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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 541 records · Page 30

Improve the Search of Very Metal-poor Stars Using the Deep Learning Method

Very metal-poor (VMP) stars have [Fe/H] < -2.0 dex. They are among the oldest stars in the universe, and their unique metallicity can help explore the enrichment mechanism and evolutionary history of the chemical elements of stars in the early universe. However, most current stellar parameter estimation methods do not perform well in determining the stellar parameters of VMP stars, which limits our ability to discover and exploit the properties of VMP stars. In this study, we propose a new model based on a convolutional neural network to determine the stellar atmospheric parameters of VMP stars. We tested our model on the LAMOST spectra; our model can determine the effective temperature (T {sub eff}), surface gravity (log g), metallicity ([Fe/H]), and carbon abundance ([C/Fe]) of the LAMOST spectra with precisions σ(T {sub eff}) = 134.82 K, σ(log g) = 0.33 dex, σ ([Fe/H]) = 0.20 dex, and σ([C/Fe]) = 0.35 dex. Furthermore, our model can distinguish VMP stars from normal stars with an accuracy of 88.65%. We also compared this model with other widely used methods, and found that this method performs better than other methods. It can be applied to the stellar parameter pipelines of upcoming large surveys such as 4MOST, WEAVES, and MOONS to search for VMP stars and identify carbon-enhanced metal-poor stars.

36 MATERIALS SCIENCE↗

Applications of truncated QR methods to sinusoidal frequency estimation

Three truncated QR methods are proposed for sinusoidal frequency estimation: (1) truncated QR without column pivoting (TQR), (2) truncated QR with preordered columns, and (3) truncated QR with column pivoting. It is demonstrated that the benefit of truncated SVD for high frequency resolution is achievable under the truncated QR approach with much lower computational cost. Other attractive features of the proposed methods include the ease of updating, which is difficult for the SVD method, and numerical stability. TQR methods thus offer efficient ways to identify sinusoidals closely clustered in frequencies under stationary and nonstationary conditions.

Hsieh, S. F.↗

Demonstration of machine-learning-enhanced Bayesian quantum state estimation

Machine learning (ML) has found broad applicability in quantum information science in topics as diverse as experimental design, state classification, and even studies on quantum foundations. Here, we experimentally realize an approach for defining custom prior distributions that are automatically tuned using ML for Bayesian quantum state estimation methods that generally better conform to the physical properties of the underlying system than standard fixed prior distributions. Previously, researchers have looked to Bayesian quantum state tomography for advantages like uncertainty quantification, the return of reliable estimates under any measurement condition, and minimal mean-squared error. However, practical challenges related to long computation times and conceptual issues concerning how to incorporate prior knowledge most suitably can overshadow these benefits. Using both simulated and experimental measurement results, we demonstrate that ML-defined prior distributions reduce net convergence times and provide a natural way to incorporate both implicit and explicit information directly into the prior distribution. These results constitute a promising path toward practical implementations of Bayesian quantum state tomography.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Comparing Tropopause-Penetrating Convection Identifications Derived from NEXRAD and GOES over the Contiguous United States

Overshooting cloud tops (OTs) are a result of powerful updrafts that rapidly transport air from the troposphere to the lower stratosphere. Aside from the well-known relationships between strong updrafts and severe weather, the boundaries of updrafts, including the OT, are turbulent, which leads to irreversible mixing of air between the stratosphere and troposphere, altering the composition of both layers. In order to better understand the impact of OTs, knowing precisely when and where they occur is vital. Within the last decade remote-sensing observations from satellites and radars have been used to identify OTs, but the results thus far have not been entirely consistent due to challenges with accurately identifying OTs with these sensor datasets. This study compares OTs identified using NEXRAD reflectivity data from the GridRad dataset with an approach that uses GOES infrared (IR) data. The GridRad method estimates the altitude of echo tops directly from the radar pointing geometry, merging a combination of radars that enables products every 5 mins, with 2 km spatial and 1 km vertical grid spacing. The GOES satellite method uses spatial patterns in tropopause-relative IR brightness temperature to derive an OT likelihood. The study region covers a large part of the contiguous United States during selected active convection dates in 2017 and includes data from GOES-13/16. A large sample of OTs observed by NEXRAD and GOES-13/16 satellites are analyzed to better understand NEXRAD and IR observations of OTs, quantify agreement between the OT detection methods, and demonstrate how the 4x increase in spatial resolution from GOES-13 to GOES-16 impacts OT algorithm detection performance. The results show that for nearly time-matched scenes, with many severe storms, GOES-13 and -16 detection accuracy is quite comparable; however, some missed detections are attributed to poorer GOES-13 image resolution. It was found that GOES-13 OT regions are ~2 K warmer than GOES-16 on average, but such differences exceed 5 K for the most intense OT regions. It is found that false GOES IR-based detections are unavoidable, given that cold cloud pixels significantly colder than the tropopause from nearby or recently decayed OTs can persist within anvils for 15 minutes or more.

