Bayesian Target Detection Algorithms for Solid Subpixel Targets in Hyperspectral Images
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97 MATHEMATICS AND COMPUTING↗
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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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Effect of Air Plasma Sprayed Flash Bond Coatings on Furnace Cycle Lifetime of Disks and Rods
Air plasma sprayed (APS) flash coatings on high velocity oxygen fuel (HVOF) bond coatings are well known to extend the lifetime of thermal barrier coatings (TBCs). Recent work compared flash coatings of NiCoCrAlY and NiCoCrAlYHfSi applied to both rods and disk substrates of alloy 247. For rod specimens, 100 h cycles were used at 1100 °C in wet air. Both flash coatings significantly improved the lifetime compared to HVOF-only and vacuum plasma spray (VPS)-only MCrAlY bond coatings with no statistical difference between the two flash coatings. For disk specimens tested in 1 h cycles at 1100 °C in wet air, the NiCoCrAlY flash coating significantly outperformed an HVOF-only NiCoCrAlYHfSi bond coating and a NiCoCrAlYHfSi flash coating. The flash coatings formed a mixed oxide-metal zone that appeared to inhibit crack formation and therefore extend lifetime. In addition to the flash coating increasing the bond coating roughness, the underlying HVOF layer acted as a source of Al for this intermixed zone and prevented the oxide from penetrating deeper into the bond coating. Here, the lower Y+Hf content in the Y-only flash coating appeared to minimize oxidation in the flash layer, thereby increasing the benefit compared to a NiCoCrAlYHfSi flash coating.
42 ENGINEERING↗
Effect of APS flash bond coatings on furnace cycle lifetime of disks and rods
Air plasma sprayed (APS) flash coatings on high velocity oxygen fuel (HVOF) bond coatings are well known to extend the lifetime of thermal barrier coatings. Recent work compared flash coatings of NiCoCrAlY and NiCoCrAlYHfSi applied to both rods and disk substrates of alloy 247. For rod specimens, 100-h cycles were used at 1100°C in wet air. Both flash coatings significantly improved the lifetime compared to HVOF-only and VPS-only MCrAlY bond coatings with no statistical difference between the two flash coatings. For disk specimens tested in 1-h cycles at 1100°C in wet air, the NiCoCrAlY flash coating significantly outperformed an HVOFonly NiCoCrAlYHfSi bond coating and a NiCoCrAlYHfSi flash coating. The flash coatings formed a mixed oxide-metal zone that appeared to inhibit crack formation and extend lifetime. In addition to the flash coating increasing the bond coating roughness, the underlying HVOF layer acted as a source of Al for this intermixed zone and prevented the oxide from penetrating deeper into the bond coating. The lower Y+Hf level in the Y-only flash coating appeared to minimize oxidation in the flash layer, thereby increasing the benefit compared to a NiCoCrAlYHfSi flash coating.
Pint, Bruce↗
Machine learning in a data-limited regime: Augmenting experiments with synthetic data uncovers order in crumpled sheets
Machine learning has gained widespread attention as a powerful tool to identify structure in complex, high-dimensional data. However, these techniques are ostensibly inapplicable for experimental systems where data are scarce or expensive to obtain. Here, we introduce a strategy to resolve this impasse by augmenting the experimental dataset with synthetically generated data of a much simpler sister system. Specifically, we study spontaneously emerging local order in crease networks of crumpled thin sheets, a paradigmatic example of spatial complexity, and show that machine learning techniques can be effective even in a data-limited regime. This is achieved by augmenting the scarce experimental dataset with inexhaustible amounts of simulated data of rigid flat-folded sheets, which are simple to simulate and share common statistical properties. This considerably improves the predictive power in a test problem of pattern completion and demonstrates the usefulness of machine learning in bench-top experiments where data are good but scarce.
