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At least 1,225 records · Page 68

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NASA NTRS1991

Simulation and analyses of the aeroassist flight experiment attitude update method

A method which will be used to update the alignment of the Aeroassist Flight Experiment's Inertial Measuring Unit is simulated and analyzed. This method, the Star Line Maneuver, uses measurements from the Space Shuttle Orbiter star trackers along with an extended Kalman filter to estimate a correction to the attitude quaternion maintained by an Inertial Measuring Unit in the Orbiter's payload bay. This quaternion is corrupted by on-orbit bending of the Orbiter payload bay with respect to the Orbiter navigation base, which is incorporated into the payload quaternion when it is initialized via a direct transfer of the Orbiter attitude state. The method of updating this quaternion is examined through verification of baseline cases and Monte Carlo analysis using a simplified simulation, The simulation uses nominal state dynamics and measurement models from the Kalman filter as its real world models, and is programmed on Microvax minicomputer using Matlab, and interactive matrix analysis tool. Results are presented which confirm and augment previous performance studies, thereby enhancing confidence in the Star Line Maneuver design methodology.

Carpenter, J. R.↗

DOE OSTI2025

Energy filtering–induced ultrahigh thermoelectric power factors in Ni 3 Ge

Traditional thermoelectric materials rely on low thermal conductivity to enhance their efficiency but suffer from inherently limited power factors. Innovative pathways to optimize electronic transport are thus crucial. Here, we achieve ultrahigh power factors in Ni 3 Ge-based systems through an unconventional thermoelectric materials design principle. When overlapping flat and dispersive bands are engineered to the Fermi level, charge carriers can undergo intense interband scattering, yielding an energy filtering effect similar to what has long been predicted in certain nanostructured materials. Via a multistep DFT-based screening method developed here, we find a family of L1 2 -ordered binary compounds with ultrahigh power factors up to 11 mW m −1 K −2 near room temperature, which are driven by an intrinsic phonon-mediated energy filtering mechanism. Our comprehensive experimental and theoretical study of these intriguing materials paves the way for understanding and designing high-performance scattering-tuned metallic thermoelectrics.

Science & Technology - Other Topics↗

NASA NTRS1995

Preliminary large-eddy simulations of flow around a NACA 4412 airfoil using unstructured grids

Large-eddy simulation (LES) has matured to the point where application to complex flows is desirable. The extension to higher Reynolds numbers leads to an impractical number of grid points with existing structured-grid methods. Furthermore, most real world flows are rather difficult to represent geometrically with structured grids. Unstructured-grid methods offer a release from both of these constraints. However, just as it took many years for structured-grid methods to be well understood and reliable tools for LES, unstructured-grid methods must be carefully studied before we can expect them to attain their full potential. In the past two years, important building blocks have been put into place making possible a careful study of LES on unstructured grids. The first building block was an efficient mesh generator which allowed the placement of points according to smooth variation of physical length scales. This variation of length scales is in all three directions independently, which allows a large reduction in points when compared to structured-grid methods, which can only vary length scales in one direction at a time. The second building block was the development of a dynamic model appropriate for unstructured grids. The principle obstacle was the development of an unstructured-grid filtering operator. In the past year, some of the new filters developed by Jansen have been implemented into a highly parallelized finite element code based on the Galerkin/least-squares finite element method. We have chosen the NACA 4412 airfoil at maximum lift as the first simulation for a variety of reasons. First, it is a problem of significant interest since it would be the first LES of an aircraft component. Second, this flow has been the subject of three experimental studies. The third reason for considering this flow is the variety of flow features which provide an important test of the dynamic model. Only the dynamic model can be expected to perform satisfactorily in this variety of situations: from the laminar regions where it must not modify the flow at all to the turbulent boundary layers and wake where it must represent a wide variety of subgrid-scale structures. The flow configuration we have chosen is that of Wadcock (1987) at Reynolds number based on chord Re(sub c) = u(sub infinity)c/v = 1.64 x 10(exp 6), Mach number M = 0.2, and 12 deg angle of attack.