John W. Cooney↗

Bootstrapping outperforms community‐weighted approaches for estimating the shapes of phenotypic distributions

Abstract Estimating phenotypic distributions of populations and communities is central to many questions in ecology and evolution. These distributions can be characterized by their moments (mean, variance, skewness and kurtosis) or diversity metrics (e.g. functional richness). Typically, such moments and metrics are calculated using community‐weighted approaches (e.g. abundance‐weighted mean). We propose an alternative bootstrapping approach that allows flexibility in trait sampling and explicit incorporation of intraspecific variation, and show that this approach significantly improves estimation while allowing us to quantify uncertainty. We assess the performance of different approaches for estimating the moments of trait distributions across various sampling scenarios, taxa and datasets by comparing estimates derived from simulated samples with the true values calculated from full datasets. Simulations differ in sampling intensity (individuals per species), sampling biases (abundance, size), trait data source (local vs. global) and estimation method (two types of community‐weighting, two types of bootstrapping). We introduce the traitstrap R package, which contains a modular and extensible set of bootstrapping and weighted‐averaging functions that use community composition and trait data to estimate the moments of community trait distributions with their uncertainty. Importantly, the first function in the workflow, trait_fill , allows the user to specify hierarchical structures (e.g. plot within site, experiment vs. control, species within genus) to assign trait values to each taxon in each community sample. Across all taxa, simulations and metrics, bootstrapping approaches were more accurate and less biased than community‐weighted approaches. With bootstrapping, a sample size of 9 or more measurements per species per trait generally included the true mean within the 95% CI. It reduced average percent errors by 26%–74% relative to community‐weighting. Random sampling across all species outperformed both size‐ and abundance‐biased sampling. Our results suggest randomly sampling ~9 individuals per sampling unit and species, covering all species in the community and analysing the data using nonparametric bootstrapping generally enable reliable inference on trait distributions, including the central moments, of communities. By providing better estimates of community trait distributions, bootstrapping approaches can improve our ability to link traits to both the processes that generate them and their effects on ecosystems.

Maitner, Brian S.↗

Kalman-like estimation for static distributed systems Antenna shape from radiation measurements

This paper advances an approach to the determination of shape of static distributed systems. It also illustrates the application of the approach to the problems of surface diagnosis of large parabolic reflectors. The estimation methods developed combine in an optimal sense the information from an elliptic model of the structure and from measurements of the structural deflection and of the far-field pattern changes due to the structural deformation. The estimators have a predictor-corrector structure, quite similar to that of a Kalman filter. The system model is first used to obtain a predicted estimate. A correction term is then added to the prediction to obtain the final state estimate. The relative weighting between prediction and correction terms is determined by an estimator gain. As in a Kalman filter, the estimator gain can be expressed in terms of the state estimation error covariance.

Rodriguez, G.↗

Method and system for non-linear motion estimation

A method and system for extrapolating and interpolating a visual signal including determining a first motion vector between a first pixel position in a first image to a second pixel position in a second image, determining a second motion vector between the second pixel position in the second image and a third pixel position in a third image, determining a third motion vector between one of the first pixel position in the first image and the second pixel position in the second image, and the second pixel position in the second image and the third pixel position in the third image using a non-linear model, determining a position of the fourth pixel in a fourth image based upon the third motion vector.

Lu, Ligang↗

Analytic marginalization of N(z) uncertainties in tomographic galaxy surveys

In this paper, we present a new method to marginalize over uncertainties in redshift distributions, N(z), within tomographic cosmological analyses applicable to current and upcoming photometric galaxy surveys. We allow for arbitrary deviations from the best-guess N(z) governed by a general covariance matrix describing the uncertainty in our knowledge of redshift distributions. In principle, this is marginalization over hundreds or thousands of new parameters describing potential deviations as a function of redshift and tomographic bin. However, by linearly expanding the theory predictions around a fiducial model, this marginalization can be performed analytically, resulting in a modified data covariance matrix that effectively downweights the modes of the data vector that are more sensitive to redshift distribution variations. We showcase this method by applying it to the galaxy clustering measurements from the Hyper Suprime-Cam first data release. We illustrate how to marginalize over sample variance of the calibration sample and a large general systematic uncertainty in photometric estimation methods, and explore the impact of priors imposing smoothness in the redshift distributions.

