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At least 1,783 records · Page 99
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Seismic moment tensor classification using elliptical distribution functions on the hypersphere

Discrimination of underground explosions from naturally occurring earthquakes and other anthropogenic sources is one of the fundamental challenges of nuclear explosion monitoring. In an operational setting, the number of events that can be thoroughly investigated by analysts is limited by available resources. The capability to rapidly screen out events that can be robustly identified as not being explosions is, therefore, of great potential benefit. Nevertheless, possible mis-classification of explosions as earthquakes currently limits the use of screening methods for verification of test-ban treaties. Moment tensors provide a physics-based classification tool for the characterization of different seismic sources and have enabled the advent of new techniques for discriminating between earthquakes and explosions. Following normalization and projection of their six-degree vectors onto the hypersphere, existing screening approaches use spherically symmetric metrics to determine whether any new moment tensor may have been an explosion. Here, we show that populations of moment tensors for both earthquakes and explosions are anisotropically distributed on the hypersphere. Distributions possessing elliptical symmetry, such as the scaled von Mises–Fisher distribution, therefore provide a better description of these populations than the existing spherically symmetric models. We describe a method that uses these elliptical distributions in combination with a Bayesian classifier to achieve successful classification rates of 99 per cent for explosions and 98 per cent for earthquakes using existing catalogues of events from the western United States. The 1983 May 5 Crowdie underground nuclear test and 2018 July 20 DAG-1 deep-borehole chemical explosion are the only two explosions out of 140 that are incorrectly classified. Application of the method to the 2006–2017 nuclear tests in the Democratic People’s Republic of Korea yields 100 per cent identification rates and we provide a simple routine MTid for general usage. The approach provides a means to rapidly assess the likelihood of an event being an explosion and can be built into monitoring workflows that rely on simultaneously assessing multiple different discrimination metrics.

58 GEOSCIENCES↗
NASA NTRS1990

Development of an integrated BEM approach for hot fluid structure interaction

A comprehensive boundary element method is presented for transient thermoelastic analysis of hot section Earth-to-Orbit engine components. This time-domain formulation requires discretization of only the surface of the component, and thus provides an attractive alternative to finite element analysis for this class of problems. In addition, steep thermal gradients, which often occur near the surface, can be captured more readily since with a boundary element approach there are no shape functions to constrain the solution in the direction normal to the surface. For example, the circular disc analysis indicates the high level of accuracy that can be obtained. In fact, on the basis of reduced modeling effort and improved accuracy, it appears that the present boundary element method should be the preferred approach for general problems of transient thermoelasticity.

Dargush, G. F.↗
NASA NTRS1985

Noise correction on LANDSAT images using a spline-like algorithm

Many applications using LANDSAT images face a dilemma: the user needs a certain scene (for example, a flooded region), but that particular image may present interference or noise in form of horizontal stripes. During automatic analysis, this interference or noise may cause false readings of the region of interest. In order to minimize this interference or noise, many solutions are used, for instane, that of using the average (simple or weighted) values of the neighboring vertical points. In the case of high interference (more than one adjacent line lost) the method of averages may not suit the desired purpose. The solution proposed is to use a spline-like algorithm (weighted splines). This type of interpolation is simple to be computer implemented, fast, uses only four points in each interval, and eliminates the necessity of solving a linear equation system. In the normal mode of operation, the first and second derivatives of the solution function are continuous and determined by data points, as in cubic splines. It is possible, however, to impose the values of the first derivatives, in order to account for shapr boundaries, without increasing the computational effort. Some examples using the proposed method are also shown.

Vijaykumar, N. L.↗
NASA NTRS1997

Determination of Residual Stress in Composite Materials Using Ultrasonic Waves

The performance of high temperature composites can be significantly affected by the presence of residual stresses. These stresses arise during cooling processes from fabrication to room temperature due to mismatch of thermal expansion coefficients between matrix and fiber materials. This effect is especially pronounced in metal matrix and intermetallic composites. It can lead to plastic deformations, matrix cracking and fiber/matrix interface debonding. In this work the feasibility of ultrasonic techniques for residual stress assessment in composites is addressed. A novel technique for absolute stress determination in orthotropic materials from angular dependencies of ultrasonic velocities is described. The technique is applicable for determination of both applied and residual stresses and does not require calibration measurements on a reference sample. The important advantage of this method is that stress is determined simultaneously with stress-dependent elastic constants and is thus decoupled from the material texture. It is demonstrated that when the principal plane stress directions coincide with acoustical axes, the angular velocity data in the plane perpendicular to the stress plane may be used to determine both stress components. When the stress is off the acoustical axes, the shear and the difference of the normal stress components may be determined from the angular dependence of group velocities in the plane of stresses. Synthetic sets of experimental data corresponding to materials with different anisotropy and stress levels are used to check the applicability of the technique. The method is also verified experimentally. A high precision ultrasonic wave transmission technique is developed to measure angular dependence of ultrasonic velocities. Examples of stress determination from experimental velocity data are given. A method is presented for determination of velocities of ultrasonic waves propagating through the composite material with residual stresses. It is based on the generalized self-consistent multiple scattering model. Calculation results for longitudinal and shear ultrasonic wave velocities propagating perpendicular to the fibers direction in SCS-6/Ti composite with and without residual stresses are presented. They show that velocity changes due to presence of stresses are of order 1%.

