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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Cassini Orbit Trim Maneuvers at Saturn - Overview of Attitude Control Flight Operations

The Cassini spacecraft has been in orbit around Saturn since July 1, 2004. To remain on the planned trajectory which maximizes science data return, Cassini must perform orbit trim maneuvers using either its main engine or its reaction control system thrusters. Over 200 maneuvers have been executed on the spacecraft since arrival at Saturn. To improve performance and maintain spacecraft health, changes have been made in maneuver design command placement, in accelerometer scale factor, and in the pre-aim vector used to align the engine gimbal actuator prior to main engine burn ignition. These and other changes have improved maneuver performance execution errors significantly since 2004. A strategy has been developed to decide whether a main engine maneuver should be performed, or whether the maneuver can be executed using the reaction control system.

spacecraft configuration↗
NASA NTRS2020

TESS Data Release Notes:Reprocessing of Sectors 14–19, DR30 & DR33

TESS data release 30 (DR30) provides reprocessed data products of Sector 14 to 19. The updated data products were generated using version 4.0 of the science processing pipeline and conform to the final set of data anomaly flags defined over the last two years of TESS data analysis and pipeline development. Data release 33 (DR33) corresponds to a multisector search for transiting planets in the same reprocessed data. A detailed description of the changes in the data products in DR30 and DR33 is discussed in§2, and a brief list of changes is summarized here: The timestamps for 2 minute cadence and FFI data are more accurate. The differences between reprocessed data and previous data releases are less than 2.0 seconds in all cases. Photometric apertures were increased in size for targets with T mag<11. Three new Data Anomaly Flags were added to mitigate the effects of scattered light:–Cadences with strong scattered light signals or saturation effects that corrupt the calibration data are flagged and removed from analysis (bit 15, value 16384, “Bad Calibration Exclude”).–Scattered light data anomaly flags are customized for each target, and flagged automatically based on the local background level (bit 13, value 4096, ”Scattered light flag”).–Cadences with insufficient targets to derive cotrending basis vectors are flagged and the PDCSAP FLUX light curves are set to NULL at these times (bit 16, value 32768, “Insufficient Targets for Error Correction Exclude”). The planet search of the reprocessed light curves produced a different set of TCEs from the original processed data. Although there is a high degree of overlap between the original and reprocessed data (∼83% of targets produced TCEs in common), new TCEs were produced in DR30 and not every TCE from previous data releases was recovered. The same is true of the multisector search results from DR33 compared to DR28

TESS'↗
DOE OSTI2019

How Well Do We Know Neutrino-Electron Scattering? EFT Approach

We determine the effective theory of neutrino-electron and neutrino-quark scattering and provide the most precise up-to-date prediction for neutrino-electron scattering cross sections quantifying errors for the first time to be of order $0.2-0.4~\%$. Radiative corrections in the theory with electron and neutrinos only involve three effective couplings. One is the Fermi constant which is known with sub-ppm accuracy. Another one has a small error of order $0.02~\%$. The uncertainty of the third one is limited by the knowledge of hadronic contributions to charge-isospin vector-vector correlation function.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2013

Automation of the guiding center expansion

We report on the use of the recently developed Mathematica package VEST (Vector Einstein Summation Tools) to automatically derive the guiding center transformation. Our Mathematica code employs a recursive procedure to derive the transformation order-by-order. This procedure has several novel features. (1) It is designed to allow the user to easily explore the guiding center transformation's numerous non-unique forms or representations. (2) The procedure proceeds entirely in cartesian position and velocity coordinates, thereby producing manifestly gyrogauge invariant results; the commonly used perpendicular unit vector fields e{sub 1},e{sub 2} are never even introduced. (3) It is easy to apply in the derivation of higher-order contributions to the guiding center transformation without fear of human error. Our code therefore stands as a useful tool for exploring subtle issues related to the physics of toroidal momentum conservation in tokamaks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2004

