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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Laser annealing of amorphous/poly: Silicon solar cell material flight experiment

The preliminary design proposed for the microelectronics materials processing equipment is presented. An overall mission profile, description of all processing steps, analysis methods and measurement techniques, data acquisition and storage, and a preview of the experimental hardware are included. The goal of the project is to investigate the viability of material processing of semiconductor microelectronics materials in a micro-gravity environment. The two key processes are examined: (1) Rapid Thermal Annealing (RTA) of semiconductor thin films and damaged solar cells, and (2) thin film deposition using a filament evaporator. The RTA process will be used to obtain higher quality crystalline properties from amorphous/poly-silicon films. RTA methods can also be used to repair radiation-damaged solar cells. On earth this technique is commonly used to anneal semiconductor films after ion-implantation. The damage to the crystal lattice is similar to the defects found in solar cells which have been exposed to high-energy particle bombardment.

Cole, Eric E.↗
NASA NTRS1991

Automation for deep space vehicle monitoring

Information on automation for deep space vehicle monitoring is given in viewgraph form. Information is given on automation goals and strategy; the Monitor Analyzer of Real-time Voyager Engineering Link (MARVEL); intelligent input data management; decision theory for making tradeoffs; dynamic tradeoff evaluation; evaluation of anomaly detection results; evaluation of data management methods; system level analysis with cooperating expert systems; the distributed architecture of multiple expert systems; and event driven response.

Schwuttke, Ursula M.↗
NASA NTRS1992

Transient loads analysis for space flight applications

A significant part of the flight readiness verification process involves transient analysis of the coupled Shuttle-payload system to determine the low frequency transient loads. This paper describes a methodology for transient loads analysis and its implementation for the Spacelab Life Sciences Mission. The analysis is carried out using two major software tools - NASTRAN and an external FORTRAN code called EZTRAN. This approach is adopted to overcome some of the limitations of NASTRAN's standard transient analysis capabilities. The method uses Data Recovery Matrices (DRM) to improve computational efficiency. The mode acceleration method is fully implemented in the DRM formulation to recover accurate displacements, stresses, and forces. The advantages of the method are demonstrated through a numerical example.

Thampi, S. K.↗
NASA NTRS1957

Comparison of several methods for obtaining the time response of linear systems to either a unit impulse or arbitrary input from frequency-response data

Several methods of obtaining the time response of Linear systems to either a unit impulse or an arbitrary input from frequency-response data are described and compared. Comparisons indicate that all the methods give good accuracy when applied to a second-order system; the main difference is the required computing time. The methods generally classified as inverse Laplace transform methods were found to be most effective in determining the response to a unit impulse from frequency-response data of higher order systems. Some discussion and examples are given of the use of such methods as flight-data-analysis techniques in predicting loads and motions of a flexible aircraft on the basis of simple calculations when the aircraft frequency response is known.

Donegan, James J↗
NASA NTRS1995

Multi-modal virtual environment research at Armstrong Laboratory

One mission of the Paul M. Fitts Human Engineering Division of Armstrong Laboratory is to improve the user interface for complex systems through user-centered exploratory development and research activities. In support of this goal, many current projects attempt to advance and exploit user-interface concepts made possible by virtual reality (VR) technologies. Virtual environments may be used as a general purpose interface medium, an alternative display/control method, a data visualization and analysis tool, or a graphically based performance assessment tool. An overview is given of research projects within the division on prototype interface hardware/software development, integrated interface concept development, interface design and evaluation tool development, and user and mission performance evaluation tool development.

Eggleston, Robert G.↗
NASA NTRS1997

A Model for Space Shuttle Orbiter Tire Side Forces Based on NASA Landing Systems Research Aircraft Test Results

Forces generated by the Space Shuttle orbiter tire under varying vertical load, slip angle, speed, and surface conditions were measured using the Landing System Research Aircraft (LSRA). Resulting data were used to calculate a mathematical model for predicting tire forces in orbiter simulations. Tire side and drag forces experienced by an orbiter tire are cataloged as a function of vertical load and slip angle. The mathematical model is compared to existing tire force models for the Space Shuttle orbiter. This report describes the LSRA and a typical test sequence. Testing methods, data reduction, and error analysis are presented. The LSRA testing was conducted on concrete and lakebed runways at the Edwards Air Force Flight Test Center and on concrete runways at the Kennedy Space Center (KSC). Wet runway tire force tests were performed on test strips made at the KSC using different surfacing techniques. Data were corrected for ply steer forces and conicity.

