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At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Estimation of soil classes and their relationship to grapevine vigor in a Bordeaux vineyard: advancing the practical joint use of electromagnetic induction (EMI) and NDVI datasets for precision viticulture

Working within a vineyard in the Pessac Léognan Appellation of Bordeaux, France, this study documents the potential of using simple statistical methods with spatially-resolved and increasingly available electromagnetic induction (EMI) geophysical and normalized difference vegetation index (NDVI) datasets to accurately estimate Bordeaux vineyard soil classes and to quantitatively explore the relationship between vineyard soil types and grapevine vigor. First, co-located electrical tomographic tomography (ERT) and EMI datasets were compared to gain confidence about how the EMI method averaged soil properties over the grapevine rooting depth. Then, EMI data were used with core soil texture and soil-pit based interpretations of Bordeaux soil types (Brunisol, Redoxisol, Colluviosol and Calcosol) to estimate the spatial distribution of geophysically-identified Bordeaux soil classes. A strong relationship (r = 0.75, p < 0.01) was revealed between the geophysically-identified Bordeaux soil classes and NDVI (both 2 m resolution), showing that the highest grapevine vigor was associated with the Bordeaux soil classes having the largest clay fraction. The results suggest that within-block variability of grapevine vigor was largely controlled by variability in soil classes, and that carefully collected EMI and NDVI datasets can be exceedingly helpful for providing quantitative estimates of vineyard soil and vigor variability, as well as their covariation. The method is expected to be transferable to other viticultural regions, providing an approach to use easy-to-acquire, high resolution datasets to guide viticultural practices, including routine management and replanting.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Determining Stability Margins in Adiabatic Superconducting Magnets with 3-D Finite Element Analysis

Superconducting magnets play a key role in the development of experiments at Fermilab; understanding the operating stability of these can allow us to utilize more potent magnets for future experiments (like the proposed Muon Collider), optimize the design of magnets in more immediate experiments (like Mu2e), and research the future use of more exotic materials (like high-temperature superconductors). This summer, I developed a 3-D parametric FEA program in ANSYS Mechanical APDL that simulates quench in superconducting magnets, and I also developed a parametric MATLAB program that predicts thermal behavior in magnet quench using the MIITS method. These programs can provide useful quenching parameters (like minimum quench energy and normal zone propagation velocity) for different cases of quench, leading to the previously mentioned objective of magnet design optimization. To test the programs, preliminary cases were run and the data produced was compared and analyzed. The results of these analyses, as well as the program operating methods, are discussed in this project.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2004

Evaluation of Double-Vacuum-Bag Process For Composite Fabrication

A non-autoclave vacuum bag process using atmospheric pressure alone that eliminates the need for external pressure normally supplied by an autoclave or a press is an attractive method for composite fabrication. This type of process does not require large capital expenditures for tooling and processing equipment. In the molding cycle (temperature/pressure profile) for a given composite system, the vacuum application point has to be carefully selected to achieve the final consolidated laminate net shape and resin content without excessive resin squeeze-out. The traditional single-vacuum- bag (SVB) process is best suited for molding epoxy matrix based composites because of their superior flow and the absence of reaction by-products or other volatiles. Other classes of materials, such as polyimides and phenolics, generate water during cure. In addition, these materials are commonly synthesized as oligomers using solvents to facilitate processability. Volatiles (solvents and reaction byproducts) management therefore becomes a critical issue. SVB molding, without additional pressure, normally fails to yield void-free quality composites for these classes of resin systems. A double-vacuum- bag (DVB) process for volatile management was envisioned, designed and built at the NASA Langley Research Center. This experimental DVB process affords superior volatiles management compared to the traditional SVB process. Void-free composites are consistently fabricated as measured by C-scan and optical photomicroscopy for high performance polyimide and phenolic resins.