79 ASTRONOMY AND ASTROPHYSICS↗

Robust Adaptive Decentralized Dynamic State Estimation with Unknown Control Inputs using Field PMU Measurements

This paper proposes a robust adaptive decentralized dynamic state estimation method for power system with unknown inputs of the highly detailed synchronous machine model. The temporal and spatial correlations among the unknown inputs are used to derive a vector auto-regressive model. The latter is further integrated together with state transition and measurement models for joint state and unknown inputs estimation. Thanks to the consideration of implicit cross-correlations between the states and the unknown inputs, only generator terminal voltage and current phasors are needed. Test results on the US WECC system using the field PMU measurements show that the proposed method is able to track both the system dynamic states and unknown controller inputs. These information could significantly benefit the validation and calibration of generator controller parameters.

Zhao, Junbo↗

Improving the Discipline of Cost Estimation and Analysis

The need to improve the quality and accuracy of cost estimates of proposed new aerospace systems has been widely recognized. The industry has done the best job of maintaining related capability with improvements in estimation methods and giving appropriate priority to the hiring and training of qualified analysts. Some parts of Government, and National Aeronautics and Space Administration (NASA) in particular, continue to need major improvements in this area. Recently, NASA recognized that its cost estimation and analysis capabilities had eroded to the point that the ability to provide timely, reliable estimates was impacting the confidence in planning man), program activities. As a result, this year the Agency established a lead role for cost estimation and analysis. The Independent Program Assessment Office located at the Langley Research Center was given this responsibility.

Piland, William M.↗

Improving The Discipline of Cost Estimation and Analysis

The need to improve the quality and accuracy of cost estimates of proposed new aerospace systems has been widely recognized. The industry has done the best job of maintaining related capability with improvements in estimation methods and giving appropriate priority to the hiring and training of qualified analysts. Some parts of Government, and National Aeronautics and Space Administration (NASA) in particular, continue to need major improvements in this area. Recently, NASA recognized that its cost estimation and analysis capabilities had eroded to the point that the ability to provide timely, reliable estimates was impacting the confidence in planning many program activities. As a result, this year the Agency established a lead role for cost estimation and analysis. The Independent Program Assessment Office located at the Langley Research Center was given this responsibility. This paper presents the plans for the newly established role. Described is how the Independent Program Assessment Office, working with all NASA Centers, NASA Headquarters, other Government agencies, and industry, is focused on creating cost estimation and analysis as a professional discipline that will be recognized equally with the technical disciplines needed to design new space and aeronautics activities. Investments in selected, new analysis tools, creating advanced training opportunities for analysts, and developing career paths for future analysts engaged in the discipline are all elements of the plan. Plans also include increasing the human resources available to conduct independent cost analysis of Agency programs during their formulation, to improve near-term capability to conduct economic cost-benefit assessments, to support NASA management's decision process, and to provide cost analysis results emphasizing "full-cost" and "full-life cycle" considerations. The Agency cost analysis improvement plan has been approved for implementation starting this calendar year. Adequate financial and human resources are being made available to accomplish the goals of this important effort, and all indications are that NASA's cost estimation and analysis core competencies will be substantially improved within the foreseeable future.

Piland, William M.↗

A Vision–based Robust $\mathcal{H}$ ∞ Gain Scheduling Longitudinal and Lateral Following Controller for Autonomous Vehicles on Urban Curved Roads

Implementing advanced driver assistance systems (ADAS) in congested and intricate urban traffic scenarios poses significant challenges. To address the frequent stop–and–go motions exhibited by autonomous vehicles (AVs) navigating urban roads with changes in curvature, we propose a vision–based robust $\mathcal{H}$ ∞ adaptive cruise control system (ACC) for longitudinal control, plus a lane keeping assist system (LKAS) for lateral control. For the vision-based ACC, a weighted probability objective function for the vehicle following behavior is formulated. We incorporate $\mathcal{H}$ ∞ performance and gain scheduling techniques to mitigate the impact of uncertainty in visual sensor measurements. Furthermore, the optimal time headway is scheduled based on the velocity to ensure traffic flow efficiency and safety during the vehicle following process. For the LKAS, we introduce a road curvature estimation method that integrates lane and vehicle dynamics information to obtain the lateral and heading offsets. Next, the design criterion of the observer–based robust gain scheduling lateral motion controller is established by linear matrix inequality (LMI). Here, a series of experiments conducted within a camera–in–loop platform validate the proposed method.