Jansen, Kenneth↗

DOE OSTI2022

Early arrival waveform inversion using data uncertainties and matching filters with application to near-surface seismic refraction data

We develop an early arrival waveform inversion (EAWI) technique for high-resolution near-surface velocity estimation by iteratively updating the P-wave velocity model to minimize the difference between the observed and calculated seismic refraction data. Traditional EAWI uses a least-squares penalty function and an acoustic forward-modeling engine. Conventional least-squares error is sensitive to data with low signal-to-noise ratio (S/N) and iterations of EAWI stop at a local-minimum data misfit or at the preassigned maximum number of iterations. These stopping criteria can result in overfitting the data. In addition, fitting the elastic field data with an acoustic modeling engine can introduce artifacts in velocity estimation, especially in land data with significant elastic effects. To overcome these challenges, we develop a robust EAWI (REAWI) method by (1) incorporating the data uncertainties into the penalty function and (2) mitigating the elastic effects using a matching filter workflow. The data uncertainties are estimated from waveform reciprocal errors. When full-waveform reciprocity is not available, trace interpolation is applied. The proposed method prevents closely fitting data with low S/N, avoids overall overfitting by stopping the iterations when a normalized chi-square ([Formula: see text]) waveform misfit of one is achieved, and is less affected by elastic effects. Numerical examples and application to near-surface refraction data at a groundwater contamination site suggest that the final REAWI models are more accurate than the corresponding EAWI models, at the same level of misfit. This is the first known application of a matching filter workflow to real land data. The final REAWI models satisfy an appropriate misfit between the real data and predicted elastic P-wave data, making this approach in this respect equivalent to elastic waveform inversion. We also develop a method to analyze model constraint by examining the energy of the wavefield Fréchet derivative thereby avoiding the influence of the data residuals in traditional Fréchet kernels.

Geochemistry & Geophysics↗

DOE OSTI2022

A Non-perturbative Approach to Computing Seismic Normal Modes in Rotating Planets

In this work, a continuous Galerkin method based approach is presented to compute the seismic normal modes of rotating planets. Special care is taken to separate out the essential spectrum in the presence of a fluid outer core using a polynomial filtering eigensolver. The relevant elastic-gravitational system of equations, including the Coriolis force, is subjected to a mixed finite-element method, while self-gravitation is accounted for with the fast multipole method. Our discretization utilizes fully unstructured tetrahedral meshes for both solid and fluid regions. The relevant eigenvalue problem is solved by a combination of several highly parallel and computationally efficient methods. We validate our three-dimensional results in the non-rotating case using analytical results for constant elastic balls, as well as numerical results for an isotropic Earth model from standard “radial” algorithms. We also validate the computations in the rotating case, but only in the slowly-rotating regime where perturbation theory applies, because no other independent algorithms are available in the general case. The algorithm and code are used to compute the point spectra of eigenfrequencies in several Earth and Mars models studying the effects of heterogeneity on a large range of scales.

58 GEOSCIENCES↗

DOE OSTI2022

Nanoscale defect evaluation framework combining real-time transmission electron microscopy and integrated machine learning-particle filter estimation

Observation of dynamic processes by transmission electron microscopy (TEM) is an attractive technique to experimentally analyze materials’ nanoscale phenomena and understand the microstructure-properties relationships in nanoscale. Even if spatial and temporal resolutions of real-time TEM increase significantly, it is still difficult to say that the researchers quantitatively evaluate the dynamic behavior of defects. Images in TEM video are a two-dimensional projection of three-dimensional space phenomena, thus missing information must be existed that makes image’s uniquely accurate interpretation challenging. Therefore, even though they are still a clustering high-dimensional data and can be compressed to two-dimensional, conventional statistical methods for analyzing images may not be powerful enough to track nanoscale behavior by removing various artifacts associated with experiment; and automated and unbiased processing tools for such big-data are becoming mission-critical to discover knowledge about unforeseen behavior. We have developed a method to quantitative image analysis framework to resolve these problems, in which machine learning and particle filter estimation are uniquely combined. The quantitative and automated measurement of the dislocation velocity in an Fe-31Mn-3Al-3Si autunitic steel subjected to the tensile deformation was performed to validate the framework, and an intermittent motion of the dislocations was quantitatively analyzed. The framework is successfully classifying, identifying and tracking nanoscale objects; these are not able to be accurately implemented by the conventional mean-path based analysis.

36 MATERIALS SCIENCE↗

NASA NTRS1995

Spacelab Charcoal Analyses

This report describes analytical methods and results obtained from chemical analysis of 31 charcoal samples in five sets. Each set was obtained from a single scrubber used to filter ambient air on board a Spacelab mission. Analysis of the charcoal samples was conducted by thermal desorption followed by gas chromatography/mass spectrometry (GC/MS). All samples were analyzed using identical methods. The method used for these analyses was able to detect compounds independent of their polarity or volatility. In addition to the charcoal samples, analyses of three Environmental Control and Life Support System (ECLSS) water samples were conducted specifically for trimethylamine.

