bands and spectral resolution were chosen by the science investigation teams to target key methane absorption features, with the aim of constraining abundances. For CGI as a technology demonstration, these are the minimum set of defining features to demonstrate on-orbit wavefront control with an IFS capable of producing science. The ability to close a wavefront control loop around an IFS, maintain a stable dark hole, and provide time resolved data that simultaneously spans spatial and spectral dimensions are crucial demonstrations for future observatories. We highlight the IFS requirements and how the on-orbit calibration is handled. We also provide further detail on the optomechanical design, its stability based on thermal and structural predictions, anticipated performance, and operations concept of the CGI IFS.

Groff, Tyler↗

WFIRST CGI: Prism and Polarizer Characterization Modes

As part of its technology demonstration, the WFIRST coronagraph instrument (CGI) will demonstrate point source spectroscopy and polarization measurements of disks. The specific implementation of spectroscopy is a zero-deviation Amici prism and slit to be placed on the planet after high contrast has been achieved by CGI. The polarization optics are a set of Wollaston prisms so that orthogonal polarization states can be measured simultaneously. The CGI spectral characterization mode, being designed and built and Goddard Space Flight Center (GSFC), has a spectral resolution of R50 and is designed to accommodate a 15% bandpass spanning 610-785nm. In order to recover Stokes information, there are two sets of Wollaston prisms clocked 45 degrees with respect to one another with each measurement taken in series. The Wollaston design and optical elements are a contribution by the Japanese Aerospace Exploration Agency, with final alignment and testing being done at GSFC. The spectroscopy mode is designed to target Methane absorption features around 730nm, keeping the spectral resolution as low as possible to improve the signal-to-noise ratio and hence reduce detection time. We highlight the requirements for these modes and address the challenge of on-orbit spectral calibration for a deployable slit in the presence of pointing drifts. Of unique interest is how the observatory error budget couples into good stellar spectrum calibration and subsequent speckle subtraction. We also provide further detail on the optomechanical design, its stability based on thermal and structural predictions, modeled performance, and operations concept. These performance metrics are simulated to demonstrate how a slit located at an arbitrary field point is homed onto the planet and converted to a calibrated spectrum.

Tyler D Groff↗

Development and application of vibroacoustic structural data banks in predicting vibration design and test criteria for rocket vehicle structures

A method of predicting broadband random vibration criteria for components on space vehicles is presented. Large amounts of vibration and acoustic data obtained from flights and static firing tests of space vehicle were formulated into vibroacoustic data banks for structural categories of ring frame, skin stringer, and honeycomb. The vibration spectra with their associated acoustic spectra are normalized to a reference acoustic spectrum. The individual normalized spectra are grouped according to definite structural characteristics and statistically analyzed to form the vibroacoustic data banks described in this report. These data banks represent the reference vibration criteria available for determining the new vehicle vibration criteria.

Bandgren, H. J.↗

Prediction of α $IIb$ $β$ 3 integrin structures along its minimum free energy activation pathway

The adhesion protein integrin is a transmembrane heterodimer that plays a pivotal role in cellular processes such as cell signaling and cell migration. To execute its function, integrin undergoes extensive conformational changes from a bent-closed to an extended-open state. Resolving the structures across these changes remains a challenge with both experimental and computational methods, but it is crucial for understanding the activation mechanism of integrin. We address this challenge for the platelet integrin α IIb β 3 by employing finite temperature string method with structures of the images along the initial guess path generated by a multiscale data-driven framework. The full-length all-atom structures along the resulting minimum free energy path between the inactive bent-closed and active extended-open states of α IIb β 3 integrin are consistent with a variety of experimentally resolved structures. Changes in these predicted structures along the path show that the extension and separation of the α and β subunits from the bent-closed to the extended-open state require correlated movements between the subdomain pairs in α IIb β 3 . Furthermore, these results provide new insights into integrin activation mechanism, and the predicted structures have potential applications in guiding the design of integrin-targeting therapeutics.

Dasetty, Siva [University of Chicago, IL (United S↗

Lifetime Reliability Prediction of Ceramic Structures Under Transient Thermomechanical Loads