Carter, John F.↗
NASA NTRS1996

Prediction Capability for Transonic Nozzle Afterbodies Improved

Under the High Speed Research (HSR) Program, the NASA Lewis Research Center, the NASA Langley Research Center, and the aerospace industry have been developing exhaust nozzle concepts for a future High Speed Civil Transport (HSCT). For such an aircraft to be both economically viable and environmentally acceptable, the exhaust nozzles must combine highly efficient operation throughout the flight envelope with low noise levels at takeoff. A team composed of researchers from Lewis, Langley, and McDonnell Douglas created a two-dimensional data base using computational fluid dynamics. First, each group validated their computational fluid dynamics code against existing experimental data to gain confidence in the code's results. Next, the organizations analyzed several configurations, and the results were used to create the new data base. Then, the analysis methods were updated to account for the effects of two-dimensional nozzles. This will result in a more accurate analysis of the propulsion system for the High Speed Civil Transport.

Source record↗
NASA NTRS2012

Subscale and Full-Scale Testing of Buckling-Critical Launch Vehicle Shell Structures

New analysis-based shell buckling design factors (aka knockdown factors), along with associated design and analysis technologies, are being developed by NASA for the design of launch vehicle structures. Preliminary design studies indicate that implementation of these new knockdown factors can enable significant reductions in mass and mass-growth in these vehicles and can help mitigate some of NASA s launch vehicle development and performance risks by reducing the reliance on testing, providing high-fidelity estimates of structural performance, reliability, robustness, and enable increased payload capability. However, in order to validate any new analysis-based design data or methods, a series of carefully designed and executed structural tests are required at both the subscale and full-scale level. This paper describes recent buckling test efforts at NASA on two different orthogrid-stiffened metallic cylindrical shell test articles. One of the test articles was an 8-ft-diameter orthogrid-stiffened cylinder and was subjected to an axial compression load. The second test article was a 27.5-ft-diameter Space Shuttle External Tank-derived cylinder and was subjected to combined internal pressure and axial compression.

Hilburger, Mark W.↗
NASA NTRS2014

Waveforms and Sonic Boom Perception and Response (WSPR): Low-Boom Community Response Program Pilot Test Design, Execution, and Analysis

The Waveforms and Sonic boom Perception and Response (WSPR) Program was designed to test and demonstrate the applicability and effectiveness of techniques to gather data relating human subjective response to multiple low-amplitude sonic booms. It was in essence a practice session for future wider scale testing on naive communities, using a purpose built low-boom demonstrator aircraft. The low-boom community response pilot experiment was conducted in California in November 2011. The WSPR team acquired sufficient data to assess and evaluate the effectiveness of the various physical and psychological data gathering techniques and analysis methods.

Page, Juliet A.↗
NASA NTRS2016

You Can't Reach for the Stars if You are Tripping Over the Ground! (Preventing Slips, Trips, and Falls)

Although there are very few mishaps related to ground, vehicle or payload processing at the Kennedy Space Center (KSC), employees have experienced a significant number of injuries due to slips, trips, and falls outside of performing flight processing operations. Slips, trips, and falls are major causes of occupational injuries at KSC, the National Aeronautics and Space Administration (NASA), and in general industry. To help KSC employees avoid these injuries, and allow them to be fully productive, KSC launched an initiative in 2013 to reduce slips, trips, and falls. This initiative is based on a four-part model focusing on DATA analysis, HAZARD awareness, PREVENTIVE methods, and BALANCE.

Falls↗
NASA NTRS2017

Thermal Radiation Anomalies Associated with Major Earthquakes

Recent developments of remote sensing methods for Earth satellite data analysis contribute to our understanding of earthquake related thermal anomalies. It was realized that the thermal heat fluxes over areas of earthquake preparation is a result of air ionization by radon (and other gases) and consequent water vapor condensation on newly formed ions. Latent heat (LH) is released as a result of this process and leads to the formation of local thermal radiation anomalies (TRA) known as OLR (outgoing Longwave radiation, Ouzounov et al, 2007). We compare the LH energy, obtained by integrating surface latent heat flux (SLHF) over the area and time with released energies associated with these events. Extended studies of the TRA using the data from the most recent major earthquakes allowed establishing the main morphological features. It was also established that the TRA are the part of more complex chain of the short-term pre-earthquake generation, which is explained within the framework of a lithosphere-atmosphere coupling processes.