Using Redundancy To Reduce Errors in Magnetometer Readings

A method of reducing errors in noisy magnetic-field measurements involves exploitation of redundancy in the readings of multiple magnetometers in a cluster. By "redundancy"is meant that the readings are not entirely independent of each other because the relationships among the magnetic-field components that one seeks to measure are governed by the fundamental laws of electromagnetism as expressed by Maxwell's equations. Assuming that the magnetometers are located outside a magnetic material, that the magnetic field is steady or quasi-steady, and that there are no electric currents flowing in or near the magnetometers, the applicable Maxwell 's equations are delta x B = 0 and delta(raised dot) B = 0, where B is the magnetic-flux-density vector. By suitable algebraic manipulation, these equations can be shown to impose three independent constraints on the values of the components of B at the various magnetometer positions. In general, the problem of reducing the errors in noisy measurements is one of finding a set of corrected values that minimize an error function. In the present method, the error function is formulated as (1) the sum of squares of the differences between the corrected and noisy measurement values plus (2) a sum of three terms, each comprising the product of a Lagrange multiplier and one of the three constraints. The partial derivatives of the error function with respect to the corrected magnetic-field component values and the Lagrange multipliers are set equal to zero, leading to a set of equations that can be put into matrix.vector form. The matrix can be inverted to solve for a vector that comprises the corrected magnetic-field component values and the Lagrange multipliers.

Kulikov, Igor↗
NASA NTRS1989

Sliding control of pointing and tracking with operator spline estimation

It is shown how a variable structure control technique could be implemented to achieve precise pointing and good tracking of a deformable structure subject to fast slewing maneuvers. The correction torque that has to be applied to the structure is based on estimates of upper bounds on the model errors. For a rapid rotation of the deformable structure, the elastic response can be modeled by oscillators driven by angular acceleration, and where stiffness and damping coefficients are also angular velocity and acceleration dependent. By transforming this slew-driven elastic dynamics into bilinear form (be regarding the vector made up of the angular velocity, squared angular velocity and angular acceleration components, which appear in the coefficients as the input to the deformation dynamics), an operator spline can be constructed, that gives a low order estimate of the induced disturbance. Moreover, a worst case error bound between the estimated deformation and the unknown exact deformation is also generated, which can be used where required in the sliding control correction.

Dwyer, Thomas A. W., III↗
NASA NTRS1995

Model-based VQ for image data archival, retrieval and distribution

An ideal image compression technique for image data archival, retrieval and distribution would be one with the asymmetrical computational requirements of Vector Quantization (VQ), but without the complications arising from VQ codebooks. Codebook generation and maintenance are stumbling blocks which have limited the use of VQ as a practical image compression algorithm. Model-based VQ (MVQ), a variant of VQ described here, has the computational properties of VQ but does not require explicit codebooks. The codebooks are internally generated using mean removed error and Human Visual System (HVS) models. The error model assumed is the Laplacian distribution with mean, lambda-computed from a sample of the input image. A Laplacian distribution with mean, lambda, is generated with uniform random number generator. These random numbers are grouped into vectors. These vectors are further conditioned to make them perceptually meaningful by filtering the DCT coefficients from each vector. The DCT coefficients are filtered by multiplying by a weight matrix that is found to be optimal for human perception. The inverse DCT is performed to produce the conditioned vectors for the codebook. The only image dependent parameter used in the generation of codebook is the mean, lambda, that is included in the coded file to repeat the codebook generation process for decoding.

Manohar, Mareboyana↗
NASA NTRS1975

Calculations for interpretation of solar vector magnetograph data

Computer techniques for data analysis of sunspot observations are presented. Photographic spectra were converted to digital form and analyzed. Methods of determining magnetic field strengths, i.e., the Zeeman effect, are discussed. Errors originating with telescope equipment and the magnetograph are treated. Flow charts of test programs and procedures of the data analysis are shown.

