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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 1,387 records · Page 77

A simple second-order digital phase-locked loop.

A simple second-order digital phase-locked loop has been designed for the Viking Orbiter 1975 command system. Excluding analog-to-digital conversion, implementation of the loop requires only an adder/subtractor, two registers, and a correctable counter with control logic. The loop considers only the polarity of phase error and corrects system clocks according to a filtered sequence of this polarity. The loop is insensitive to input gain variation, and therefore offers the advantage of stable performance over long life. Predictable performance is guaranteed by extreme reliability of acquisition, yet in the steady state the loop produces only a slight degradation with respect to analog loop performance.

Tegnelia, C. R.↗

Propulsion system tests on a full scale Centaur vehicle to investigate 3-burn mission capability of the D-lT configuration

Propulsion system tests were conducted on a full scale Centaur vehicle to investigate system capability of the proposed D-lT configuration for a three-burn mission. This particular mission profile requires that the engines be capable of restarting and firing for a final maneuver after a 5-1/2-hour coast to synchronous orbit. The thermal conditioning requirements of the engine and propellant feed system components for engine start under these conditions were investigated. Performance data were also obtained on the D-lT type computer controlled propellant tank pressurization system. The test results demonstrated that the RL-10 engines on the Centaur vehicle could be started and run reliably after being thermally conditioned to predicted engine start conditions for a one, two and three burn mission. Investigation of the thermal margins also indicated that engine starts could be accomplished at the maximum predicted component temperature conditions with prestart durations less than planned for flight.

Groesbeck, W. A.↗

NASA transmission research and its probable effects on helicopter transmission design

Transmissions studied for application to helicopters in addition to the more conventional geared transmissions include hybrid (traction/gear), bearingless planetary, and split torque transmissions. Research is being performed to establish the validity of analysis and computer codes developed to predict the performance, efficiency, life, and reliability of these transmissions. Results of this research should provide the transmission designer with analytical tools to design for minimum weight and noise with maximum life and efficiency. In addition, the advantages and limitations of drive systems as well as the more conventional systems will be defined.

Zaretsky, E. V.↗

NASA transmission research and its probable effects on helicopter transmission design

Transmissions studied for application to helicopters in addition to the more conventional geared transmissions include hybrid (traction/gear), bearingless planetary, and split torque transmissions. Research is being performed to establish the validity of analysis and computer codes developed to predict the performance, efficiency, life, and reliability of these transmissions. Results of this research should provide the transmission designer with analytical tools to design for minimum weight and noise with maximum life and efficiency. In addition, the advantages and limitations of drive systems as well as the more conventional systems will be defined.

Zaretsky, E. V.↗

Photon noise and constant-volume operators

In a previous paper, a class of constant volume (CV) operators designed to maximize spatial resolution in the presence of photon noise was introduced. In this paper, the statistical properties are derived of the output images created by CV operators applied to photon-noisy versions of input images consisting of edges, spots, and gratings. The results are used to calculate the input image parameters that would permit any test image to be discriminated from a uniform field with a given level of reliability and consequently to compare the predictions of a CV operator model with psychophysical data. These results also allow the potential usefulness of CV operators in artificial image processing applications to be assessed.

Yellott, John I., Jr.↗

Subsonic flight test evaluation of a propulsion system parameter estimation process for the F100 engine

Integrated engine-airframe optimal control technology may significantly improve aircraft performance. This technology requires a reliable and accurate parameter estimator to predict unmeasured variables. To develop this technology base, NASA Dryden Flight Research Facility (Edwards, CA), McDonnell Aircraft Company (St. Louis, MO), and Pratt & Whitney (West Palm Beach, FL) have developed and flight-tested an adaptive performance seeking control system which optimizes the quasi-steady-state performance of the F-15 propulsion system. This paper presents flight and ground test evaluations of the propulsion system parameter estimation process used by the performance seeking control system. The estimator consists of a compact propulsion system model and an extended Kalman filter. The extended Laman filter estimates five engine component deviation parameters from measured inputs. The compact model uses measurements and Kalman-filter estimates as inputs to predict unmeasured propulsion parameters such as net propulsive force and fan stall margin. The ability to track trends and estimate absolute values of propulsion system parameters was demonstrated. For example, thrust stand results show a good correlation, especially in trends, between the performance seeking control estimated and measured thrust.