Ouzounov, Dimitar↗
DOE OSTI2021

Deciphering Degradation: Machine Learning on Real-World Performance Data (Final Report)

This project addresses a fundamental flaw in solar PV research and solar project financing; the assumed rate of degradation for solar plants. The solar industry currently relies on an out-dated report that observed a 0.5% degradation rate based on a small sample size of systems (~100). While the research conducted at the time was new and innovative, the solar community has not updated this research and universally applies this 0.5% degradation assumption in financial models. Our project updates this assumption by analyzing observed degradation from the industry’s largest dataset of operating solar assets (>10,000 systems) and creating the first machine-learning model based on these observed results to quantify and identify features that drive degradation. There are two strategic goals for this award: reduce the cost of capital (enable solar to attract more capital) and improve the reliability of solar itself. These dual goals are achieved by leveraging an industry dataset to observe system degradation on a large scale, deploying advanced data analysis and machine learning methods to quantify and predict system reliability, and engaging with industry stakeholders to help them accurately price degradation in financial models.

14 SOLAR ENERGY↗
DOE OSTI2023

Domain Adaptation for Measurements of Strong Gravitational Lenses

Upcoming surveys are predicted to discover galaxy-scale strong lenses on the order of $10^5$, making deep learning methods necessary in lensing data analysis. Currently, there is insufficient real lensing data to train deep learning algorithms, but the alternative of training only on simulated data results in poor performance on real data. Domain Adaptation may be able to bridge the gap between simulated and real datasets. We utilize domain adaptation for the estimation of Einstein radius ($\Theta_E$) in simulated galaxy-scale gravitational lensing images with different levels of observational realism. We evaluate two domain adaptation techniques - Domain Adversarial Neural Networks (DANN) and Maximum Mean Discrepancy (MMD). We train on a source domain of simulated lenses and apply it to a target domain of lenses simulated to emulate noise conditions in the Dark Energy Survey (DES). We show that both domain adaptation techniques can significantly improve the model performance on the more complex target domain dataset. This work is the first application of domain adaptation for a regression task in strong lensing imaging analysis. Our results show the potential of using domain adaptation to perform analysis of future survey data with a deep neural network trained on simulated data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Domain Adaptation for Measurements of Strong Gravitational Lenses

Upcoming surveys are predicted to discover galaxy-scale strong lenses on the magnitude of 105, making deep learning methods necessary in lensing data analysis. Currently, there is insufficient real lensing data to train deep learning algorithms, but training only on simulated data results in poor performance on real data. Domain adaptation can bridge the gap between simulated and real datasets. We adopt domain adaptation on the estimation of Einstein radius in simulated galaxy-scale gravitational lensing images. We evaluate two domain adaptation techniques - domain adversarial neural networks (DANN) and maximum mean discrepancy (MMD). We train on a source domain of simulated lenses and apply it to a target domain with emulation of DES survey conditions. We show that both domain adaptation techniques can significantly improve the model performance on the more complex target domain datasets. Our results show the potential of using domain adaptation to perform analysis on future survey data with a deep neural network trained on simulated data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

