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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Electromagnetics and Fluid Dynamics

Previous efforts focused on developing tools for design of low observables were sustained. The final product was the maturation of a high-order accurate finite-volume based code to solve Maxwell's equations. One of the primary achievements was the development and implementation of efficient filtering techniques which enhance the robustness of high-order and optimized schemes without significant adverse impact on accuracy. This has eliminated the stability barrier which restrains the common use of high-order schemes for conservative wave propagation phenomena on curvilinear meshes. A study was performed of crossing shock interactions under conditions of increasing interaction strength and asymmetry. In the first category, the observed computed topological bifurcations were correlated with the formation of various lines of coalescence and divergence evident in experimental and computed surf-ace oil maps. ne flow structure arising from asymmetric interactions was investigated with particular emphasis on: 1) vorticity dynamics, 2) shock-structure and 3) sidewall vortex loading. Several efforts of the prior year were successfully published in archival journals. The high-order algorithms developed for CEM have been implemented into the FDL3DI CFD code are presently undergoing extensive testing. Preliminary results are highly encouraging.

Gaitonde, Datta↗
NASA NTRS2004

Photometric Detection of Extra-Solar Planets

This NASA Origins Program grant supported the TEMPEST Texas McDonald Photometric Extrasolar Search for Transits) program at McDonald Observatory, which searches for transits of extrasolar planets across the disks of their parent stars. The basic approach is to use a wide-field ground-based telescope (in our case the McDonald Observatory 0.76m telescope and it s Prime Focus Corrector) to search for transits of short period (1-15 day orbits) of close-in hot-Jupiter planets in orbit around a large sample of field stars. The next task is to search these data streams for possible transit events. We collected our first set of test data for this program using the 0.76 m PFC in the summer of 1998. From those data, we developed the optimal observing procedures, including tailoring the stellar density, exposure times, and filters to best-suit the instrument and project. In the summer of 1999, we obtained the first partial season of data on a dedicated field in the constellation Cygnus. These data were used to develop and refine the reduction and analysis procedures to produce high-precision photometry and search for transits in the resulting light curves. The TeMPEST project subsequently obtained three full seasons of data on six different fields using the McDonald Observatory 0.76m PFC.

Hatzes, Artie P.↗
NASA NTRS2010

Feature Extraction and Selection Strategies for Automated Target Recognition

Several feature extraction and selection methods for an existing automatic target recognition (ATR) system using JPLs Grayscale Optical Correlator (GOC) and Optimal Trade-Off Maximum Average Correlation Height (OT-MACH) filter were tested using MATLAB. The ATR system is composed of three stages: a cursory region of-interest (ROI) search using the GOC and OT-MACH filter, a feature extraction and selection stage, and a final classification stage. Feature extraction and selection concerns transforming potential target data into more useful forms as well as selecting important subsets of that data which may aide in detection and classification. The strategies tested were built around two popular extraction methods: Principal Component Analysis (PCA) and Independent Component Analysis (ICA). Performance was measured based on the classification accuracy and free-response receiver operating characteristic (FROC) output of a support vector machine(SVM) and a neural net (NN) classifier.

computer vision↗
NASA NTRS1999

Frequency-Weighting Filter Selection, for H2 Control of Microgravity Isolation Systems: A Consideration of the "Implicit Frequency Weighting" Problem

Many space-science experiments need an active isolation system to provide them with the requisite microgravity environment. The isolation systems planned for use with the International Space Station (ISS) have been appropriately modeled using relative position, relative velocity, and acceleration states. In theory, frequency-weighting design filters can be applied to these state-space models, in order to develop optimal H2 or mixed-norm controllers with desired stability and performance characteristics. In practice, however, since there is a kinematic relationship among the various states, any frequency weighting applied to one state will implicitly weight other states. These implicit frequency-weighting effects must be considered, for intelligent frequency-weighting filter assignment. This paper suggests a rational approach to the assignment of frequency-weighting design filters, in the presence of the kinematic coupling among states that exists in the microgravity vibration isolation problem.

