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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Pulse-Burst PIV of an Impulsively Started Cylinder in a Shock Tube for Re > 10 5

Here, the impulsive start of a circular cylinder in a shock tube was characterized with time-resolved particle image velocimetry measurements (TR-PIV) using a pulse-burst laser. Three Reynolds numbers Re of 1.07 × 10 5 , 1.63 × 10 5 and 2.46 × 10 5 were studied adding insight into the transient process in the vicinity of the drag crisis. One symmetric vortex pair was shed from the cylinder at the lower Reynolds number prior to the wake going asymmetric in a fashion analogous to studies at lower Re. At Re ≥ 1.63 × 10 5 , two or more symmetric vortex pairs occurred prior to asymmetry and the eventual transition to a von Kármán vortex street. The non-dimensional rise time for vortex shedding to begin, as quantified by wavelet analysis, was found to be lower at the two higher Re. Finally, the study indicates a transformation in the impulsive wake to occur at Re near the critical regime and may serve as a benchmark for high Re numerical solutions.

42 ENGINEERING↗
DOE OSTI2016

Drivers and potential predictability of summer time North Atlantic polar front jet variability

The variability of the North Atlantic polar front jet stream is crucial in determining summer weather around the North Atlantic basin. Recent extreme summers in western Europe and North America have highlighted the need for greater understanding of this variability, in order to aid seasonal forecasting and mitigate societal, environmental and economic impacts. Here we find that simple linear regression and composite models based on a few predictable factors are able to explain up to 35 % of summertime jet stream speed and latitude variability from 1955 onwards. Sea surface temperature forcings impact predominantly on jet speed, whereas solar and cryospheric forcings appear to influence jet latitude. The cryospheric associations come from the previous autumn, suggesting the survival of an ice-induced signal through the winter season, whereas solar influences lead jet variability by a few years. Regression models covering the earlier part of the twentieth century are much less effective, presumably due to decreased availability of data, and increased uncertainty in observational reanalyses. Wavelet coherence analysis identifies that associations fluctuate over the study period but it is not clear whether this is just internal variability or genuine non-stationarity. Finally we identify areas for future research.

Meteorology & Atmospheric Sciences↗
DOE OSTI2023

Mallat Scattering Transformation based surrogate for Magnetohydrodynamics

Abstract A Machine and Deep Learning (MLDL) methodology is developed and applied to give a high fidelity, fast surrogate for 2D resistive MagnetoHydroDynamic (MHD) simulations of Magnetic Liner Inertial Fusion (MagLIF) implosions. The resistive MHD code is used to generate an ensemble of implosions with different liner aspect ratios, initial gas preheat temperatures (that is, different adiabats), and different liner perturbations. The liner density and magnetic field as functions of x , y , and z were generated. The Mallat Scattering Transformation (MST) is taken of the logarithm of both fields and a Principal Components Analysis (PCA) is done on the logarithm of the MST of both fields. The fields are projected onto the PCA vectors and a small number of these PCA vector components are kept. Singular Value Decompositions of the cross correlation of the input parameters to the output logarithm of the MST of the fields, and of the cross correlation of the SVD vector components to the PCA vector components are done. This allows the identification of the PCA vectors vis-a-vis the input parameters. Finally, a Multi Layer Perceptron (MLP) neural network with ReLU activation and a simple three layer encoder/decoder architecture is trained on this dataset to predict the PCA vector components of the fields as a function of time. Details of the implosion, stagnation, and the disassembly are well captured. Examination of the PCA vectors and a permutation importance analysis of the MLP show definitive evidence of an inverse turbulent cascade into a dipole emergent behavior. The orientation of the dipole is set by the initial liner perturbation. The analysis is repeated with a version of the MST which includes phase, called Wavelet Phase Harmonics (WPH). While WPH do not give the physical insight of the MST, they can and are inverted to give field configurations as a function of time, including field-to-field correlations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Spatial–temporal changes in potential evaporation patterns based on the Cloud model and their possible causes