A High-Quality Genome-Scale Model for Rhodococcus opacus Metabolism

Rhodococcus opacus is a bacterium that has a high tolerance to aromatic compounds and can produce significant amounts of triacylglycerol (TAG). Here, we present iGR1773, the first genome-scale model (GSM) of R. opacus PD630 metabolism based on its genomic sequence and associated data. The model includes 1773 genes, 3025 reactions, and 1956 metabolites, was developed in a reproducible manner using CarveMe, and was evaluated through Metabolic Model tests (MEMOTE). We combine the model with two Constraint-Based Reconstruction and Analysis (COBRA) methods that use transcriptomics data to predict growth rates and fluxes: E-Flux2 and SPOT (Simplified Pearson Correlation with Transcriptomic data). Growth rates are best predicted by E-Flux2. Flux profiles are more accurately predicted by E-Flux2 than flux balance analysis (FBA) and parsimonious FBA (pFBA), when compared to 44 central carbon fluxes measured by 13C-Metabolic Flux Analysis (13C-MFA). Under glucose-fed conditions, E-Flux2 presents an R2 value of 0.54, while predictions based on pFBA had an inferior R2 of 0.28. We attribute this improved performance to the extra activity information provided by the transcriptomics data. For phenol-fed metabolism, in which the substrate first enters the TCA cycle, E-Flux2’s flux predictions display a high R2 of 0.96 while pFBA showed an R2 of 0.93. We also show that glucose metabolism and phenol metabolism function with similar relative ATP maintenance costs. These findings demonstrate that iGR1773 can help the metabolic engineering community predict aromatic substrate utilization patterns and perform computational strain design.

Roell, Garrett W.↗
NASA NTRS1997

Bayesian Blocks: A New Method to Analyze Photon Counting Data

A Bayesian analysis of photon-counting data leads to a new time-domain algorithm for detecting localized structures (bursts), revealing pulse shapes, and generally characterizing intensity variations. The raw counting data -- time-tag events (TTE), time-to-spill (TTS) data, or binned counts -- is converted to a maximum likelihood segmentation of the observation into time intervals during which the photon arrival rate is perceptibly constant -- i.e. has a fixed intensity without statistically significant variations. The resulting structures, Bayesian Blocks, can be thought of as bins with arbitrary spacing determined by the data. The method itself sets no lower limit to the time scale on which variability can be detected. We have applied the method to RXTE data on Cyg X-1, yielding information on this source's short-time-scale variability.

Scargle, Jeffrey D.↗
DOE OSTI2022

Dynamics retrieval from stochastically weighted incomplete data by low-pass spectral analysis

Time-resolved serial femtosecond crystallography (TR-SFX) provides access to protein dynamics on sub-picosecond timescales, and with atomic resolution. Due to the nature of the experiment, these datasets are often highly incomplete and the measured diffracted intensities are affected by partiality. To tackle these issues, one established procedure is that of splitting the data into time bins, and averaging the multiple measurements of equivalent reflections within each bin. This binning and averaging often involve a loss of information. Here, we propose an alternative approach, which we call low-pass spectral analysis (LPSA). In this method, the data are projected onto the subspace defined by a set of trigonometric functions, with frequencies up to a certain cutoff. This approach attenuates undesirable high-frequency features and facilitates retrieving the underlying dynamics. A time-lagged embedding step can be included prior to subspace projection to improve the stability of the results with respect to the parameters involved. Subsequent modal decomposition allows to produce a low-rank description of the system's evolution. Using a synthetic time-evolving model with incomplete and partial observations, we analyze the LPSA results in terms of quality of the retrieved signal, as a function of the parameters involved. We compare the performance of LPSA to that of a range of other sophisticated data analysis techniques. We show that LPSA allows to achieve excellent dynamics reconstruction at modest computational cost. Finally, we demonstrate the superiority of dynamics retrieval by LPSA compared to time binning and merging, which is, to date, the most commonly used method to extract dynamical information from TR-SFX data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Determining biomolecular structures near room temperature using X-ray crystallography: concepts, methods and future optimization

For roughly two decades, cryocrystallography has been the overwhelmingly dominant method for determining high-resolution biomolecular structures. Competition from single-particle cryo-electron microscopy and micro-electron diffraction, increased interest in functionally relevant information that may be missing or corrupted in structures determined at cryogenic temperature, and interest in time-resolved studies of the biomolecular response to chemical and optical stimuli have driven renewed interest in data collection at room temperature and, more generally, at temperatures from the protein–solvent glass transition near 200 K to ∼350 K. Fischer has recently reviewed practical methods for room-temperature data collection and analysis [Fischer (2021), Q. Rev. Biophys. 54 , e1]. Here, the key advantages and physical principles of, and methods for, crystallographic data collection at noncryogenic temperatures and some factors relevant to interpreting the resulting data are discussed. For room-temperature data collection to realize its potential within the structural biology toolkit, streamlined and standardized methods for delivering crystals prepared in the home laboratory to the synchrotron and for automated handling and data collection, similar to those for cryocrystallography, should be implemented.

59 BASIC BIOLOGICAL SCIENCES↗