Orme, John S.↗

A walking prescription for statically-stable walkers based on walker/terrain interaction

The walker/terrain interaction phenomena for the control of a statically stable walking machine are described. The algorithms, measures, and knowledge of walker/terrain interaction phenomena are then combined to form a prescription for how to walk on general terrain. This prescription consists of two parts: nominal control and reactive control. The function of nominal control is the evaluation and execution of planned motions, based on predicted foot force redistributions, to achieve reliable locomotion. The function of reactive control is the monitoring of walker/terrain interaction in real-time to detect anomalous conditions and then respond with the appropriate reflexive actions. Simulations and experiments have been used to test and verify various aspects of the walking prescription.

Nagy, Peter V.↗

Static stability of a three-dimensional space truss

In order to deploy large flexible space structures it is necessary to develop support systems that are strong and lightweight. The most recent example of this aerospace design need is vividly evident in the space station solar array assembly. In order to accommodate both weight limitations and strength performance criteria, ABLE Engineering has developed the Folding Articulating Square Truss (FASTMast) support structure. The FASTMast is a space truss/mechanism hybrid that can provide system support while adhering to stringent packaging demands. However, due to its slender nature and anticipated loading, stability characterization is a critical part of the design process. Furthermore, the dire consequences surely to result from a catastrophic instability quickly provide the motivation for careful examination of this problem. The fundamental components of the space station solar array system are the (1) solar array blanket system, (2) FASTMast support structure, and (3) mast canister assembly. The FASTMast once fully deployed from the canister will provide support to the solar array blankets. A unique feature of this structure is that the system responds linearly within a certain range of operating loads and nonlinearly when that range is exceeded. The source of nonlinear behavior in this case is due to a changing stiffness state resulting from an inability of diagonal members to resist applied loads. The principal objective of this study was to establish the failure modes involving instability of the FASTMast structure. Also of great interest during this effort was to establish a reliable analytical approach capable of effectively predicting critical values at which the mast becomes unstable. Due to the dual nature of structural response inherent to this problem, both linear and nonlinear analyses are required to characterize the mast in terms of stability. The approach employed herein is one that can be considered systematic in nature. The analysis begins with one and two-dimensional failure models of the system and its important components. From knowledge gained through preliminary analyses a foundation is developed for three-dimensional analyses of the FASTMast structure. The three-dimensional finite element (FE) analysis presented here involves a FASTMast system one-tenth the size of the actual flight unit. Although this study does not yield failure analysis results that apply directly to the flight article, it does establish a method by which the full-scale mast can be evaluated.

Shaker, John F.↗

Simulation of MEMS for the Next Generation Space Telescope

The NASA Goddard Space Flight Center (GSFC) is developing optical micro-electromechanical system (MEMS) components for potential application in Next Generation Space Telescope (NGST) science instruments. In this work, we present an overview of the electro-mechanical simulation of three MEMS components for NGST, which include a reflective micro-mirror array and transmissive microshutter array for aperture control for a near infrared (NIR) multi-object spectrometer and a large aperture MEMS Fabry-Perot tunable filter for a NIR wide field camera. In all cases the device must operate at cryogenic temperatures with low power consumption and low, complementary metal oxide semiconductor (CMOS) compatible, voltages. The goal of our simulation efforts is to adequately predict both the performance and the reliability of the devices during ground handling, launch, and operation to prevent failures late in the development process and during flight. This goal requires detailed modeling and validation of complex electro-thermal-mechanical interactions and very large non-linear deformations, often involving surface contact. Various parameters such as spatial dimensions and device response are often difficult to measure reliably at these small scales. In addition, these devices are fabricated from a wide variety of materials including surface micro-machined aluminum, reactive ion etched (RIE) silicon nitride, and deep reactive ion etched (DRIE) bulk single crystal silicon. The above broad set of conditions combine to be a formidable challenge for space flight qualification analysis. These simulations represent NASA/GSFC's first attempts at implementing a comprehensive strategy to address complex MEMS structures.