It is of importance to comprehensively investigate the spatial-temporal changes in potential evaporation patterns, which helps guide the long-term water resource allocation and irrigation managements. In this study, the Cloud model was adopted to quantify the average, uniformity, and stability of annual potential evaporation in the Wei River Basin (WRB), a typical arid and semi-arid region in China.. The cross wavelet analysis was then applied to explore the correlations between potential evaporation and Arctic Oscillation (AO)/El Niño Southern Oscillation (ENSO) with an aim to determine the possible causes of potential evaporation variations. Results indicated that: (1) the average of annual potential evaporation in the WRB first declined and then increased, which was similar with its stability, whilst its dispersion degree exhibited a decreasing trend, implying that potential evaporation has a small inter-annual variation; (2) the average of potential evaporation in the western basin was obviously smaller than that in the other areas, while its uniformity and stability in the Guanzhong plain and the Loess Plateau areas are larger than those in other areas, particularly in the western basin where the uniformity and stability are the smallest; (3) both AO and ENSO exhibited strong correlations with potential evaporation variations, indicating that both AO and ENSO have played an important role in the annual potential evaporation variations in the WRB.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Minimal spanning tree algorithm for γ-ray source detection in sparse photon images: cluster parameters and selection strategies

We present that the minimal spanning tree (MST) algorithm is a graph-theoretical cluster-finding method. We previously applied it to γ-ray bidimensional images, showing that it is quite sensitive in finding faint sources. Possible sources are associated with the regions where the photon arrival directions clusterize. MST selects clusters starting from a particular “tree” connecting all the point of the image and performing a cut based on the angular distance between photons, with a number of events higher than a given threshold. In this paper, we show how a further filtering, based on some parameters linked to the cluster properties, can be applied to reduce spurious detections. We find that the most efficient parameter for this secondary selection is the magnitudeM of a cluster, defined as the product of its number of events by its clustering degree. We test the sensitivity of the method by means of simulated and real Fermi-Large Area Telescope (LAT) fields. Our results show that √M is strongly correlated with other statistical significance parameters, derived from a wavelet based algorithm and maximum likelihood (ML) analysis, and that it can be used as a good estimator of statistical significance of MST detections. Finally, we apply the method to a 2-year LAT image at energies higher than 3 GeV, and we show the presence of new clusters, likely associated with BL Lac objects.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

In-situ sensor monitoring of multi-class gas porosity formation in laser powder bed fusion using convolutional neural network

In-situ monitoring of defect formation remains a significant challenge in the laser powder bed fusion (LPBF) process. Recent advances have enabled real-time defect detection with machine learning and in-situ sensing technologies; however, most studies focus on binary classification of keyhole pores, limiting nuanced multi-class pore differentiation and formation mechanisms. This work introduces a multi-class pore detection framework (no pore, small pores < 15 µm, and large pores > 15 µm) by leveraging photodiode sensor data alongside high-fidelity synchrotron X-ray imaging. The 15 µm threshold is selected to distinguish between two fundamentally different defect mechanisms, following the physical size-mechanism boundary established by prior high-resolution synchrotron X-ray characterization of Al6061 LPBF. Distinguishing these classes is critical because large keyhole pores are structurally detrimental, whereas small gas pores are often benign, requiring different process control strategies. Thermal emission monitoring data collected simultaneously with high-speed X-ray imaging at the Stanford Synchrotron Radiation Lightsource (SSRL), are correlated with subsurface melt pool dynamics to establish ground truth. Continuous Wavelet Transform (CWT) with optimized parameters converts the photodiode time-series signals into time–frequency images, facilitating feature extraction. Convolutional Neural Networks (CNN) are then applied for real-time multi-class pore classification in an average inference time of 1 ms per signal window. It achieves 79% accuracy and an Area Under the Receiver Operating Characteristic curve (AUC ROC) score of 0.89 with five-fold cross-validation. The results demonstrate that coupling CWT-based feature engineering with CNN architecture enables reliable multi-class pore detection in Al6061 builds using affordable in-situ sensors. This approach advances scalable and affordable quality assurance in additive manufacturing by moving beyond binary defect detection toward more nuanced classification of porosity mechanisms with in-situ sensors and machine learning.