Hampton, Roy David↗
NASA NTRS2000

Frequency-Weighting Filter Selection for H2 Control of Microgravity Isolation Systems: A Consideration of the "Implicit Frequency Weighting" Problem

Many space-science experiments need an active isolation system to provide them with the requisite microgravity environment. The isolation system planned for use with the International Space Station (ISS) have been appropriately modeled using relative position, relative velocity, and acceleration states. In theory, frequency-weighting design filters can be applied to them state-space models, In order to develop optimal H2 or mixed-norm controllers with desired stability and performance characteristics. In practice. however, since there Is a kinematic relationship among the various states. any frequency weighting applied to one state will implicitly weight other states. These implicit frequency-weighting effects must be considered, for intelligent frequency-weighting filter assignment. This paper suggests a rational approach to the assignment of frequency-weighting design filters, in the presence of the kinematic coupling among states that exists in the microgravity vibration isolation problem.

Hampton, R. David↗
DOE OSTI2023

Rapid discovery of high hardness multi-principal-element alloys using a generative adversarial network model

Multi-principal element alloys (MPEAs) continue to gain research prominence due to their promising high-temperature microstructural and mechanical properties. Recently, machine learning (ML) and materials informatics have been used extensively for screening MPEAs, however, most of these efforts were focused on constructing classification and regression models for predicting phase stability and mechanical properties of known compositions. These approaches may accelerate the screening process but optimizing new compositions with desirable properties within a practical time frame from an infinitely large design space of MPEA systems remains a grand challenge. To tackle this composition optimization challenge, a generative adversarial network coupled with a neural-network ML model was utilized to design MPEAs by filtering compositions that have high hardness. Even in a high-dimensional space with 18 elements as descriptors, the ML model was able to generate optimized compositions from which one composition was found to have 10% higher hardness (941 HV) than the maximum in the training data (857 HV). Density-functional theory was used to provide thermodynamic and electronic insights to higher hardness of the new MPEA found. The present work can optimize compositions from a wide design space of 18 elements (including W, Ta and Nb) that presents an opportunity to synthesize new compositions for applications ranging from corrosion-resistant alloys to nuclear materials. Here the findings suggest that generative ML can greatly accelerate materials discovery by identifying novel compositions, which can serve as a data-informed tool to guide experiments.

36 MATERIALS SCIENCE↗
NASA NTRS2011

Packing Optimization of Sorbent Bed Containing Dissimilar and Irregular Shaped Media

The Fire Cartridge is a packed bed air filter with two different and separate layers of media designed to provide respiratory protection from combustion products after a fire event on the International Space Station (ISS). The first layer of media is a carbon monoxide catalyst and the second layer of media is universal carbon. During development of Fire Cartridge prototypes, the two media beds were noticed to have shifted inside the cartridge. The movement of media within the cartridge can cause mixing of the bed layers, air voids, and channeling, which could cause preferential air flow and allow contaminants to pass through without removal. An optimally packed bed mitigates these risks and ensures effective removal of contaminants from the air. In order to optimally pack each layer, vertical, horizontal, and orbital agitations were investigated and a packed bulk density was calculated for each method. Packed bulk density must be calculated for each media type to accommodate variations in particle size, shape, and density. Additionally, the optimal vibration parameters must be re-evaluated for each batch of media due to variations in particle size distribution between batches. For this application it was determined that orbital vibrations achieve an optimal pack density and the two media layers can be packed by the same method. Another finding was media with a larger size distribution of particles achieve an optimal bed pack easier than media with a smaller size distribution of particles.