97 MATHEMATICS AND COMPUTING↗
An Improved Double-Gaussian Closure for the Subgrid Vertical Velocity Probability Distribution Function
Abstract The vertical velocity probability distribution function (PDF) is analyzed throughout the depth of the lower atmosphere, including the subcloud and cloud layers, in four large-eddy simulation (LES) cases of shallow cumulus and stratocumulus. Double-Gaussian PDF closures are examined to test their ability to represent a wide range of turbulence statistics, from stratocumulus cloud layers characterized by Gaussian turbulence to shallow cumulus cloud layers displaying strongly non-Gaussian turbulence statistics. While the majority of the model closures are found to perform well in the former case, the latter presents a considerable challenge. A new model closure is suggested that accounts for high skewness and kurtosis seen in shallow cumulus cloud layers. The well-established parabolic relationship between skewness and kurtosis is examined, with results in agreement with previous studies for the subcloud layer. In cumulus cloud layers, however, a modified relationship is necessary to improve performance. The new closure significantly improves the estimation of the vertical velocity PDF for shallow cumulus cloud layers, in addition to performing well for stratocumulus. In particular, the long updraft tail representing the bulk of cloudy points is much better represented and higher-order moments diagnosed from the PDF are also greatly improved. However, some deficiencies remain owing to fundamental limitations of representing highly non-Gaussian turbulence statistics with a double-Gaussian PDF.
Fitch, A. C.↗
A Statistical Evaluation of WRF-LES Trace Gas Dispersion Using Project Prairie Grass Measurements
In recent years, new measurement systems have been deployed to monitor and quantify methane emissions from the natural gas sector. Large-eddy simulation (LES) has complemented measurement campaigns by serving as a controlled environment in which to study plume dynamics and sampling strategies. However, with few comparisons with controlled-release experiments, the accuracy of LES for modeling natural gas emissions is poorly characterized. In this paper, we evaluate LES from the Weather Research and Forecasting (WRF) Model against Project Prairie Grass campaign measurements and surface layer similarity theory. Using WRF-LES, we simulate continuous emissions from 30 near-surface trace gas sources in two stability regimes: strong convection and weak convection. We examine the impact of grid resolutions ranging from 6.25 to 52 m in the horizontal dimension on model results. We evaluate performance in a statistical framework, calculating fractional bias and conducting Welch’s t tests. WRF-LES accurately simulates observed surface concentrations at 100 m and beyond under strong convection; simulated concentrations pass t tests in this region irrespective of grid resolution. However, in weakly convective conditions with strong winds, WRF-LES substantially overpredicts concentrations—the magnitude of fractional bias often exceeds 30%, and all but one t test fails. The good performance of WRF-LES under strong convection correlates with agreement with local free convection theory and a minimal amount of parameterized turbulent kinetic energy. The poor performance under weak convection corresponds to misalignment with Monin–Obukhov similarity theory and a significant amount of parameterized turbulent kinetic energy.
17 WIND ENERGY↗
Generalizable, fast, and accurate DeepQSPR with fastprop
Abstract Quantitative Structure–Property Relationship studies (QSPR), often referred to interchangeably as QSAR, seek to establish a mapping between molecular structure and an arbitrary target property. Historically this was done on a target-by-target basis with new descriptors being devised to specifically map to a given target. Today software packages exist that calculate thousands of these descriptors, enabling general modeling typically with classical and machine learning methods. Also present today are learned representation methods in which deep learning models generate a target-specific representation during training. The former requires less training data and offers improved speed and interpretability while the latter offers excellent generality, while the intersection of the two remains under-explored. This paper introduces , a software package and general Deep-QSPR framework that combines a cogent set of molecular descriptors with deep learning to achieve state-of-the-art performance on datasets ranging from tens to tens of thousands of molecules. provides both a user-friendly Command Line Interface and highly interoperable set of Python modules for the training and deployment of feedforward neural networks for property prediction. This approach yields improvements in speed and interpretability over existing methods while statistically equaling or exceeding their performance across most of the tested benchmarks. is designed with Research Software Engineering best practices and is free and open source, hosted at github.com/jacksonburns/fastprop.
Burns, Jackson W. (ORCID:0000000206579426)↗
Time-lapse seismic data inversion for estimating reservoir parameters using deep learning
Geologic carbon sequestration involves the injection of captured carbon dioxide ([Formula: see text]) into subsurface formations for long-term storage. The movement and fate of the injected [Formula: see text] plume is of great concern to regulators because monitoring helps to identify potential leakage zones and determines the possibility of safe long-term storage. To address this concern, we design a deep-learning framework for [Formula: see text] saturation monitoring to determine the geologic controls on the storage of the injected [Formula: see text]. We use different combinations of porosities and permeabilities for a given reservoir to generate saturation and velocity models. We train the deep-learning model with a few time-lapse seismic images and their corresponding changes in saturation values for a particular [Formula: see text] injection site. The deep-learning model learns the mapping from the change in the time-lapse seismic response to the change in [Formula: see text] saturation during the training phase. We then apply the trained model to data sets comprising different time-lapse seismic image slices (corresponding to different time instances) generated using different porosity and permeability distributions that are not part of the training to estimate the [Formula: see text] saturation values along with the plume extent. Our algorithm provides a deep-learning assisted framework for the direct estimation of [Formula: see text] saturation values and plume migration in heterogeneous formations using the time-lapse seismic data. Our method improves the efficiency of time-lapse inversion by streamlining the large number of intermediate steps in the conventional time-lapse inversion workflow. This method also helps to incorporate the geologic uncertainty for a given reservoir by accounting for the statistical distribution of porosity and permeability during the training phase. Tests on different examples verify the effectiveness of our approach.