Mott, Brent↗

Electrical Resistance as a NDE Technique to Monitor Processing and Damage Accumulation in SiC/SiC Composites

Ceramic matrix composites are suitable for high temperature structural applications such as turbine airfoils and hypersonic thermal protection systems. The employment of these materials in such applications is limited by the ability to process components reliable and to accurately monitor and predict damage evolution that leads to failure under stressed-oxidation conditions. Current nondestructive methods such as ultrasound, x-ray, and thermal imaging are limited in their ability to quantify small scale, transverse, in-plane, matrix cracks developed over long-time creep and fatigue conditions. Electrical resistance of SiC/SiC composites is one technique that shows special promise towards this end. Since both the matrix and the fibers are conductive, changes in matrix or fiber properties should relate to changes in electrical conductivity along the length of a specimen or part. Initial efforts to quantify the electrical resistance of different fiber and different matrix SiC/SiC composites will be presented. Also, the effect of matrix cracking on electrical resistivity for several composite systems will be presented. The implications towards electrical resistance as a technique applied to composite processing, damage detection, and life-modeling will be discussed.

Smith, Craig↗

Electrical Resistance Technique to Monitor SiC Composite Detection

Ceramic matrix composites are suitable for high temperature structural applications such as turbine airfoils and hypersonic thermal protection systems. The employment of these materials in such applications is limited by the ability to process components reliable and to accurately monitor and predict damage evolution that leads to failure under stressed-oxidation conditions. Current nondestructive methods such as ultrasound, x-ray, and thermal imaging are limited in their ability to quantify small scale, transverse, in-plane, matrix cracks developed over long-time creep and fatigue conditions. Electrical resistance of SiC/SiC composites is one technique that shows special promise towards this end. Since both the matrix and the fibers are conductive, changes in matrix or fiber properties should relate to changes in electrical conductivity along the length of a specimen or part. The effect of matrix cracking on electrical resistivity for several composite systems will be presented and some initial measurements performed at elevated temperatures under stress-rupture conditions. The implications towards electrical resistance as a technique applied to composite processing, damage detection (health monitoring), and life-modeling will be discussed.

Smith, Craig↗

Using Air Temperature to Quantitatively Predict the MODIS Fractional Snow Cover Retrieval Errors over the Continental US (CONUS)

In the middle to high latitude and alpine regions, the seasonal snow pack can dominate the surface energy and water budgets due to its high albedo, low thermal conductivity, high emissivity, considerable spatial and temporal variability, and ability to store and then later release a winters cumulative snowfall (Cohen, 1994; Hall, 1998). With this in mind, the snow drought across the U.S. has raised questions about impacts on water supply, ski resorts and agriculture. Knowledge of various snow pack properties is crucial for short-term weather forecasts, climate change prediction, and hydrologic forecasting for producing reliable daily to seasonal forecasts. One potential source of this information is the multi-institution North American Land Data Assimilation System (NLDAS) project (Mitchell et al., 2004). Real-time NLDAS products are used for drought monitoring to support the National Integrated Drought Information System (NIDIS) and as initial conditions for a future NCEP drought forecast system. Additionally, efforts are currently underway to assimilate remotely-sensed estimates of land-surface states such as snowpack information into NLDAS. It is believed that this assimilation will not only produce improved snowpack states that better represent snow evolving conditions, but will directly improve the monitoring of drought.

MODIS↗

Individual Data Sparsity in Smart Thermostat Big Data: Impacts on Modeling Thermostat Use Behavior Dynamics

This study explores the impacts of the sparsity of individual thermostat interaction data on modeling thermostat use behavior dynamics using a dataset of over 100,000 smart thermostats. In developing a data-driven model of Thermal Frustration Theory (TFT), we investigate the challenges and trade-offs in clustering occupant data to enhance predictive accuracy. Our findings reveal that a single, aggregated model fails to capture the diversity of occupant behaviors, resulting in extremely poor prediction performance. Conversely, excessive clustering exacerbates data sparsity, undermining model reliability. By identifying an optimal clustering strategy, we achieve a balance that significantly improves the prediction of manual setpoint changes during demand response (DR) events, enhancing energy management and occupant comfort

Fannon, David↗

Single Primary Heat Extraction and Removal Emulator (SPHERE) Long Duration Testing

For the development of heat-pipe cooled microreactors, it is crucial to thoroughly understand the characteristics and functioning of heat pipes across a wide spectrum of operating conditions. Passive heat removal and its long-term performance stability are critical factors in this context. Enhanced experimental data is vital for evaluating the operational lifespan of alkali metal heat pipes. Idaho National Laboratory (INL) has successfully conducted an extended duration test on a high-performance sodium-filled heat pipe, closely monitoring the axial temperature profile, power supplied by the heaters, and heat removed by a gas-gap calorimeter. The results from this testing provide valuable data that are instrumental in supporting heat pipe validation efforts. Specifically, this data aids in the development and validation of Sockeye, the Multiphysics Object-Oriented Simulation Environment (MOOSE) tool under the US-DOE NEAMS program designed for heat pipe modeling. By comparing experimental results with Sockeye’s predictions, the tool's accuracy and reliability can be assessed and improved, thereby enhancing its capability to simulate heat pipe operations under various conditions.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Lifetimes and Reliabilities of Bevel-Gear Drive Trains