Laser powder bed fusion, Multi-class pores, In-sit↗
DOE OSTI2018

Analysis of Acoustic Emission Propagation in Metal-to-Metal Adhesively Bonded Joints

Acoustic emission (AE) monitoring shows promise as one of the most effective methods for condition monitoring of adhesively-bonded joints. Previous research has demonstrated its ability to detect, locate and classify adhesive joint failure, though in these studies little attention appears to have been paid to the differences in AE wave propagation through the bonded and un-bonded sections of the specimens tested, or to the effects of the wave modes excited or the propagation distances. This paper details an experimental study conducted on large aluminium sheet specimens to identify the effects of the presence of an adhesive layer on AE wave propagation. Three specimens are considered; a single aluminium sheet, two aluminium sheets placed together without adhesive, and an adhesively-bonded specimen. A pencil lead break (PLB) is used as a simulated AE source, and is applied to the three specimens at varying propagation distances and orientations. The acquired signals are processed using wavelet-transforms to explore time-frequency features, and compared with modified group-velocity curves based on the Rayleigh–Lamb equations to allow identification of wave-modes and edge-reflections. The effects of propagation distance and source orientation are investigated while comparison is made between the three specimens. It is concluded that while the wave propagation modes can be approximated as being constant throughout all three specimens, there is a significant change in the received waveforms due to the attenuation of high-frequency components exhibited by the bonded specimen. These findings may be utilised to provide a deeper understanding of acquired AE data, improving the current abilities to identify, locate and characterise damage mechanisms occurring within adhesive joints, ultimately improving safety in the use of adhesive bonding for critical applications.

42 ENGINEERING↗
DOE OSTI2019

A Chaos Theoretic Approach to Animal Activity Recognition

Animal activity is a descriptor that can be potentially used to track the health and well-being, which is obviously very important to improve the management process and productivity of farms. This paper deals with an animal behavior recognition problem using a chaos theory approach where we adopt such a technique for automatic classification of calves behavioral states. Two main mutually exclusive behaviors are of interest, namely, lying and standing/walking with six possible activities: feeding, drinking water, drinking milk, playing, rumination, and neutral. The time series generated by ear-tags with a 3D-accelerometer after a wavelet denoising transformation and frequency stabilization are treated as representations of the nonlinear dynamical system. The dynamical system of a certain animal state exhibits specific strange attractor in a phase space. A characterization of such an attractor is performed through metric, dynamic, and topological invariants including Lyapunov exponent, correlation dimension, length of a phase trajectory, sum of edges forming a convex hull and others. These measures are used as a feature vector for the subsequent classification. In a cross validation scheme, six classifiers are built on each training set, and the hyper-parameters are optimized using an inner validation set. The classifier that reaches the highest accuracy on the inner validation set is used to classify the outer validation set. It is shown that this approach can be useful at predicting activity states as an alternative methodology for the animal behavior state recognition problem with acceptable classification accuracy. Furthermore it is possible to include this procedure as part of an ensemble method in machine learning where a combination of different models is used.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

South African droughts and decadal variability

We explore the historical occurrence of extensive droughts over South Africa within the context of decadal climate variability. A Standardized Precipitation Index dataset is developed and used to assess the spatial extent of droughts in South Africa for the period 1920–2014. The most extensive droughts over the period at various time scales are identified and discussed. Results of a wavelet analysis are also presented towards identifying statistically significant regional climate variation with which the occurrence of droughts is associated. The occurrence of drought with respect to the El Niño Southern Oscillation and decadal climate variability is also considered. Significant associations between short-term droughts and decadal variability are pointed out. An overview of global sea surface temperature and Southern Hemisphere sea-level pressure associations with three prominent scales of multi-year climate variability is given. Dry epochs at the most prominent time scales are shown to be significantly negatively related to the Southern Annular Mode and associated sea surface temperature anomalies in the mid-to-high southern latitudes. Relations with the Pacific Decadal Oscillation, Inter-Decadal Pacific Oscillation and ENSO, which are all associated with a Southern Annular Mode of opposite sign, are also highlighted.