Hou, T. H.↗
NASA NTRS1983

Transformer induced instability of the series resonant converter

It is shown that the common series resonant power converter is subject to a low frequency oscillation that can lead to the loss of cyclic stability. This oscillation is caused by a low frequency resonant circuit formed by the normal L and C components in series with the magnetizing inductance of the output transformer. Three methods for eliminating this oscillation are presented and analyzed. One of these methods requires a change in the circuit topology during the resonance cycle. This requires a new set of steady state equations which are derived and presented in a normalized form. Experimental results are included which demonstrate the nature of the low frequency oscillation before cyclic stability is lost.

King, R. J.↗
NASA NTRS1991

Radiation Modeling with Direct Simulation Monte Carlo

Improvements in the modeling of radiation in low density shock waves with direct simulation Monte Carlo (DSMC) are the subject of this study. A new scheme to determine the relaxation collision numbers for excitation of electronic states is proposed. This scheme attempts to move the DSMC programs toward a more detailed modeling of the physics and more reliance on available rate data. The new method is compared with the current modeling technique and both techniques are compared with available experimental data. The differences in the results are evaluated. The test case is based on experimental measurements from the AVCO-Everett Research Laboratory electric arc-driven shock tube of a normal shock wave in air at 10 km/s and .1 Torr. The new method agrees with the available data as well as the results from the earlier scheme and is more easily extrapolated to di erent ow conditions.

Carlson, Ann B.↗
NASA NTRS2003

Calibration of TOMS Radiances From Ground Observations

Verification of a stratospheric ozone recovery remains a high priority for environmental research and policy definition. Models predict an ozone recovery at a much lower rate than the measured depletion rate observed to date. Therefore improved precision of the satellite and ground ozone observing systems are required over the long term to verify its recovery. We show that validation of radiances from the ground can be a very effective means for correcting long term drifts of backscatter type satellite measurements and can be used to cross calibrate all BUV instruments in orbit (TOMS, SBUV/2, GOME, SCIAMACHY, OMI, GOME-2, OMPS). This method bypasses the retrieval algorithms used to derive ozone products from both satellite and ground based measurements that are normally used to validate the satellite data. Radiance comparisons employ forward models, but they are inherently more accurate than the retrieval This method employs very accurate comparisons between ground based zenith sicy radiances and satellite nadir radiances and employs two well established capabilities at the Goddard Space Flight Center, 1) the SSBUV calibration facilities and 2) the radiative transfer codes used for the TOMS and SBUV/2 algorithms and their subsequent refinements. The zenith sky observations are made by the SSBUV where its calibration is maintained to a high degree of accuracy and precision. Radiative transfer calculations show that ground based zenith sky and satellite nadir backscatter ultraviolet comparisons can be made very accurately under certain viewing conditions. Initial ground observations taken from Goddard Space Flight Center compared with radiative transfer calculations has indicated the feasibility of this method. The effect of aerosols and varying ozone amounts are considered in the model simulations and the theoretical comparisons. The radiative transfer simulations show that the ground and satellite radiance comparisons can be made with an uncertainty of less than l\% without the knowledge of the amount ozone viewed by either instrument on ground or in space. algorithms.

Bojkov, B. R.↗
DOE OSTI2022

Inference for Nonparanormal Partial Correlation via Regularized Rank-Based Nodewise Regression

Abstract Partial correlation is a common tool in studying conditional dependence for Gaussian distributed data. However, partial correlation being zero may not be equivalent to conditional independence under non-Gaussian distributions. In this paper, we propose a statistical inference procedure for partial correlations under the high-dimensional nonparanormal (NPN) model where the observed data are normally distributed after certain monotone transformations. The NPN partial correlation is the partial correlation of the normal transformed data under the NPN model, which is a more general measure of conditional dependence. We estimate the NPN partial correlations by regularized nodewise regression based on the empirical ranks of the original data. A multiple testing procedure is proposed to identify the nonzero NPN partial correlations. The proposed method can be carried out by a simple coordinate descent algorithm for lasso optimization. It is easy-to-implement and computationally more efficient compared to the existing methods for estimating NPN graphical models. Theoretical results are developed to show the asymptotic normality of the proposed estimator and to justify the proposed multiple testing procedure. Numerical simulations and a case study on brain imaging data demonstrate the utility of the proposed procedure and evaluate its performance compared to the existing methods. Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Using Median Point in Keeling Plot to Reduce the Uncertainty of the Isotopic Composition of Evapotranspiration