Rokhlin, S. I.↗
NASA NTRS1985

High-latitude filtering in a global grid-point model using model normal modes

A normal modes expansion technique is applied to perform high latitude filtering in the GLAS fourth order global shallow water model with orography. The maximum permissible time step in the solution code is controlled by the frequency of the fastest propagating mode, which can be a gravity wave. Numerical methods are defined for filtering the data to identify the number of gravity modes to be included in the computations in order to obtain the appropriate zonal wavenumbers. The performances of the model with and without the filter, and with a time tendency and a prognostic field filter are tested with simulations of the Northern Hemisphere winter. The normal modes expansion technique is shown to leave the Rossby modes intact and permit 3-5 day predictions, a range not possible with the other high-latitude filters.

Takacs, L. L.↗
NASA NTRS1989

Controlled method of reducing electrophoretic mobility of various substances

A method of reducing electrophoretic mobility of macromolecules, particles, cells, and the like is provided. The method comprises interacting the particles or cells with a polymer-linked affinity compound composed of: a hydrophilic neutral polymer such as polyethylene glycol, and an affinity component consisting of a hydrophobic compound such as a fatty acid ester, an immunocompound such as an antibody or active fragment thereof or simular macromolecule, or other ligands. The reduction of electrophoretic mobility achieved is directly proportional to the concentration of the polymer-linked affinity compound employed, and the mobility reduction obtainable is up to 100 percent for particular particles and cells. The present invention is advantageous in that analytical electrophoretic separation can not be achieved for macromolecules, particles, and cells whose native surface charge structure had prevented them from being separated by normal electrophoretic means. Depending on the affinity component utilized, separation can be achieved on the basis of specific/irreversible, specific/reversible, semi-specific/reversible, relatively nonspecific/reversible, or relatively nonspecific/irreversible ligand-substance interactions. The present method is also advantageous in that it can be used in a variety of standard laboratory electrophoresis equipment.

Vanalstine, James M.↗
NASA NTRS2005

Effects of space flight conditions on the function of the immune system and catecholamine production simulated in a rodent model of hindlimb unloading

The rodent model of hindlimb unloading has been successfully used to simulate some of the effects of space flight conditions. Previous studies have indicated that mice exposed to hindlimb-unloading conditions have decreased resistance to infections compared to restrained and normally housed control mice. OBJECTIVE: The purpose of this study was to clarify the mechanisms involved in resistance to infection in this model by examining the effects of hindlimb unloading on the function of the immune system and its impact on the production of catecholamines. METHODS: Female Swiss Webster mice were hindlimb-unloaded during 48 h and the function of the immune system was assessed in spleen and peritoneal cells immediately after this period. In addition, the kinetics of catecholamine production was measured throughout the hindlimb-unloading period. RESULTS: The function of the immune system was significantly suppressed in the hindlimb-unloaded group compared to restrained and normally housed control mice. Levels of catecholamines were increased in the hindlimb-unloaded group and peaked at 12 h following the commencement of unloading. CONCLUSION: These results suggest that physiological responses of mice are altered early after hindlimb unloading and that catecholamines may play a critical role in the modulation of the immune system. These changes may affect the ability of mice to resist infections. Copyright (c) 2005 S. Karger AG, Basel.

NASA Discipline Regulatory Physiology↗
NASA NTRS2015

Representing Matrix Cracks Through Decomposition of the Deformation Gradient Tensor in Continuum Damage Mechanics Methods

A method is presented to represent the large-deformation kinematics of intraply matrix cracks and delaminations in continuum damage mechanics (CDM) constitutive material models. The method involves the additive decomposition of the deformation gradient tensor into 'crack' and 'bulk material' components. The response of the intact bulk material is represented by a reduced deformation gradient tensor, and the opening of an embedded cohesive interface is represented by a normalized cohesive displacement-jump vector. The rotation of the embedded interface is tracked as the material deforms and as the crack opens. The distribution of the total local deformation between the bulk material and the cohesive interface components is determined by minimizing the difference between the cohesive stress and the bulk material stress projected onto the cohesive interface. The improvements to the accuracy of CDM models that incorporate the presented method over existing approaches are demonstrated for a single element subjected to simple shear deformation and for a finite element model of a unidirectional open-hole tension specimen. The material model is implemented as a VUMAT user subroutine for the Abaqus/Explicit finite element software. The presented deformation gradient decomposition method reduces the artificial load transfer across matrix cracks subjected to large shearing deformations, and avoids the spurious secondary failure modes that often occur in analyses based on conventional progressive damage models.