33 ADVANCED PROPULSION SYSTEMS↗

Pterodactyl: Thermal Protection System for Integrated Control Design of a Mechanically Deployed Entry Vehicle

The need for precision landing of high mass payloads on Mars and the return of sensitive samples from other planetary bodies to specific locations on Earth is driving the development of an innovative NASA technology referred to as the Deployable Entry Vehicle (DEV). A DEV has the potential to deliver an equivalent science payload with a stowed diameter 3 to 4 times smaller than a traditional rigid capsule configuration. However, the DEV design does not easily lend itself to traditional methods of directional control. The NASA Space Technology Mission Directorate (STMD)’s Pterodactyl project is currently investigating the effectiveness of three different Guidance and Control (G&C) systems – actuated flaps, Center of Gravity (CG) or mass movement, and Reaction Control System (RCS) – for use with a DEV using the Adaptable, Deployable, Entry, and Placement Technology (ADEPT) design. This paper details the Thermal Protection System (TPS) design and associated mass estimation efforts for each of the G&C systems. TPS is needed for the nose cap of the DEV and the flaps of the actuated flap control system. The development of a TPS selection, sizing, and mass estimation method designed to deal with the varying requirements for the G&C options throughout the trajectory is presented. The paper discusses the methods used to i) obtain heating environments throughout the trajectory with respect to the chosen control system and resulting geometry; ii) determine a suitable TPS material; iii) produce TPS thickness estimations; and, iv) determine the final TPS mass estimation based on TPS thickness, vehicle control system, vehicle structure, and vehicle payload.

Hays, Zane B.↗

Sedimentary Facies Analysis Using AVIRIS Data: A Geophysical Inverse Problem

AVIRIS data can be used to quantitatively analyze and map sedimentary lithofacies. The observed radiance spectra can be reduced to 'apparent reflectance' spectra by topographic and reflectance characterization of several field sites within the image. These apparent reflectance spectra correspond to the true reflectance at each pixel, multiplied by an unknown illumination factor (ranging in value from zero to one). The spatial abundance patterns of spectrally defined lithofacies and the unknown illumination factors can be simultaneously derived using constrained linear spectral unmixing methods. Estimates of the minimum uncertainty in the final results (due to noise, instrument resolutions, degree of illumination and mixing systematics) can be made by forward and inverse modeling. Specific facies studies in the Rattlesnake Hills region of Wyoming illustrate the successful application of these methods.

Boardmann, Joe W.↗

A slope reversal video processor having amplitude and pulse width discrimination.

A timing discriminator whose output is relatively insensitive to input pulse width and amplitude is described. The video-handling technique is known as slope reversal processing and is based on tapped delay line estimation methods. The concept, design, breadboard construction, and preliminary laboratory test results are reviewed. The processor system features (1) a peak input voltage dynamic range of 80x starting at 100 microvolts; (2) a four stage preamplifier/line-driver having a voltage gain of 2400x; (3) a tapped delay-line estimator implemented for slope reversal triggering by differential comparison; (4) a nominal plus or minus 2.5 nsec shift of the output trigger leading edge over the entire input voltage range, (5) up to 7 dB discrimination against pulse widths less than 35 nsec; and (6) up to one order of magnitude reduction in the false alarm rate compared to a constant fraction system.

Hoge, F. E.↗

Venus Gravity Handbook

This report documents the Venus gravity methods and results to date (model MGNP90LSAAP). It is called a handbook in that it contains many useful plots (such as geometry and orbit behavior) that are useful in evaluating the tracking data. We discuss the models that are used in processing the Doppler data and the estimation method for determining the gravity field. With Pioneer Venus Orbiter and Magellan tracking data, the Venus gravity field was determined complete to degree and order 90 with the use of the JPL Cray T3D Supercomputer. The gravity field shows unprecedented high correlation with topography and resolution of features to the 2OOkm resolution. In the procedure for solving the gravity field, other information is gained as well, and, for example, we discuss results for the Venus ephemeris, Love number, pole orientation of Venus, and atmospheric densities. Of significance is the Love number solution which indicates a liquid core for Venus. The ephemeris of Venus is determined to an accuracy of 0.02 mm/s (tens of meters in position), and the rotation period to 243.0194 +/- 0.0002 days.

Konopliv, Alexander S.↗