Abstract The isotopic composition of evapotranspirationδ ET is a crucial parameter in isotope-based evapotranspiration (ET) partitioning and moisture recycling studies. The Keeling plot method is the most prevalent method to calculateδ ET , though it contains large extrapolated uncertainties from the least squares regression. Traditional Keeling regression uses the mean point of individual measurements. Here, a modified Keeling plot framework was proposed using the median point of individual measurements. We tested theδ ET uncertainty using the mean point [σ ET (mean)] and median point [σ ET (median)]. Multiple resolutions of input and output data from six independent sites were used to test the performance of the two methods. Theσ ET (mean) would be greater thanσ ET (median) when the mean value of inverse vapor concentration () is greater than the median value of inverse vapor concentration []. When applying the filter ofr 2 > 0.8, around 70% ofσ ET (mean) was greater thanσ ET (median). This phenomenon might be due to the normality of the vapor concentrationC υ producing the asymmetric distribution of 1/C υ . The median method could perform significantly better than the mean method when inputting high-resolution measurements (e.g., 1 Hz) and when the water vapor concentrationC υ is relatively low. Compared to the mean method, applying the median method could on average reduce 6.88% of ET partitioning uncertainties and could on average reduce 9.00% of moisture recycling uncertainties. This study provided a new insight of the Keeling plot method and emphasized handling model output uncertainty from multiple perspectives instead of only from input parameters.

Meteorology & Atmospheric Sciences↗
NASA NTRS1986

Making High-Porosity Alloy Spheroids

Noncontact process yields low-density, porous microstructure. Small spheroids of porous alloys with large surface area per unit volume produced by containerless processing method. Without container walls to serve as nucleation sites, alloy cools to well below normal freezing point without solidifying. Solidification then proceeds rapidly; interdendritic liquid pulled out by growing crystals, resulting in porous microstructure. The more rapid the cooling rate, the faster crystals grow and more porous solid becomes. Drop-tube method useful in creating porous microstructures from other materials including oxides, carbides, and organic materials. Other means of containerless processing - acoustic or air-jet levitation, low-gravity float melting, melt spinning, or jet spraying, adapted to process.

Ethridge, E. C.↗
NASA NTRS1982

Climate studies from satellite observations - Special problems in the verification of earth radiation balance, cloud climatology, and related climate experiments

A body of techniques that have been developed and planned for use during the Earth Radiation Budget Experiment (ERBE), the International Satellite Cloud Climatology Project (ISCCP), and related climate experiments of the 1980's are reviewed. Validation and verification methods must apply for systems of satellites. They include: (1) use of a normalization or intercalibration satellite, (2) special intensive observation areas located over ground-truth sites, and (3) monitoring of sun and earth by several satellites and/or several instruments at the same time. Since each climate application area has a hierarchy of user communities, validation techniques vary from very detailed methods to those that simply assure high relative accuracy in detecting space and time variations for climate studies. It is shown that climate experiments generally require more emphasis on long-term stability and internal consistency of satellite data sets than high absolute accuracy.

Vonder Haar, T. H.↗
DOE OSTI2021

Detection of Outliers in LiDAR Data Acquired by Multiple Platforms over Sorghum and Maize