Geochemistry & Geophysics↗
Data and Scripts associated with: “Laboratory evaluation of open source and commercial electrical conductivity sensor precision and accuracy”
This data package is associated with the publication “Laboratory evaluation of open source and commercial electrical conductivity sensor precision and accuracy: How do they compare?” submitted to PLOS ONE and accepted for publication (Fulton, S.G. et al. 2023; doi not yet available).Variation in electrical conductivity (EC) of water is important to reveal environmental disturbance and natural dynamics, including factors such as anthropogenic salinization. This data package supports a study addressing the need for a robust performance assessment of open source (OS) EC sensors. We evaluated the accuracy (mean error, %) and precision (sample standard deviation) of OS EC sensors in the laboratory via comparison to EC calibration standards using three different OS and OS/commercial-hybrid (OS/C) EC sensors and data logger configurations and two commercial (C) EC sensors and data logger configurations. We also evaluated the effect of cable length (7.5 m and 30 m) and sensor calibration on OS sensor accuracy and precision. This data package presents the results from the different testing laboratory configurations. It also includes an R script for statistical analysis of the data and an Arduino IDE file used to calibrate and collect data with the OS Atlas EC sensor. File types are .csv, .pdf, .R, and .ino.
54 ENVIRONMENTAL SCIENCES↗
PredNet Algorithm for NGSS Cameras: June 2019 Update [Slides]
PredNet experiments used datasets from the NGSS cameras at the Gamma Irradiation Facility at Sandia National Laboratories. PredNet results show containers entering the facility as anomalous and with these results we are now determining the best suited statistics to evaluate the outputs. A statistical evaluation of the number of pixels flagged during the testing for the container entering or exiting the facility shows significant differences between the two directions which is very promising
47 OTHER INSTRUMENTATION↗
Analysis of Deformation and Fracture Mechanisms in the Harvested Low-Dose Baffle Former Bolt via Advanced Mechanical Tests
This report details the production of tensile specimens from in-service irradiated baffle former bolts (BFBs) and presents the results of a pilot in-situ SEM/EBSD test conducted at Oak Ridge National Laboratory’s Low Activation Materials Development and Analysis (LAMDA) facility. The SEM/EDS results confirmed that the material is AISI 316L steel, not AISI 347, and that no Nb addition was detected in several analyzed locations. EBSD analysis of the microstructure revealed in-grain misorientation gradients indicative of cold work, likely caused by material processing, and no retained ferrite was identified. During straining, dislocation channel formation was the primary deformation mechanism, with twinning also observed in favorably oriented grains at local strains as small as ~1.5%. No strain-induced phase instability was observed, likely due to the fact that the Ni and Cr content reached the upper limits for the 316L steel specification. Multiple microfracture events were observed during the tensile test. Fine strain-induced pores formed at the channel-grain boundary intersection points, while coarser microcracks were associated with non-metallic inclusions. Data analysis is ongoing, and additional tests are planned in the near future to provide more statistics and details.
36 MATERIALS SCIENCE↗
Diffusion of energetic electrons in turbulent plasmas of the solar wind
A method of calculation of the diffusion coefficients D(v) of particles in velocity space, based on the statistical analysis of the motion of a great number of test electrons, is proposed. In the case of Langmuir turbulence developing in plasmas with fluctuating density inhomogeneities such as the solar wind, simulations provide coefficients D(v) which mainly depend on the Langmuir wave spectra and agree well with the analytical predictions D{sub th}(v) of the quasilinear theory of weak turbulence. Nevertheless, some noticeable differences exist with this theory: in the range of phase velocity of the short waves where the main part of the wave energy is concentrated, D(v) is noticeably smaller than D{sub th}(v), due to the scattering, the reflection, and the focusing effects encountered by the Langmuir waves when they interact with the plasma density inhomogeneities. Moreover, the probability of large velocity jumps in the particles’ trajectories essentially exceeds the probability of a Gaussian distribution. These large jumps, which are connected with the waves’ transformation processes, modify the nature of the particle diffusion, which is no more classical. These higher order effects cause the discrepancies observed with the quasilinear theory, which does not take them into account in its perturbative approach. The solar wind plasmas, which present fluctuating density inhomogeneities of noticeable average levels, are a very good laboratory to study such diffusion processes, which can eventually influence significantly on the development of essential physical phenomena, as electromagnetic radio emissions by type III solar radio bursts, for example.