Statistical methods used to predict system lifetimes from component lifetimes. Report shows how to use information to determine system life of drive train, using methods of probability and statistics. Presents life and reliability model for bevel-gear drive trains. Bevel-gear and support-bearing lives analyzed for each gear and bearing in drive train, with results statistically combined to produce system life for entire drive train. Numerical example included.

Lewicki, D.↗

Predicting bulge to total luminosity ratio of galaxies using deep learning

ABSTRACT We present a deep learning model to predict the r-band bulge-to-total luminosity ratio (B/T) of nearby galaxies using their multiband JPEG images alone. Our Convolutional Neural Network (CNN) based regression model is trained on a large sample of galaxies with reliable decomposition into the bulge and disc components. The existing approaches to estimate the B/T ratio use galaxy light-profile modelling to find the best fit. This method is computationally expensive, prohibitively so for large samples of galaxies, and requires a significant amount of human intervention. Machine learning models have the potential to overcome these shortcomings. In our CNN model, for a test set of 20 000 galaxies, 85.7 per cent of the predicted B/T values have absolute error (AE) less than 0.1. We see further improvement to 87.5 per cent if, while testing, we only consider brighter galaxies (with r-band apparent magnitude <17) with no bright neighbours. Our model estimates the B/T ratio for the 20 000 test galaxies in less than a minute. This is a significant improvement in inference time from the conventional fitting pipelines, which manage around 2–3 estimates per minute. Thus, the proposed machine learning approach could potentially save a tremendous amount of time, effort, and computational resources while predicting B/T reliably, particularly in the era of next-generation sky surveys such as the Legacy Survey of Space and Time (LSST) and the Euclid sky survey which will produce extremely large samples of galaxies.

Grover, Harsh (ORCID:0000000321338142)↗

Residual Stress Modeling and Advanced Diffraction Measurements of 347H Steel Weldments

The 347H stainless steel is a primary high-temperature material for many energy and power generation industries. Stress relief cracking (SRC) has been a particular concern in welding of this material. The residual stress induced by welding and its evolution during post-welding heat treatment (PWHT) and subsequent operating and service conditions is one of the primary factors contributing to SRC. The lifetime of welded structure components is also controlled by the precipitation kinetics that accompanies PWHT, stress relaxation process, and long-term aging and complex synergistic factors. Various theories have been proposed in the past to explain SRC. However, a widely accepted approach to predicting the entire damage evolution and the resulting performance reduction is still lacking. This study is to demonstrate a reliable solution for two critical issues that affect the predictions. First, the residual stress distribution obtained from both simulation and neutron diffraction is compared, which increases the accuracy of mechanical analysis simulation model and therefore builds a solid basis for the lifetime prediction model. Second, the generation, evolution, and annihilation of precipitates are monitored by the synchrotron diffraction experiment. Preliminary results demonstrate the critical importance of precipitation kinetics on the residual stress distribution/redistribution during heat treatments.

Yang, Yi↗

A Photometric Machine-Learning Method to Infer Stellar Metallicity

Following its formation, a star's metal content is one of the few factors that can significantly alter its evolution. Measurements of stellar metallicity ([Fe/H]) typically require a spectrum, but spectroscopic surveys are limited to a few x 10(exp 6) targets; photometric surveys, on the other hand, have detected > 10(exp 9) stars. I present a new machine-learning method to predict [Fe/H] from photometric colors measured by the Sloan Digital Sky Survey (SDSS). The training set consists of approx. 120,000 stars with SDSS photometry and reliable [Fe/H] measurements from the SEGUE Stellar Parameters Pipeline (SSPP). For bright stars (g' < or = 18 mag), with 4500 K < or = Teff < or = 7000 K, corresponding to those with the most reliable SSPP estimates, I find that the model predicts [Fe/H] values with a root-mean-squared-error (RMSE) of approx.0.27 dex. The RMSE from this machine-learning method is similar to the scatter in [Fe/H] measurements from low-resolution spectra..

machine learning↗