Leone, Frank A., Jr.↗
DOE OSTI2025

New Probe of Cosmic Birefringence Using Galaxy Polarization and Shapes

We propose a novel statistical method to measure cosmic birefringence and demonstrate its power in probing parity violation due to axions. Exploiting an empirical correlation between the integrated radio polarization direction of a spiral galaxy and its apparent shape, we devise an unbiased minimum-variance estimator for the rotation angle, which should achieve an uncertainty of 5°–15° per galaxy. In conclusion, large galaxy samples from the forthcoming SKA continuum surveys, together with optical shape catalogs, promise a comparable or even lower noise power spectrum for the rotation angle than in the CMB Stage-IV (CMB-S4) experiment, with different systematics.

Axion-like particles↗
DOE OSTI2023

A bi-level data-driven framework for fault-detection and diagnosis of HVAC systems

Long-term operation of heating, ventilation, and air conditioning (HVAC) systems will eventually lead to a range of HVAC system failures, resulting in excessive energy consumption and maintenance costs. Here, to avoid HVAC malfunctioning, fault detection diagnostic (FDD) is utilized as a common practice. Machine learning methods have lately received considerable interest for FDD analysis of HVAC systems due to their high detection accuracy. Meanwhile, HVAC malfunctions are regarded as rare occurrences, hence normal operating data samples are much more accessible than data samples in faulty and malfunctioning conditions. The dominating frequency of normal operation in HVAC datasets has also led to heavily biased classification algorithms within the literature. Moreover, the focus of previous literature has been on increasing the accuracy of the models which leads to a high number of false positives (misleading alarms) in the system. In order to enhance the performance of diagnostic procedures and fill the mentioned gaps, this study proposes a novel data-driven framework. A bi-level machine learning framework is developed for diagnosing faults in air handling units (AHUs) and rooftop units (RTUs) based on principal component analysis (PCA), time series anomaly detection, and random forest (RF). It is shown that PCA can reduce the dataset dimension with one principal component accounting for 95% of data variance. Also, the random forest could classify the faults with 89% precision for single-zone AHU, 85% precision for RTU, and 79% for multi-zone AHU. By proposing this framework, three persistent challenges are addressed: (I) minimizing false positives; (II) accounting for data imbalance; and (III) normal condition monitoring of equipment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Prediction of Structures and Atomization Energies of Coinage Metals, (M)n, n < 20: Extrapolation of Normalized Clustering Energies to Predict the Cohesive Energy

The geometries of the group 11 coinage metals (n = 2-20) were optimized to determine the lowest energy isomers for each cluster size, singlets for even numbers and doublets for odd numbers. For copper and silver, 2-D (planar) geometries were favored up to n = 6. For gold, 2D (planar) geometries were favored up to n = 13. Normalized clustering energies were plotted as a function of cluster size (n-1/3, for n = 4-20) with various DFT functionals and the CCSD(T)-F12b method and were extrapolated to predict the bulk cohesive energy. In the case of copper and silver, there is excellent agreement between the cohesive energies predicted at the CCSD(T)-F12b level of theory and the experimental values. For gold, the CCSD(T)-F12b values needed to be corrected for spin-orbit relativistic effects to obtain good agreement with experiment. Electronic properties including the HOMO-LUMO gaps for the even clusters and the spin densities for the odd clusters were calculated. The lowest gap is predicted to occur for n = 16 where the HOMO and LUMO are very similar in shape.

Persuad, Rudradatt R.↗
DOE OSTI2020

Robust Matrix Completion State Estimation in Distribution Systems

Due to the insufficient measurements in the distribution system state estimation (DSSE), full observability and redundant measurements are difficult to achieve without using the pseudo measurements. The matrix completion state estimation (MCSE) combines the matrix completion and power system model to estimate voltage by exploring the low-rank characteristics of the matrix. This paper proposes a robust matrix completion state estimation (RMCSE) to estimate the voltage in a distribution system under a low-observability condition. Tradition state estimation weighted least squares (WLS) method requires full observability to calculate the states and needs redundant measurements to proceed a bad data detection. The proposed method improves the robustness of the MCSE to bad data by minimizing the rank of the matrix and measurements residual with different weights. It can estimate the system state in a low-observability system and has robust estimates without the bad data detection process in the face of multiple bad data. The method is numerically evaluated on the IEEE 33-node radial distribution system. The estimation performance and robustness of RMCSE are compared with the WLS with the largest normalized residual bad data identification (WLS-LNR), and the MCSE.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Sensor-based phenology from snowmelt experiment gradient, East River, Colorado, 2017 to 2020