Dunn, A. R.↗
DOE OSTI2018

Short-Term Global Horizontal Irradiance Forecasting Based on Sky Imaging and Pattern Recognition

Accurate short-term forecasting is crucial for solar integration in the power grid. In this paper, a classification forecasting framework based on pattern recognition is developed for 1-hour-ahead global horizontal irradiance (GHI) forecasting. Three sets of models in the forecasting framework are trained by the data partitioned from the preprocessing analysis. The first two sets of models forecast GHI for the first four daylight hours of each day. Then the GHI values in the remaining hours are forecasted by an optimal machine learning model determined based on a weather pattern classification model in the third model set. The weather pattern is determined by a support vector machine (SVM) classifier. The developed framework is validated by the GHI and sky imaging data from the National Renewable Energy Laboratory (NREL). Results show that the developed short-term forecasting framework outperforms the persistence benchmark by 16% in terms of the normalized mean absolute error and 25% in terms of the normalized root mean square error.

14 SOLAR ENERGY↗
DOE OSTI2024

Quantum subspace expansion in the presence of hardware noise

Finding ground state energies on current quantum processing units (QPUs) using algorithms such as the variational quantum eigensolver (VQE) continues to pose challenges. Hardware noise severely affects both the expressivity and trainability of parameterized quantum circuits, limiting them to shallow depths in practice. Here, we demonstrate that both issues can be addressed by synergistically integrating VQE with a quantum subspace expansion, allowing for an optimal balance between quantum and classical computing capabilities and costs. We perform a systematic benchmark analysis of the iterative quantum-assisted eigensolver in the presence of hardware noise. We determine ground state energies of 1D and 2D mixed-field Ising spin models on noisy simulators and the IBM QPUs ibmq_quito (5 qubits) and ibmq_guadalupe (16 qubits). To maximize accuracy, we propose a suitable criterion to select the subspace basis vectors according to the trace of the noisy overlap matrix. Finally, we show how to systematically approach the exact solution by performing controlled quantum error mitigation based on probabilistic error reduction on the noisy backend fake_guadalupe.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

A two-stage method for microcalcification cluster segmentation in mammography by deformable models

Purpose: Segmentation of microcalcification (MC) clusters in x-ray mammography is a difficult task for radiologists. Accurate segmentation is prerequisite for quantitative image analysis of MC clusters and subsequent feature extraction and classification in computer-aided diagnosis schemes. Methods: In this study, a two-stage semiautomated segmentation method of MC clusters is investigated. The first stage is targeted to accurate and time efficient segmentation of the majority of the particles of a MC cluster, by means of a level set method. The second stage is targeted to shape refinement of selected individual MCs, by means of an active contour model. Both methods are applied in the framework of a rich scale-space representation, provided by the wavelet transform at integer scales. Segmentation reliability of the proposed method in terms of inter and intraobserver agreements was evaluated in a case sample of 80 MC clusters originating from the digital database for screening mammography, corresponding to 4 morphology types (punctate: 22, fine linear branching: 16, pleomorphic: 18, and amorphous: 24) of MC clusters, assessing radiologists’ segmentations quantitatively by two distance metrics (Hausdorff distance—HDIST{sub cluster}, average of minimum distance—AMINDIST{sub cluster}) and the area overlap measure (AOM{sub cluster}). The effect of the proposed segmentation method on MC cluster characterization accuracy was evaluated in a case sample of 162 pleomorphic MC clusters (72 malignant and 90 benign). Ten MC cluster features, targeted to capture morphologic properties of individual MCs in a cluster (area, major length, perimeter, compactness, and spread), were extracted and a correlation-based feature selection method yielded a feature subset to feed in a support vector machine classifier. Classification performance of the MC cluster features was estimated by means of the area under receiver operating characteristic curve (Az ± Standard Error) utilizing tenfold cross-validation methodology. A previously developed B-spline active rays segmentation method was also considered for comparison purposes. Results: Interobserver and intraobserver segmentation agreements (median and [25%, 75%] quartile range) were substantial with respect to the distance metrics HDIST{sub cluster} (2.3 [1.8, 2.9] and 2.5 [2.1, 3.2] pixels) and AMINDIST{sub cluster} (0.8 [0.6, 1.0] and 1.0 [0.8, 1.2] pixels), while moderate with respect to AOM{sub cluster} (0.64 [0.55, 0.71] and 0.59 [0.52, 0.66]). The proposed segmentation method outperformed (0.80 ± 0.04) statistically significantly (Mann-Whitney U-test, p < 0.05) the B-spline active rays segmentation method (0.69 ± 0.04), suggesting the significance of the proposed semiautomated method. Conclusions: Results indicate a reliable semiautomated segmentation method for MC clusters offered by deformable models, which could be utilized in MC cluster quantitative image analysis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Single-energy computed tomography-based pulmonary perfusion imaging: Proof-of-principle in a canine model