High-resolution point cloud data acquired with a laser scanner from any platform contain random noise and outliers. Therefore, outlier detection in LiDAR data is often necessary prior to analysis. Applications in agriculture are particularly challenging, as there is typically no prior knowledge of the statistical distribution of points, plant complexity, and local point densities, which are crop-dependent. The goals of this study were first to investigate approaches to minimize the impact of outliers on LiDAR acquired over agricultural row crops, and specifically for sorghum and maize breeding experiments, by an unmanned aerial vehicle (UAV) and a wheel-based ground platform; second, to evaluate the impact of existing outliers in the datasets on leaf area index (LAI) prediction using LiDAR data. Two methods were investigated to detect and remove the outliers from the plant datasets. The first was based on surface fitting to noisy point cloud data via normal and curvature estimation in a local neighborhood. The second utilized the PointCleanNet deep learning framework. Both methods were applied to individual plants and field-based datasets. To evaluate the method, an F-score was calculated for synthetic data in the controlled conditions, and LAI, the variable being predicted, was computed both before and after outlier removal for both scenarios. Results indicate that the deep learning method for outlier detection is more robust than the geometric approach to changes in point densities, level of noise, and shapes. The prediction of LAI was also improved for the wheel-based vehicle data based on the coefficient of determination (R2) and the root mean squared error (RMSE) of the residuals before and after the removal of outliers.

36 MATERIALS SCIENCE↗
NASA NTRS1987

Cellular automatons applied to gas dynamic problems

This paper compares the results of a relatively new computational fluid dynamics method, cellular automatons, with experimental data and analytical results. This technique has been shown to qualitatively predict fluidlike behavior; however, there have been few published comparisons with experiment or other theories. Comparisons are made for a one-dimensional supersonic piston problem, Stokes first problem, and the flow past a normal flat plate. These comparisons are used to assess the ability of the method to accurately model fluid dynamic behavior and to point out its limitations. Reasonable results were obtained for all three test cases, but the fundamental limitations of cellular automatons are numerous. It may be misleading, at this time, to say that cellular automatons are a computationally efficient technique. Other methods, based on continuum or kinetic theory, would also be very efficient if as little of the physics were included.

Long, Lyle N.↗
NASA NTRS1992

Electromagnetic scattering by coated convex surfaces and wedges simulated by approximate boundary conditions

Asymptotic/high-frequency solutions are developed for analyzing the non-specular scattering mechanisms associated with coated convex surfaces and edges simulated by approximate boundary conditions. In particular, the standard impedance boundary conditions (SIBC's) and the second order generalized impedance boundary conditions (GIBC's) are employed for a characterization of the edge diffraction, creeping wave, and surface diffracted wave contributions. To study the creeping wave and surface diffracted wave mechanisms, rigorous UTD (uniform geometrical theory of diffraction) diffraction coefficients are developed for a convex coated cylinder simulated with SIBC's and GIBC's. The ray solutions obtained remain valid in the transition region and reduce uniformly to those in the deep lit and shadow regions. A uniform asymptotic solution is also presented for observations in the close vicinity of the cylinder. The diffraction coefficient for a convex cylinder are obtained via a generalization of the corresponding ones of the circular cylinder. To validate the asymptotic/high-frequency solution, integral equations are derived for both E and H-polarization and solved numerically using the method of moments. Results are presented for a single and three layered coated convex cylinder. Some insights are also provided on the accuracy of the employed GIBC's versus SIBC's for application to curved surfaces. To characterize the scattering by impedance wedges illuminated at skew incidence, diffraction coefficients are derived from an approximate solution of the governing functional difference equations. This solution exactly recovers the known ones for an impedance half plane or an arbitrary wedge at normal incidence, and to validate it for other wedge angles, a moment method code was used. Finally, to test the usefulness of the approximate skew incidence impedance wedge diffraction coefficient for three dimensional structures, equivalent currents are derived in the context of the physical theory of diffraction (PTD) for a finite length impedance wedge of arbitrary internal angles. These are incorporated in a standard general purpose PTD code and results are presented for a number of different impedance structures.