Slivon, L. E.↗

DOE OSTI2023

Fast Semi-automated Filtration Method for Non-targeted LC-QTOF Data of Aged Nitroplasticizer Samples

A full dataset of aged nitroplasticizer (NP) is composed of more than 2000 unique mass-to-charges (m/z) when combining the non-targeted data obtained from both positive and negative electrospray ionization modes in time-of-flight mass spectrometry. Therefore, manual processing of these data often takes days, weeks, or even months to scrutinize for mechanistic insights. To effectively extract meaningful signals that represent vital degradation intermediates in the early NP degradation mechanism, a semi-automated postprocessing workflow for data filtering, tailored to the aging experiment of NP, has been developed. The automated portion of this workflow is written in a Python code (using pandas, numpy, and matplotlib libraries), which removes more than 65% of potential false signals within seconds via four threshold-based adjustable filters: signal sensitivity, coefficient of variation, number of measurements, and retention time variability. As for the manual portion, a pattern-based inspection method is employed to reduce another 23% or more false positives, which greatly simplifies data visualization and results in less than 3% of potential candidate m/z needing in-depth data interpretation. As a positive control, known compounds are verified. Using this semi-automated data reduction method, the amount of time required is reduced to a matter of hours for data filtering in the non-targeted datasets of aged NP, which saves more time and effort for compound identification.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Long short-term memory embedded nudging schemes for nonlinear data assimilation of geophysical flows

Reduced rank nonlinear filters are increasingly utilized in data assimilation of geophysical flows, but often require a set of ensemble forward simulations to estimate forecast covariance. On the other hand, predictor-corrector type nudging approaches are still attractive due to their simplicity of implementation when more complex methods need to be avoided. However, optimal estimate of nudging gain matrix might be cumbersome. In this paper, we put forth a fully nonintrusive recurrent neural network approach based on a long short-term memory (LSTM) embedding architecture to estimate the nudging term, which plays a role not only to force the state trajectories to the observations but also acts as a stabilizer. Furthermore, our approach relies on the power of archival data and the trained model can be retrained effectively due to power of transfer learning in any neural network applications. In order to verify the feasibility of the proposed approach, we perform twin experiments using Lorenz 96 system. Our results demonstrate that the proposed LSTM nudging approach yields more accurate estimates than both extended Kalman filter (EKF) and ensemble Kalman filter (EnKF) when only sparse observations are available. With the availability of emerging AI-friendly and modular hardware technologies and heterogeneous computing platforms, we articulate that our simplistic nudging framework turns out to be computationally more efficient than either the EKF or EnKF approaches.

42 ENGINEERING↗

DOE OSTI2023

The Flux-Differencing Discontinuous Galerkin Method Applied to an Idealized Fully Compressible Nonhydrostatic Dry Atmosphere

Dynamical cores used to study the circulation of the atmosphere employ various numerical methods ranging from finite-volume, spectral element, global spectral, and hybrid methods. In this work, we explore the use of Flux-Differencing Discontinuous Galerkin (FDDG) methods to simulate a fully compressible dry atmosphere at various resolutions. We show that the method offers a judicious compromise between high-order accuracy and stability for large-eddy simulations and simulations of the atmospheric general circulation. In particular, filters, divergence damping, diffusion, hyperdiffusion, or sponge-layers are not required to ensure stability; only the numerical dissipation naturally afforded by FDDG is necessary. We apply the method to the simulation of dry convection in an atmospheric boundary layer and in a global atmospheric dynamical core in the standard benchmark of Held and Suarez

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Improving IPATS Channel-to-Channel Registration Assessment

The Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) is a primary tool for assessing INR performance of GOES-R series ABI images. IPATS assesses five INR metrics: navigation, channel-to-channel registration (CCR), frame-to-frame registration, within-frame registration, and swath-to-swath registration. It was discovered that CCR assessment results between Visible-Near-Infrared (VNIR) channels and Infrared (IR) channels exhibits an annual oscillation in the north-south (NS) direction and a diurnal oscillation in the east-west (EW) direction, with an amplitude of approximately 5 μrad and 2.5 μrad, respectively. However, differences of navigation assessment results between VNIR and IR channels do not exhibit the annual or diurnal oscillations observed in CCR results. This indicates that the observed oscillations are due to measurement errors. The characteristics of the oscillations imply that cloud shadows are a possible cause of these measurement errors. In this study, several methods are explored to minimize the impact of cloud shadows on VNIR to IR CCR assessments: a) assessment at landmark locations only; b) using navigation assessment results to filter CCR assessments; c) using the ABI clear-sky-ratio product as a cloud mask; and d) smaller CCR assessment windows. In this paper, each method and a combination of several methods are evaluated based on assessment accuracy and the number of successful assessments. The selected approach is then used to reprocess GOES-16 ABI CCR data to show reductions in the annual and diurnal measurement error oscillations.