Purpose: Radiotherapy (RT) that selectively avoids irradiating highly functional lung regions may reduce pulmonary toxicity, which is substantial in lung cancer RT. Single-energy computed tomography (CT) pulmonary perfusion imaging has several advantages (e.g., higher resolution) over other modalities and has great potential for widespread clinical implementation, particularly in RT. The purpose of this study was to establish proof-of-principle for single-energy CT perfusion imaging. Methods: Single-energy CT perfusion imaging is based on the following: (1) acquisition of end-inspiratory breath-hold CT scans before and after intravenous injection of iodinated contrast agents, (2) deformable image registration (DIR) for spatial mapping of those two CT image data sets, and (3) subtraction of the precontrast image data set from the postcontrast image data set, yielding a map of regional Hounsfield unit (HU) enhancement, a surrogate for regional perfusion. In a protocol approved by the institutional animal care and use committee, the authors acquired CT scans in the prone position for a total of 14 anesthetized canines (seven canines with normal lungs and seven canines with diseased lungs). The elastix algorithm was used for DIR. The accuracy of DIR was evaluated based on the target registration error (TRE) of 50 anatomic pulmonary landmarks per subject for 10 randomly selected subjects as well as on singularities (i.e., regions where the displacement vector field is not bijective). Prior to perfusion computation, HUs of the precontrast end-inspiratory image were corrected for variation in the lung inflation level between the precontrast and postcontrast end-inspiratory CT scans, using a model built from two additional precontrast CT scans at end-expiration and midinspiration. The authors also assessed spatial heterogeneity and gravitationally directed gradients of regional perfusion for normal lung subjects and diseased lung subjects using a two-sample two-tailed t-test. Results: The mean TRE (and standard deviation) was 0.6 ± 0.7 mm (smaller than the voxel dimension) for DIR between pre contrast and postcontrast end-inspiratory CT image data sets. No singularities were observed in the displacement vector fields. The mean HU enhancement (and standard deviation) was 37.3 ± 10.5 HU for normal lung subjects and 30.7 ± 13.5 HU for diseased lung subjects. Spatial heterogeneity of regional perfusion was found to be higher for diseased lung subjects than for normal lung subjects, i.e., a mean coefficient of variation of 2.06 vs 1.59 (p = 0.07). The average gravitationally directed gradient was strong and significant (R{sup 2} = 0.99, p < 0.01) for normal lung dogs, whereas it was moderate and nonsignificant (R{sup 2} = 0.61, p = 0.12) for diseased lung dogs. Conclusions: This canine study demonstrated the accuracy of DIR with subvoxel TREs on average, higher spatial heterogeneity of regional perfusion for diseased lung subjects than for normal lung subjects, and a strong gravitationally directed gradient for normal lung subjects, providing proof-of-principle for single-energy CT pulmonary perfusion imaging. Further studies such as comparison with other perfusion imaging modalities will be necessary to validate the physiological significance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Utah FORGE: InSAR Data 2019