Holland, Nathan↗
DOE OSTI2025

Structural, chemical, and electronic control in Co–SiNx granular metals for high-pass filter applications

Granular metals, consisting of nanoscale conducting and insulating regions, have been studied for more than 50 years for fundamental and applied research. Granular metals exhibit non-linear conductivity vs frequency behavior, consistent with the universal power law response, and have recently been suggested for high-pass filter applications. Here, we report that cobalt–silicon nitride (Co–SiNx) granular metals with optimized sputter conditions and post-growth annealing exhibit an exceptional 109 increase in conductivity at 1 MHz compared to the DC conductivity. The improved frequency response is correlated with structural and chemical improvements examined via scanning transmission electron microscopy and x-ray photoemission spectroscopy. While we focus on improvements for high-pass filter applications, the structural, chemical, and electronic control demonstrated here will benefit a variety of granular metal and nanoparticle applications.

Annealing↗
NASA NTRS2008

Hyperspectral Fluorescence and Reflectance Imaging Instrument

The system is a single hyperspectral imaging instrument that has the unique capability to acquire both fluorescence and reflectance high-spatial-resolution data that is inherently spatially and spectrally registered. Potential uses of this instrument include plant stress monitoring, counterfeit document detection, biomedical imaging, forensic imaging, and general materials identification. Until now, reflectance and fluorescence spectral imaging have been performed by separate instruments. Neither a reflectance spectral image nor a fluorescence spectral image alone yields as much information about a target surface as does a combination of the two modalities. Before this system was developed, to benefit from this combination, analysts needed to perform time-consuming post-processing efforts to co-register the reflective and fluorescence information. With this instrument, the inherent spatial and spectral registration of the reflectance and fluorescence images minimizes the need for this post-processing step. The main challenge for this technology is to detect the fluorescence signal in the presence of a much stronger reflectance signal. To meet this challenge, the instrument modulates artificial light sources from ultraviolet through the visible to the near-infrared part of the spectrum; in this way, both the reflective and fluorescence signals can be measured through differencing processes to optimize fluorescence and reflectance spectra as needed. The main functional components of the instrument are a hyperspectral imager, an illumination system, and an image-plane scanner. The hyperspectral imager is a one-dimensional (line) imaging spectrometer that includes a spectrally dispersive element and a two-dimensional focal plane detector array. The spectral range of the current imaging spectrometer is between 400 to 1,000 nm, and the wavelength resolution is approximately 3 nm. The illumination system consists of narrowband blue, ultraviolet, and other discrete wavelength light-emitting-diode (LED) sources and white-light LED sources designed to produce consistently spatially stable light. White LEDs provide illumination for the measurement of reflectance spectra, while narrowband blue and UV LEDs are used to excite fluorescence. Each spectral type of LED can be turned on or off depending on the specific remote-sensing process being performed. Uniformity of illumination is achieved by using an array of LEDs and/or an integrating sphere or other diffusing surface. The image plane scanner uses a fore optic with a field of view large enough to provide an entire scan line on the image plane. It builds up a two-dimensional image in pushbroom fashion as the target is scanned across the image plane either by moving the object or moving the fore optic. For fluorescence detection, spectral filtering of a narrowband light illumination source is sometimes necessary to minimize the interference of the source spectrum wings with the fluorescence signal. Spectral filtering is achieved with optical interference filters and absorption glasses. This dual spectral imaging capability will enable the optimization of reflective, fluorescence, and fused datasets as well as a cost-effective design for multispectral imaging solutions. This system has been used in plant stress detection studies and in currency analysis.

Ryan, Robert E.↗
NASA NTRS1981

Classical and modern control design of a speed-hold system for a STOL airplane

A speed-hold system for an experimental short takeoff and landing jet airplane has been designed using both classical root-locus and modern optimal control synthesis techniques. The purpose of the speed-hold system is to maintain airspeed during final approach in the presence of wind shears, gusts, engine failures, and pilot control inputs. Designs were based on using airspeed as a single measurement and two symmetrically deployed upper surface blown flaps as a single control. An optimal control law feeding back all the states and the integral of airspeed through constant gains provided superior performance in terms of speed tracking and control surface activity. However, when a constant-gain Kalman filter was inserted to estimate the states using only the measurement of airspeed, the performance of the optimal control law was reduced to the same as that of a much simpler classical proportional-path plus integral-path control law. To improve the performance of the optimal control law, additional measurements would be required.