INR↗

NASA NTRS1994

Advanced data assimilation in strongly nonlinear dynamical systems

Advanced data assimilation methods are applied to simple but highly nonlinear problems. The dynamical systems studied here are the stochastically forced double well and the Lorenz model. In both systems, linear approximation of the dynamics about the critical points near which regime transitions occur is not always sufficient to track their occurrence or nonoccurrence. Straightforward application of the extended Kalman filter yields mixed results. The ability of the extended Kalman filter to track transitions of the double-well system from one stable critical point to the other depends on the frequency and accuracy of the observations relative to the mean-square amplitude of the stochastic forcing. The ability of the filter to track the chaotic trajectories of the Lorenz model is limited to short times, as is the ability of strong-constraint variational methods. Examples are given to illustrate the difficulties involved, and qualitative explanations for these difficulties are provided. Three generalizations of the extended Kalman filter are described. The first is based on inspection of the innovation sequence, that is, the successive differences between observations and forecasts; it works very well for the double-well problem. The second, an extension to fourth-order moments, yields excellent results for the Lorenz model but will be unwieldy when applied to models with high-dimensional state spaces. A third, more practical method--based on an empirical statistical model derived from a Monte Carlo simulation--is formulated, and shown to work very well. Weak-constraint methods can be made to perform satisfactorily in the context of these simple models, but such methods do not seem to generalize easily to practical models of the atmosphere and ocean. In particular, it is shown that the equations derived in the weak variational formulation are difficult to solve conveniently for large systems.

Miller, Robert N.↗

NASA NTRS1988

Expanded envelope concepts for aircraft control-element failure detection and identification

The purpose of this effort was to develop and demonstrate concepts for expanding the envelope of failure detection and isolation (FDI) algorithms for aircraft-path failures. An algorithm which uses analytic-redundancy in the form of aerodynamic force and moment balance equations was used. Because aircraft-path FDI uses analytical models, there is a tradeoff between accuracy and the ability to detect and isolate failures. For single flight condition operation, design and analysis methods are developed to deal with this robustness problem. When the departure from the single flight condition is significant, algorithm adaptation is necessary. Adaptation requirements for the residual generation portion of the FDI algorithm are interpreted as the need for accurate, large-motion aero-models, over a broad range of velocity and altitude conditions. For the decision-making part of the algorithm, adaptation may require modifications to filtering operations, thresholds, and projection vectors that define the various hypothesis tests performed in the decision mechanism. Methods of obtaining and evaluating adequate residual generation and decision-making designs have been developed. The application of the residual generation ideas to a high-performance fighter is demonstrated by developing adaptive residuals for the AFTI-F-16 and simulating their behavior under a variety of maneuvers using the results of a NASA F-16 simulation.

Weiss, Jerold L.↗

NASA NTRS1980

The sensitivity of a very long baseline interferometer

The theoretical sensitivity of various methods of acquiring and processing interferometer data are compared. It is shown that for a fixed digital recording capacity one bit quantization of single sideband data filtered with a rectangular bandpass and sampled at the Nyquist rate yields the optimum signal to noise ratio. The losses which result from imperfect bandpass, poor image rejection, approximate methods of fringe rotation, fractional bit correction, and loss of quadrature are discussed. Also discussed is the use of the complex delay function as a maximum likelihood fringe estimator.

Rogers, A. E. E.↗

NASA NTRS1993

Rate determination from vector observations

Vector observations are a common class of attitude data provided by a wide variety of attitude sensors. Attitude determination from vector observations is a well-understood process and numerous algorithms such as the TRIAD algorithm exist. These algorithms require measurement of the line of site (LOS) vector to reference objects and knowledge of the LOS directions in some predetermined reference frame. Once attitude is determined, it is a simple matter to synthesize vehicle rate using some form of lead-lag filter, and then, use it for vehicle stabilization. Many situations arise, however, in which rate knowledge is required but knowledge of the nominal LOS directions are not available. This paper presents two methods for determining spacecraft angular rates from vector observations without a priori knowledge of the vector directions. The first approach uses an extended Kalman filter with a spacecraft dynamic model and a kinematic model representing the motion of the observed LOS vectors. The second approach uses a 'differential' TRIAD algorithm to compute the incremental direction cosine matrix, from which vehicle rate is then derived.