This dataset contains Interferometric Synthetic Aperture Radar (InSAR) data used for ground deformation monitoring during Phase 2C of the Utah FORGE project. The dataset includes measurements of the mean rate of range change and associated standard errors, provided in both CSV and NetCDF formats. Supporting materials include histograms, maps, and MATLAB scripts used for data processing, as well as unit vector information describing the satellite's sensor orientation. Compressed archives contain additional metadata and masked range change data for individual interferometric pairs. A README file is included to provide further details on the dataset's structure and contents.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Random Forest Regressor-Based Approach for Detecting Fault Location and Duration in Power Systems

Power system failures or outages due to short-circuits or “faults” can result in long service interruptions leading to significant socio-economic consequences. It is critical for electrical utilities to quickly ascertain fault characteristics, including location, type, and duration, to reduce the service time of an outage. Existing fault detection mechanisms (relays and digital fault recorders) are slow to communicate the fault characteristics upstream to the substations and control centers for action to be taken quickly. Fortunately, due to availability of high-resolution phasor measurement units (PMUs), more event-driven solutions can be captured in real time. In this paper, we propose a data-driven approach for determining fault characteristics using samples of fault trajectories. A random forest regressor (RFR)-based model is used to detect real-time fault location and its duration simultaneously. This model is based on combining multiple uncorrelated trees with state-of-the-art boosting and aggregating techniques in order to obtain robust generalizations and greater accuracy without overfitting or underfitting. Four cases were studied to evaluate the performance of RFR: 1. Detecting fault location (case 1), 2. Predicting fault duration (case 2), 3. Handling missing data (case 3), and 4. Identifying fault location and length in a real-time streaming environment (case 4). A comparative analysis was conducted between the RFR algorithm and state-of-the-art models, including deep neural network, Hoeffding tree, neural network, support vector machine, decision tree, naive Bayesian, and K-nearest neighborhood. Experiments revealed that RFR consistently outperformed the other models in detection accuracy, prediction error, and processing time.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1972

Burst decoding of binary block codes on Q-ary output channels.

The burst-b distance between two binary vectors is defined and shown to be a metric. This definition is applied to a binary-input, Q-ary output channel where errors occur in bursts. A decoding algorithm is presented for such a channel that is an extension of Weldon's (1971) weighted erasure decoding. Examples are presented illustrating the techniques.

Wainberg, S.↗
NASA NTRS1978

Navigation performance of the Triscan concept for shipboard VTOL aircraft operations

The paper deals with the Triscan concept - a dual-antenna microwave landing guidance system, using triangulation for close-in accuracy - developed to facilitate the landing of VTOL aircraft on ships in all-weather conditions. Analysis of the navigation performance of an onboard system receiving data from Triscan and data-linked information regarding the motion of the ship showed that the approach navigation performance depends on the approach path profile flown, the magnitude of the measurement bias error, and the navigation system's knowledge of the shipboard landing pad motion, which was implemented through the concept of a landing pad deviation vector.

Mcgee, L. A.↗
NASA NTRS1980

Backus effect observed by Magsat

Two harmonic expansions of the geomagnetic potential, obtained from Magsat, are compared, one based on scalar data and one based on vector data. It is found that although the field magnitudes given by the two models are in close agreement, the vector fields are not; the vector difference was highly regular. Analysis of the data showed that the Backus effect (1970) accounted for most of the discrepancy. This result emphasizes the importance of using vector data in deriving global models of the geomagnetic field and suggests that some past models based on scalar data alone may suffer from errors of a similar nature.

Source record↗
NASA NTRS1989

Additional development of the XTRAN3S computer program

Additional developments and enhancements to the XTRAN3S computer program, a code for calculation of steady and unsteady aerodynamics, and associated aeroelastic solutions, for 3-D wings in the transonic flow regime are described. Algorithm improvements for the XTRAN3S program were provided including an implicit finite difference scheme to enhance the allowable time step and vectorization for improved computational efficiency. The code was modified to treat configurations with a fuselage, multiple stores/nacelles/pylons, and winglets. Computer program changes (updates) for error corrections and updates for version control are provided.

Borland, C. J.↗