Blight, J. D.↗
NASA NTRS1990

A proposed Kalman filter algorithm for estimation of unmeasured output variables for an F100 turbofan engine

To develop advanced control systems for optimizing aircraft engine performance, unmeasurable output variables must be estimated. The estimation has to be done in an uncertain environment and be adaptable to varying degrees of modeling errors and other variations in engine behavior over its operational life cycle. This paper presents an approach to estimate unmeasured output variables by explicitly modeling the effects of off-nominal engine behavior as biases on the measurable output variables. A state variable model accommodating off-nominal behavior is developed for the engine, and Kalman filter concepts are used to estimate the required variables. Results are presented from nonlinear engine simulation studies as well as the application of the estimation algorithm on actual flight data. The formulation presented has a wide range of application since it is not restricted or tailored to the particular application described in the paper.

Alag, Gurbux S.↗
NASA NTRS1990

A proposed Kalman filter algorithm for estimation of unmeasured output variables for an F100 turbofan engine

To develop advanced control systems for optimizing aircraft engine performance, unmeasurable output variables must be estimated. The estimation has to be done in an uncertain environment and be adaptable to varying degrees of modeling errors and other variations in engine behavior over its operational life cycle. This paper represented an approach to estimate unmeasured output variables by explicitly modeling the effects of off-nominal engine behavior as biases on the measurable output variables. A state variable model accommodating off-nominal behavior is developed for the engine, and Kalman filter concepts are used to estimate the required variables. Results are presented from nonlinear engine simulation studies as well as the application of the estimation algorithm on actual flight data. The formulation presented has a wide range of application since it is not restricted or tailored to the particular application described.

Alag, Gurbux S.↗
NASA NTRS2011

Reduced Kalman Filters for Clock Ensembles

This paper summarizes the author's work ontimescales based on Kalman filters that act upon the clock comparisons. The natural Kalman timescale algorithm tends to optimize long-term timescale stability at the expense of short-term stability. By subjecting each post-measurement error covariance matrix to a non-transparent reduction operation, one obtains corrected clocks with improved short-term stability and little sacrifice of long-term stability.

Kalman filter↗
NASA NTRS2003

Advanced Signal Processing for Integrated LES-RANS Simulations: Anti-aliasing Filters

Currently, a wide variety of flow phenomena are addressed with numerical simulations. Many flow solvers are optimized to simulate a limited spectrum of flow effects effectively, such as single parts of a flow system, but are either inadequate or too expensive to be applied to a very complex problem. As an example, the flow through a gas turbine can be considered. In the compressor and the turbine section, the flow solver has to be able to handle the moving blades, model the wall turbulence, and predict the pressure and density distribution properly. This can be done by a flow solver based on the Reynolds-Averaged Navier-Stokes (RANS) approach. On the other hand, the flow in the combustion chamber is governed by large scale turbulence, chemical reactions, and the presence of fuel spray. Experience shows that these phenomena require an unsteady approach. Hence, for the combustor, the use of a Large Eddy Simulation (LES) flow solver is desirable. While many design problems of a single flow passage can be addressed by separate computations, only the simultaneous computation of all parts can guarantee the proper prediction of multi-component phenomena, such as compressor/combustor instability and combustor/turbine hot-streak migration. Therefore, a promising strategy to perform full aero-thermal simulations of gas-turbine engines is the use of a RANS flow solver for the compressor sections, an LES flow solver for the combustor, and again a RANS flow solver for the turbine section.