Syed, H. H.↗
DOE OSTI2024

Generative machine learning for detector response modeling with a conditional normalizing flow

In this paper, we explore the potential of generative machine learning models as an alternative to the computationally expensive Monte Carlo (MC) simulations commonly used by the Large Hadron Collider (LHC) experiments. Our objective is to develop a generative model capable of efficiently simulating detector responses for specific particle observables, focusing on the correlations between detector responses of different particles in the same event and accommodating asymmetric detector responses. Here, we present a conditional normalizing flow model ($\mathcal{CNF}$) based on a chain of Masked Autoregressive Flows, which effectively incorporates conditional variables and models high-dimensional density distributions. We assess the performance of the $\mathcal{CNF}$ model using a simulated sample of Higgs boson decaying to diphoton events at the LHC. We create reconstruction-level observables using a smearing technique. We show that conditional normalizing flows can accurately model complex detector responses and their correlation. This method can potentially reduce the computational burden associated with generating large numbers of simulated events while ensuring that the generated events meet the requirements for data analyses. We make our code available at https://github.com/allixu/normalizing_flow_for_detector_response

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1993

Failure monitoring in dynamic systems: Model construction without fault training data

Advances in the use of autoregressive models, pattern recognition methods, and hidden Markov models for on-line health monitoring of dynamic systems (such as DSN antennas) have recently been reported. However, the algorithms described in previous work have the significant drawback that data acquired under fault conditions are assumed to be available in order to train the model used for monitoring the system under observation. This article reports that this assumption can be relaxed and that hidden Markov monitoring models can be constructed using only data acquired under normal conditions and prior knowledge of the system characteristics being measured. The method is described and evaluated on data from the DSS 13 34-m beam wave guide antenna. The primary conclusion from the experimental results is that the method is indeed practical and holds considerable promise for application at the 70-m antenna sites where acquisition of fault data under controlled conditions is not realistic.

Smyth, P.↗
NASA NTRS1976

Application of parametric and non-parametric statistics to sounding rocket dispersion including large sample and small sample theory

Analytical methods for obtaining large and small samples to be used in sounding rocket dispersion statistics are described. When the distribution of the parent population is assumed known, a method is called parametric. When no assumption is made about the parent population, the method is called nonparametric. Parametric and nonparametric methods are given for both large and small samples. The assumed distribution for the parametric case will be normal and it is shown that sample nonparametric theory is easier to apply in many cases, giving essentially the same results as parametric theory. The method is applied to the dispersion of NASA sounding rockets from 1959 to 1974.

James F. McGarvey↗
NASA NTRS1987

The calculated influence of atmospheric conditions on solar cell ISC under direct and global solar irradiances

Calculations of the influence of atmospheric conditions on solar cell short-circuit current (Isc) are made using a recently developed computer model for solar spectral irradiance distribution. The results isolate the dependence of Isc on changes in the spectral irradiance distribution without the direct influence of the total irradiance level. The calculated direct normal irradiance and percent diffuse irradiance are given as a reference to indicate the expected irradiance levels. This method can be applied to the calibration of photovoltaic reference cells. Graphic examples are provided for amorphous silicon and monocrystalline silicon solar cells under direct normal and global normal solar irradiances.

Mueller, Robert L.↗
NASA NTRS2021

Sputtering of Surfaces by Ion Irradiation: A Comparison of Molecular Dynamics and Binary Collision Approximation Models to Laboratory Measurements

We compare various sputtering simulation methods to experimental results in both the low energy (<1 keV) and high energy (≥1 keV) impact regimes for argon ions impacting a pure copper substrate at normal incidence. Our results indicate that for high energy impacts, both binary collision approximation (BCA) and molecular dynamics methods can be used to generate reasonable predictions for the yield and energy distribution of the sputtered atoms. We also find reasonable agreement between the theoretical and experimental results down to impact energies of 600 eV. However, at 200 eV impact energies, significant discrepancies appear between the experimental and theoretical ejecta energy distributions in the peak position, the width of the energy distribution, and the magnitude of the high energy tail. These discrepancies appear to arise from the experimental results being only for atoms sputtered normal to the substrate surface, whereas the theoretical results are integrated over all 2π solid angles above the surface. Using the BCA code SDTrimSP and limiting the results to only atoms emitted within ±15° of the surface normal brings theory and experiment into reasonable agreement. These results suggest that for low energy impacts, the energy distribution of sputtered atoms is highly dependent on the emission angle of the ejecta.

Solar wind↗