Geology↗
DOE OSTI2019

Multi-scale fusion algorithm of intensity and polarization-difference images based on edge information enhancement

To better integrate complementary and redundant information from different source images, improve the edge information, and facilitate the target detection. A multi-scale fusion algorithm of intensity and polarization-difference (PD) images based on edge information enhancement is proposed. Firstly, intensity images are obtained by the polarization information analysis method. PD images are obtained by the adaptive polarization-difference imaging approach based on the principle of minimum mutual information. Secondly, guided filter, affine transformations and Block-Matching and 3D filtering are embedded in visibility enhancement to improve the intensity and PD images. Thirdly, the two images are decomposed into high-frequency and low-frequency images by the dual-tree complex wavelet transform (DT-CWT). The high-frequency and low-frequency images are fused by the fusion rules based on edge detection and the regional variance matching degree respectively. Finally, the fusion image is obtained by the inverse DT-CWT. Experimental results demonstrate that fusion images of the proposed algorithm are significantly improved in information entropy, average gradient, and spatial frequency. Compared with the existing methods, it can achieve a better edge enhancement for images in a turbid medium.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Elastic Scattering of Ultrashort Laser Pulses on Noble Gas Atoms

The work deals with a theoretical investigation of elastic scattering of ultrashort electromagnetic pulses (USP) on the noble gas atoms in the far ultra-violet and soft X-ray regions. The investigation is performed within the framework of a dipole approximation and the first-order quantum-mechanics perturbation theory. Major attention is given to the study of the dependence of the total probability of scattering within the pulse time on the USP duration at different carrying frequency values. It is shown that at certain values of the problem parameters this dependence is nonlinear. The calculations are performed for the corrected Gaussian pulses and wavelet pulses without the carrying frequency.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Crack Detection in High-Velocity Oxygen-Fuel-Sprayed Al{sub 59.2}Cu{sub 25.5}Fe{sub 12.3}B{sub 3} Quasicrystalline Coatings Using Piezoelectric Active Sensors

Quasicrystals have received some attention in recent years regarding their potential usefulness as low friction and wear resistant materials. When quasicrystalline (QC) coatings are exposed to different levels of external loading or are subjected to thermal stresses, crack nucleation, and propagation become life-limiting factors. In this investigation, Al{sub 59.2}Cu{sub 25.5}Fe{sub 12.3}B{sub 3} QC coatings were deposited onto AISI-A36 steel substrates using the high-velocity oxygen-fuel (HVOF) technique. The coatings were deposited at different oxygen-to-fuel ratios. To characterize the integrity of the coatings, the active piezoceramic excitation technique was applied to detect the propagation of cracks during three-point bending tests. The piezoelectric transducer signal was processed using wavelet transformation analysis. The results revealed that the coated samples displayed different densities of cracks depending on the oxygen-to-fuel. The crack density was found higher for coatings formed using a slightly oxidizing flame. The opening of the pre-existing cracks in the coating was the main reason of signal attenuation during piezoelectric excitation. The HVOF-sprayed AlCuFeB quasicrystalline coating, with thickness between 150 and 180 μm, withstands a flexural stress as high as 340 MPa. To the best of our knowledge, this study is the first that provides a quantitative assessment of the viability of QC coatings in mechanical applications in spite of their intrinsic brittleness.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Tidal-Fluvial and Estuarine Processes in the Lower Columbia River: I. Along-channel Water Level Variations, Pacific Ocean to Bonneville Dam

This two-part paper provides comprehensive time and frequency domain analyses and models of along-channel water level variations in the 234km-long Lower Columbia River and Estuary (LCRE) and documents the response of floodplain wetlands thereto. In Part I, power spectra, continuous wavelet transforms, and harmonic analyses are used to understand the influences of tides, river flow, upwelling and downwelling, and hydropower operations ("power-peaking") on the water level regime. Estuarine water levels are influenced primarily by astronomical tides and coastal processes, and secondarily by river flow. The importance of coastal and tidal influences decreases in the landward direction, and water levels are increasingly controlled by river flow variations at periods from ≤1 day to years. Water level records are only slightly non-stationary near the ocean, but become increasingly irregular upriver. Although astronomically forced tidal constituents decrease above the estuary, tidal fortnightly and overtide variations increase for 80-200km landward, both relative to major tidal constituents and in absolute terms.