Schlueter, J. U.↗
NASA NTRS1986

Combined optimization of image-gathering optics and image-processing algorithm for edge detection

This paper investigates the relationships between the image-gathering and image-processing systems for minimum mean-squared error estimation of scene characteristics. A stochastic optimization problem is formulated in which the objective is to determine a spatial characteristic of the scene rather than a feature of the already blurred, sampled, and noisy image data. The Wiener filter for the sampled image case is obtained as a special case, where the desired characteristics is scene restoration. Optimal edge detection is investigated. It is shown that the optimal edge detector compensates for the blurring introduced by the image-gathering optics, and, notably, that it is not circularly symmetric. The lack of circular symmetry is largely due to the geometric effects of the sampling lattice used in image acquisition.

Halyo, N.↗
NASA NTRS1989

Globally optimal maneuver of distributed systems

This paper examines the globally optimal maneuver of distributed systems undergoing large overall rigid-body motion and small relative elastic motion. Using floating coordinates the rigid-body motion and the elastic motion are decoupled thereby allowing the globally optimal maneuver problem to be separated into components associated with the rigid-body and elastic motions. The maneuvers are performed using distributed maneuvering forces based on modal measurements. The modal measurements are extracted from the physical measurements using modal filters. Rest-to-rest maneuvers of a uniform beam illustrate the decentralized nature of the globally optimal solutions.

Silverberg, Larry↗
DOE OSTI2020

RIFTA: A Robust Iterative Fourier Transform-based dwell time Algorithm for ultra-precision ion beam figuring of synchrotron mirrors

With the rapid evolution of synchrotron X-ray sources, the demand for high-precision X-ray mirrors has greatly increased. Single nanometer profile error is required to keep imaging capability at the diffraction limit. Ion Beam Figuring (IBF), as a highly deterministic surfacing technique, has been used for ultra-precision finishing of mirrors. One crucial step that guides the IBF process is dwell time calculation. A valid dwell time solution should be non-negative and duplicate the shape of the desired removal map. Another important aspect is to minimize the total dwell time. In this study, we propose a Robust Iterative Fourier Transform-based dwell time Algorithm (RIFTA) that automatically fulfills these requirements. First, the thresholded inverse filtering in Fourier transform-based deconvolution is stabilized and automated by optimizing the threshold value using the Nelder-Mead simplex algorithm. Second, a novel two-level iterative scheme is proposed to guarantee the minimized total dwell time with its non-negativity at each dwell point. Third, a bicubic resampling is employed to flexibly adapt the calculated dwell time map to any IBF process intervals. The performance of RIFTA is first studied with simulation, followed by a comparison with the other state-of-the-art dwell time algorithms. We then demonstrate with an experiment that, using the dwell time calculated by the RIFTA, the total dwell time is shortened by a factor of two and the RMS in a 5 × 50 mm clear aperture was reduced from 3.4 nm to 1.1 nm after one IBF run, which proves the effectiveness and the efficiency of the proposed algorithm.

42 ENGINEERING↗
DOE OSTI2024

Analysis of Power-Maximizing Region 2 Controllers for Wind and Marine Turbines

Wind and marine energy are rapidly growing and complementary technologies that share some techniques for simplified modeling and control, particularly in below-rated flow speeds. A turbine operator has several choices of controller for maximizing power in Region 2. The simple and ubiquitous KΩ 2 control law is often effective but limited in its flexibility. Alternative controllers use reference tracking to split the control objectives into a low-bandwidth optimal tip-speed ratio tracking loop to maximize steady-state power and a higher-bandwidth proportional-integral control loop to reject inflow turbulence. Several options exist for identifying the slowly varying optimal set point during operation, based on estimating the inflow velocity or filtering the power or torque signals. This study compares the trade-offs between performance and other design priorities for a few choices of reference-tracking controller in the literature for reference wind and marine turbines. Analysis is performed in the frequency domain using the linearization of each controller, and the impact of turbulent disturbances on the closed-loop system is described. The controllers are simulated in OpenFAST to analyze their performance with higher-order nonlinear turbine dynamics.

17 WIND ENERGY↗