79 ASTRONOMY AND ASTROPHYSICS↗
The Thousand Aviator Study - Distributions and intercorrelations of selected variables
Distributions and intercorrelations of 100 variables selected from physiological, personal history, and psychological measures of 1963 evaluation in Pensacola thousand aviator study
PSYCHOLOGICAL TESTING↗
Tables of critical values for examining compositional non-randomness in proteins and nucleic acids
A binomially distributed statistic is defined to show whether or not the proportion of a particular amino acid in a protein deviates from random expectation. An analogous statistic is derived for nucleotides in nucleic acids. These new statistics are simply related to the classical chi-squared test. They explicitly account for the compositional fluctuations imposed by the finite length of proteins, and they are more accurate than previous tables.
Laird, M.↗
CARETS: A prototype regional environmental information system. Volume 2, parts A and B: Norfolk and environs; a land use perspective
The author has identified the following significant results. The Norfolk-Portsmouth metropolitan statistical area in southeastern Virginia was the site of intensive testing of a number of land resources assessment methods. Land use and land cover data at three levels of detail were derived by manual image interpretation from both aircraft and satellite sources and used to characterize the 1,766 sq km (682 sq mi) area from the perspective of its various resource-related activities and problems. Measurements at level 1 from 1:100, 000 scale maps revealed 42 percent of the test area (excluding bays and estuaries) to be forest, 28 percent agriculture, 23 percent urban and built-up, 4 percent nonforested wetlands, and 2 percent water. At the same scale and level of detail, 10 percent of the area underwent change from one land use category to another in the period 1959-70, 62 percent of which involved the relatively irreversible change from forest or agriculture to urban uses.
Norfolk-Portsmouth SHSA↗
Statistically conditioned least squares retrievals planned for the VAS demonstration experiment
Problems in the retrieval of atmospheric profiles from passively observed satellite radiances are reviewed. Plans are described for statistically conditioned least squares retrievals of temperature and moisture profiles around mesoscale events, based upon the expected sensitivity of the VAS channels to the atmospheric variations. Simulated soundings for a global data set and for the 1976 National Storm Laboratory (NSSL) severe storm data set are also examined. This combination of radiance modeling and statistical conditioning should yield reliable mesoscale soundings and provide a test bed for sounding research and development with the VAS instrument.
Chester, D.↗
Crop classification using airborne radar and LANDSAT data
Airborne radar data acquired with a 13.3 GHz scatterometer over a test-site near Colby, Kansas were used to investigate the statistical properties of the scattering coefficient of three types of vegetation cover and of bare soil. A statistical model for radar data was developed that incorporates signal-fading and natural within-field variabilities. Estimates of the within-field and between-field coefficients of variation were obtained for each cover-type and compared with similar quantities derived from LANDSAT images of the same fields. The classification accuracy provided by LANDSAT alone, radar alone, and both sensors combined was investigated. The results indicate that the addition of radar to LANDSAT improves the classification accuracy by about 10; percentage-points when the classification is performed on a pixel basis and by about 15 points when performed on a field-average basis.
Ulaby, F. T.↗
Analysis of the quality of image data acquired by the LANDSAT-4 thematic mapper and multispectral scanners
A seven step procedure developed for evaluating the geometric properties of MSS and TM film produces is being implemented. Some 476 control points were selected of which 238 are being tested and edited for digitization and scaling errors. Tables show statistics established for assessing the spectral characteristics and variability, as well as the spatial resolution and radiometric sensitivity of TM data for a forest environment in an effort to determine the extent to which major forest cover type can be detected and identified on TM digital and image products. Results thus far show that the high quality obtained are more than sufficient for meeting most of the inventory objectives of the renewable resource specialist. The TM data should be extremely valuable for: (1) estimating forest cover types; (2) updating land use survey maps; and (3) determining the size and shape and location of individual forest clearings and water resources.
Colwell, R. N.↗