Jay, D. A.↗
DOE OSTI2018

Numerical multi-scaling method to solve the linear stochastic partial differential equations

In this paper, we propose a multi-scaling method to solve a class of the stochastic partial differential equations (SPDEs) of Itô-type. By this method, we approximate the solution of the SPDEs with strongly elliptic operator on a finite domain. The method is based on B-spline wavelet approximations; some of these functions are reshaped to satisfy on boundary conditions exactly. We prove the consistency and stability of the method. Illustrative examples are included to demonstrate the validity and applicability of our proposed technique.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Integral quantizations with two basic examples

The paper concerns integral quantization, a procedure based on operator-valued measure and resolution of the identity. We insist on covariance properties in the important case where group representation theory is involved. We also insist on the inherent probabilistic aspects of this classical–quantum map. The approach includes and generalizes coherent state quantization. Two applications based on group representation are carried out. The first one concerns the Weyl–Heisenberg group and the euclidean plane viewed as the corresponding phase space. We show that a world of quantizations exist, which yield the canonical commutation rule and the usual quantum spectrum of the harmonic oscillator. The second one concerns the affine group of the real line and gives rise to an interesting regularization of the dilation origin in the half-plane viewed as the corresponding phase space. -- Highlights: •Original approach to quantization based on (positive) operator-valued measures. •Includes Berezin–Klauder–Toeplitz and Weyl–Wigner quantizations. •Infinitely many such quantizations produce canonical commutation rule. •Set of objects to be quantized is enlarged in order to include singular functions or distributions. •Are given illuminating examples like quantum angle and affine or wavelet quantization.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Multiresolution classification of turbulence features in image data through machine learning

During large-scale simulations, intermediate data products such as image databases have become popular due to their low relative storage cost and fast in-situ analysis. Serving as a form of data reduction, these image databases have become more acceptable to perform data analysis on. In this work, we present an image-space detection and classification system for extracting vortices at multiple scales through wavelet-based filtering. A custom image-space descriptor is used to encode a large variety of vortex-types and a machine learning system is trained for fast classification of vortex regions. By combining a radial-based histogram descriptor, a bag of visual words feature descriptor, and a support vector machine, our results show that we are able to detect and classify vortex features at various sizes at multiple scales. Once trained, our framework enables the fast extraction of vortices on new, unknown image datasets for flow analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A particle resolved simulation approach for studying shock interactions with moving, colliding solid particles

This work applies a new combination of techniques for the fully resolved simulation of compressible, gas–particle multiphase flows. Here, the adaptive wavelet collocation method is used to dynamically, and efficiently, adapt the computational grid to localized flow features and the particles. A characteristic-based volume penalization method that imposes arbitrary Dirichlet, Neumann, or Robin-type immersed boundary conditions, is used to enforce the no-slip condition at particle surfaces. A hard-sphere collision model is applied to capture the particle–particle collisions. Proof of concept test cases are presented, showcasing the dynamic grid adaptation and fully resolved two-way coupling between the phases that is possible with this approach. Results for a shock-driven single cylinder under viscous and inviscid conditions are presented along with a demonstration of a shock interacting with a cloud of randomly distributed cylinders and spheres.

42 ENGINEERING↗
DOE OSTI2013

Confinement effects of solvation on a molecule physisorbed on a polarizable continuum particle

We investigate the effects of solvation on the static properties of a molecule physisorbed on a spherical polarizable continuum particle, with a static dielectric constant. The effective polarizability of the physisorbed molecule is enhanced by a factor of 105 in vacuo and by only 102 when solvated. The electrostatic interaction between molecules and the polarizable continuum particle (PCP) results in a magnified reflected electric field with a magnitude that depends on the PCP-molecule separation. A similar and greater magnification effect in reflected field also results from the PCP-field (external electric field) interaction. The variation of the polarizability of the molecules with respect to the changes in their environment illustrates the importance of electrostatic interaction in the enhancement of the effective polarizability. In the course of the investigation, the solute and the continuous body are represented with the same adaptive multi-wavelet basis functions, thereby, within the user specified precision, eliminating basis set error.

Chemistry↗