Weiss, Jerold L.↗

NASA NTRS1976

Interpolation of a surface from sets of discrete height data of different statistical characteristics

This paper presents and analyzes a method for the interpolation of a unique surface from two sets of independent digital height data of differing statistical characteristics. This method is based on linear prediction and thus relies on the concepts of auto- and cross-covariance functions. The linear prediction algorithm for two sets of digital height measurements is first derived and then evaluated using the method of moving averages and bilinear interpolation for comparison. It is found that the overall root mean square interpolation errors of linear prediction are similar to those from moving averages and bilinear interpolation. This accuracy performance, together with the well known potential for controlled filtering of measuring errors and good-behavior in areas of poor control, makes linear prediction a versatile and general method for interpolating a unique surface from two sets of digital height data, with applications in photogrammetric mapping, remote sensing, and other fields.

Leberl, F.↗

NASA NTRS2000

Optimization of Microelectronic Devices for Sensor Applications

The NASA/JPL goal to reduce payload in future space missions while increasing mission capability demands miniaturization of active and passive sensors, analytical instruments and communication systems among others. Currently, typical system requirements include the detection of particular spectral lines, associated data processing, and communication of the acquired data to other systems. Advances in lithography and deposition methods result in more advanced devices for space application, while the sub-micron resolution currently available opens a vast design space. Though an experimental exploration of this widening design space-searching for optimized performance by repeated fabrication efforts-is unfeasible, it does motivate the development of reliable software design tools. These tools necessitate models based on fundamental physics and mathematics of the device to accurately model effects such as diffraction and scattering in opto-electronic devices, or bandstructure and scattering in heterostructure devices. The software tools must have convenient turn-around times and interfaces that allow effective usage. The first issue is addressed by the application of high-performance computers and the second by the development of graphical user interfaces driven by properly developed data structures. These tools can then be integrated into an optimization environment, and with the available memory capacity and computational speed of high performance parallel platforms, simulation of optimized components can proceed. In this paper, specific applications of the electromagnetic modeling of infrared filtering, as well as heterostructure device design will be presented using genetic algorithm global optimization methods.

Cwik, Tom↗

NASA NTRS2004

Active Suppression of Instabilities in Engine Combustors

A method of feedback control has been proposed as a means of suppressing thermo-acoustic instabilities in a liquid- fueled combustor of a type used in an aircraft engine. The basic principle of the method is one of (1) sensing combustor pressure oscillations associated with instabilities and (2) modulating the rate of flow of fuel to the combustor with a control phase that is chosen adaptively so that the pressure oscillations caused by the modulation oppose the sensed pressure oscillations. The need for this method arises because of the planned introduction of advanced, lean-burning aircraft gas turbine engines, which promise to operate with higher efficiencies and to emit smaller quantities of nitrogen oxides, relative to those of present aircraft engines. Unfortunately, the advanced engines are more susceptible to thermoacoustic instabilities. These instabilities are hard to control because they include large dead-time phase shifts, wide-band noise characterized by amplitudes that are large relative to those of the instabilities, exponential growth of the instabilities, random net phase walks, and amplitude fluctuations. In this method (see figure), the output of a combustion-pressure sensor would be wide-band-pass filtered and then further processed to generate a control signal that would be applied to a fast-actuation valve to modulate the flow of fuel. Initially, the controller would rapidly take large phase steps in order to home in, within a fraction of a second, to a favorable phase region within which the instability would be reduced. Then the controller would restrict itself to operate within this phase region and would further restrict itself to operate within a region of stability, as long as the power in the instability signal was decreasing. In the phase-shifting scheme of this method, the phase of the control vector would be made to continuously bounce back and forth from one boundary of an effective stability region to the other. Computationally, this scheme would be implemented by the adaptive sliding phaser averaged control (ASPAC) algorithm, which requires very little detailed knowledge of the combustor dynamics. In the ASPAC algorithm, the power of the instability signal would be calculated from the wide-bandpass- filtered combustion-pressure signal and averaged over a period of time (typically of the order of a few hundredths of a second) corresponding to the controller updating cycle [not to be confused with the controller sampling cycle, which would be much shorter (typically of the order of 10(exp -4) second)].

Kopasakis, George↗