An analytical methodology is developed to predict the probability of survival (reliability) of ceramic components subjected to harsh thermomechanical loads that can vary with time (transient reliability analysis). This capability enables more accurate prediction of ceramic component integrity against fracture in situations such as turbine startup and shutdown, operational vibrations, atmospheric reentry, or other rapid heating or cooling situations (thermal shock). The transient reliability analysis methodology developed herein incorporates the following features: fast-fracture transient analysis (reliability analysis without slow crack growth, SCG); transient analysis with SCG (reliability analysis with time-dependent damage due to SCG); a computationally efficient algorithm to compute the reliability for components subjected to repeated transient loading (block loading); cyclic fatigue modeling using a combined SCG and Walker fatigue law; proof testing for transient loads; and Weibull and fatigue parameters that are allowed to vary with temperature or time. Component-to-component variation in strength (stochastic strength response) is accounted for with the Weibull distribution, and either the principle of independent action or the Batdorf theory is used to predict the effect of multiaxial stresses on reliability. The reliability analysis can be performed either as a function of the component surface (for surface-distributed flaws) or component volume (for volume-distributed flaws). The transient reliability analysis capability has been added to the NASA CARES/ Life (Ceramic Analysis and Reliability Evaluation of Structures/Life) code. CARES/Life was also updated to interface with commercially available finite element analysis software, such as ANSYS, when used to model the effects of transient load histories. Examples are provided to demonstrate the features of the methodology as implemented in the CARES/Life program.

Nemeth, Noel N.↗

Displacement Theories for In-Flight Deformed Shape Predictions of Aerospace Structures

Displacement theories are developed for a variety of structures with the goal of providing real-time shape predictions for aerospace vehicles during flight. These theories are initially developed for a cantilever beam to predict the deformed shapes of the Helios flying wing. The main structural configuration of the Helios wing is a cantilever wing tubular spar subjected to bending, torsion, and combined bending and torsion loading. The displacement equations that are formulated are expressed in terms of strains measured at multiple sensing stations equally spaced on the surface of the wing spar. Displacement theories for other structures, such as tapered cantilever beams, two-point supported beams, wing boxes, and plates also are developed. The accuracy of the displacement theories is successfully validated by finite-element analysis and classical beam theory using input-strains generated by finite-element analysis. The displacement equations and associated strain-sensing system (such as fiber optic sensors) create a powerful means for in-flight deformation monitoring of aerospace structures. This method serves multiple purposes for structural shape sensing, loads monitoring, and structural health monitoring. Ultimately, the calculated displacement data can be visually displayed to the ground-based pilot or used as input to the control system to actively control the shape of structures during flight.

Ko, William L.↗

Random forest prediction of crystal structure from electron diffraction patterns incorporating multiple scattering

Diffraction is the most common method to solve for unknown or partially known crystal structures. However, it remains a challenge to determine the crystal structure of a new material that may have nanoscale size or heterogeneities. Here, in this study, we train an architecture of hierarchical random forest models capable of predicting the crystal system, space group, and lattice parameters from one or more unknown two-dimensional electron diffraction patterns. Our initial model correctly identifies the crystal system of a simulated electron diffraction pattern from a 20-nm-thick specimen of arbitrary orientation 67% of the time. We achieve a topline accuracy of 79% when aggregating predictions from ten patterns of the same material but different zone axes. The space group and lattice predictions range from 70% to 90% accuracy and median errors of 0.01-0.5Å, respectively, for cubic, hexagonal, trigonal, and tetragonal crystal systems while being less reliable on orthorhombic and monoclinic systems. We apply this architecture to a four-dimensional scanning transmission electron microscopy scan of gold nanoparticles, where it accurately predicts the crystal structure and lattice constants. These random forest models can be used to significantly accelerate the analysis of electron diffraction patterns, particularly in the case of unknown crystal structures. Additionally, due to the speed of inference, these models could be integrated into live transmission electron microscopy experiments, allowing real-Time labeling of a specimen.

36 MATERIALS SCIENCE↗

Nonlinear Analysis and Scaling Laws for Noncircular Composite Structures Subjected to Combined Loads

Results from an analytical study of the response of a built-up, multi-cell noncircular composite structure subjected to combined internal pressure and mechanical loads are presented. Nondimensional parameters and scaling laws based on a first-order shear-deformation plate theory are derived for this noncircular composite structure. The scaling laws are used to design sub-scale structural models for predicting the structural response of a full-scale structure representative of a portion of a blended-wing-body transport aircraft. Because of the complexity of the full-scale structure, some of the similitude conditions are relaxed for the sub-scale structural models. Results from a systematic parametric study are used to determine the effects of relaxing selected similitude conditions on the sensitivity of the effectiveness of using the sub-scale structural model response characteristics for predicting the full-scale structure response characteristics.

Hilburger, Mark W.↗

Methods for evaluating the predictive accuracy of structural dynamic models

Uncertainty of frequency response using the fuzzy set method and on-orbit response prediction using laboratory test data to refine an analytical model are emphasized with respect to large space structures. Two aspects of the fuzzy set approach were investigated relative to its application to large structural dynamics problems: (1) minimizing the number of parameters involved in computing possible intervals; and (2) the treatment of extrema which may occur in the parameter space enclosed by all possible combinations of the important parameters of the model. Extensive printer graphics were added to the SSID code to help facilitate model verification, and an application of this code to the LaRC Ten Bay Truss is included in the appendix to illustrate this graphics capability.

Hasselman, T. K.↗