The timing of snowmelt is a critical cue for the initiation of growth in mountain meadow ecosystems and can also impact the duration and magnitude of plant production. High frequency observations of species-level phenology are time consuming and require a high degree of expertise, and publicly available remote sensing products lack the necessary temporal resolution to assess fine-scale growing season dynamics. Near-surface sensing methods provide a middle ground with high temporal frequency and tractable spatial scales (from sub-meter to hillslope scale). This data package includes csv files of Normalized Difference Vegetation Index (NDVI) timeseries (SM_NDVI_dailymax.csv) and phenological thresholds (SM_NDVI_summary.csv) for sub-plots (1m2) and Green Chromatic Coordinate (GCC) phenological thresholds (SM_GCC_summary.csv) at the plot scale (10m x 14m). Location IDs associated with this data package are: ER-LM, WG-UM, WG-LS, ER-US, and XX-AL. Related data packages include: “Microclimate observations associated with snowmelt experiment gradient sites, East River, Colorado, 2017 to 2020” and “Colorado Elevation Gradient Snowmelt Manipulation Plant Phenology 2017-2018”.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Sensitivity and Uncertainty of the IFR-1 BISON Benchmark

The fuel performance code BISON is being used to evaluate metallic fuel for a new fast-spectrum test reactor called the Versatile Test Reactor, which is being considered by the US Department of Energy. To quantify the accuracy of BISON predictions, researchers at Oak Ridge National Laboratory have been developing a series of benchmarks based on legacy metallic fuel experiments. As part of this effort, the sensitivity of BISON predictions to variations in model inputs and the uncertainties associated with BISON predictions must be established. This report summarizes efforts to perform a comprehensive sensitivity analysis (SA) and uncertainty quantification (UQ) on a benchmark based on the IFR-1 experiment. For the SA, at least one input was chosen from every BISON model and physics module used in the benchmark. The inputs were varied individually in a series of BISON simulations. The resulting variations in benchmark predictions were normalized to calculate sensitivities. The strongest sensitivities were identified and used to inform input selections for the UQ. The UQ was performed using the Monte Carlo UQ method. A literature review was conducted to estimate uncertainty distributions for the selected inputs, and values were sampled randomly from each distribution in a series of BISON simulations. Variations in the benchmark predictions were used to estimate uncertainty distributions and confidence intervals. It was found that nearly 100% of benchmark predictions matched the corresponding legacy values within the confidence intervals. However, this is at least partially because of the wide confidence intervals associated with the benchmark predictions. The uncertainty contributions of assumptions in the benchmark, experimental uncertainties, and BISON models were quantified. Some analysis was performed to identify inputs that contributed to the uncertainties. Finally, recommendations are made for future benchmark development and future BISON development.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1972

The acoustic response of rooms with open windows to airborne sounds.

The objective of the work described in this and the companion paper was to establish a theory for predicting the sound field generated in a room by a sonic boom incident on an open window. In this paper, some basic theoretical results are presented. First, the case of a normally incident harmonic wave was considered. Expressions for the pressure field were obtained by viewing the room as a terminated duct and by using a Green function method. The concept of mode excitation distribution functions was formulated and used to match the boundary conditions. This concept has been extended for oblique incidence. A modified form of Laplace transform technique was used to obtain expressions in the time domain for transient signals.

Vaidya, P. G.↗
NASA NTRS1973

Oxygen consumption measurements during continual centrifugation of mice.

A simple method is described for measurement of metabolism of conscious, unrestrained animals, during chronic centrifugation or other conditions of isolation (23.75 hr/day) from the investigators in an essentially normal atmospheric environment for as long as seven days. This involves telemetry of pressure changes in a metabolic chamber. At 7 G's, increased O2 intake lasting two to seven days and a decreased excursion of the day-night difference were measured for male white mice with less effect or even an opposite effect at lower fields. Base-line measurements of metabolic rate per mouse are less affected by animal size than expected from the surface area law.

Fethke, W.↗
NASA NTRS1974

A solution to the problem of optimizing the fuel bias for a liquid propellant rocket by an application of the central limit theorem

A method of determining the fuel bias for a bipropellant liquid rocket that minimizes outage associated penalties on payload potential is presented. A fuel bias so derived is normally called the optimum fuel bias. The subjects discussed are: (1) probability density function of outage, (2) computer program listing, and (3) choosing the optimum fuel bias.

Viera, W. J.↗