Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “High dimensional data,”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Synthesis of regional crust and upper-mantle structure from seismic and gravity data

Available seismic and ground based gravity data are combined to infer the three dimensional crust and upper mantle structure in selected regions. This synthesis and interpretation proceeds from large-scale average models suitable for early comparison with high-altitude satellite potential field data to more detailed delineation of structural boundaries and other variations that may be significant in natural resource assessment. Seismic and ground based gravity data are the primary focal point, but other relevant information (e.g. magnetic field, heat flow, Landsat imagery, geodetic leveling, and natural resources maps) is used to constrain the structure inferred and to assist in defining structural domains and boundaries. The seismic data consists of regional refraction lines, limited reflection coverage, surface wave dispersion, teleseismic P and S wave delay times, anelastic absorption, and regional seismicity patterns. The gravity data base consists of available point gravity determinations for the areas considered.

Alexander, S. S.↗
NASA NTRS1992

Turbulence measurements of high shear flow fields in a turbomachine seal configuration

The mean velocity and Reynolds stress tensor throughout a whirling annular seal are presented. The data was collected with a three dimensional laser Doppler velocimeter using phase averaging. Two axial flow conditions (Re = 12,000 and 24,000) were studied at one shaft speed (Ta = 6,600). The eccentricity and whirl ratios were 50 and 100 percent, respectively. There is a region of high axial momentum in this region is higher in the low Reynolds number case due to an axial recirculation zone that occurs on the suction side of the rotor at the inlet. The recirculation zone does not occur in the high Reynolds number case. At both Reynolds numbers, there is a recirculation zone on the rotor surface in the pressure side of the inlet. This recirculation zone extends from 20 to 200 degrees rotor zenith in the tangential direction, and is one third of a clearance wide radially. The high Reynolds number recirculation zone is 1.5 mean clearances long, while the low Reynolds number zone extends 2 mean clearances downstream. When compared to previous studies, it is apparent that the tangential momentum is no greater for a seal with whirl than for one without if other parameters are constant. Areas of high tangential momentum occur in the clearance where the axial momentum is low. Average exit plane tangential velocities in the high Reynolds number case are 1.5 times greater than those in the other flow case. These results are in general agreement with predictions made by other investigators.

Morrison, Gerald L.↗
NASA NTRS1987

Application of Advanced Very High Resolution Radiometer vegetation index to study atmosphere-biosphere exchange of CO2

Normalized difference vegetation indices derived from radiances measured by the Advanced Very High Resolution Radiometer were used to prescribe the phasing of terrestrial photosynthesis. The satellite data were combined with field data on soil respiration and a global map of net primary productivity to obtain the seasonal exchange of CO2 between the atmosphere and the terrestrial biosphere. The monthly fluxes of CO2 thus obtained were employed as source/sink functions in a global three-dimensional atmospheric tracer transport model to simulate the annual oscillations of CO2 in the atmosphere. The results demonstrate that satellite data of high spatial and temporal resolution can be used to provide quantitative information about seasonal and longer-term variations of photosynthetic activity on a global scale.

Fung, I. Y.↗
DOE OSTI2024

ML-based Data Assimilation and History Matching: Application to the IBDP CCS Project

It is crucial to monitor the CO2 plume effectively throughout the life cycle of a geologic CO2 sequestration project to ensure safety and storage efficiency. However, the computational cost of existing data assimilation methods can be prohibitively expensive due to the complex physics with multi-component non-isothermal simulation and high dimensionality of large-scale reservoir models. We address this challenge by proposing an accelerated deep learning-based workflow for model calibration and prediction of CO2 plume evolution in the reservoir.The power and efficacy of our workflow is demonstrated by application to the Illinois Basin-Decatur Project (IBDP), a large-scale CO2 storage test in saline aquifer. The data assimilation process is implemented rapidly by the proposed workflow with given field measurements including distributed pressure and temperature sensing (DTS) data at an injection and a monitoring well. CO2 plume evolution is predicted by running the simulations of the calibrated reservoir models.

Nagao, Masahiro↗
NASA NTRS1990

Model of the high-latitude ionospheric convection pattern during southward interplanetary magnetic field using DE 2 data

Data from the polar-orbiting satellite DE 2 are used to calculate one-dimensional electrostatic potential distributions across the polar cap region. Using passes that lie within + or - 3 hours MLT of the dawn-dusk line, various parameters of the polar potential distribution (location and magnitude of the maxima and minima, location of the zero potential point, etc.) are analyzed in relation to each other and to the IMF. The resulting dependences are used to derive a two-dimensional model of the distribution of the electrostatic potential in the high-latitude ionosphere during times of southward IMF. This model can be generated using as inputs either the ionospheric potential parameters or, based on the relationships analyzed here, the IMF conditions. The capabilities of the resulting mathematical model are illustrated, and the importance of retaining a flexibility in the model to accommodate individual observations is emphasized.

Hairston, M. R.↗
DOE OSTI2019

Cooperative Adsorption of Trehalose to DPPC Monolayers at the Water-Air Interface Studied with Vibrational Sum Frequency Generation

A combination of surface tension, surface-specific vibrational spectroscopy, and differential scanning calorimetry experiments were performed to examine the ability of lipid films to enrich interfacial organic content by attracting soluble, neutral saccharides from bulk aqueous solution. This “cooperative adsorption” hypothesis has been proposed as a possible source of the high organic fractions found in sea spray aerosols and is believed to be responsible for cryoprotection in some organisms. Experiments described in this work show that the neutral disaccharide trehalose (Tre) is drawn to lipid films comprised of dipalmitoylphosphatidylcholine (DPPC), a saturated lipid that is a major component of most eukaryotic cells. The effects of Tre on DPPC monolayer structure and organization were tested with tightly packed monolayers in the two-dimensional solid phase (40 Å2/molecule) and more expanded monolayers in the two dimensional liquid condensed phase (55 Å2/molecule). Surface tension data show that DPPC monolayer behaviour remains largely unchanged until Tre bulk concentrations are sufficiently high (= 50 mM). In contrast, surface specific vibrational sum frequency spectra show that when Tre bulk concentrations are = 10 mM, DPPC monolayers in their liquid condensed state (55 Å2/molecule) became more ordered, implying relatively strong noncovalent interactions between the two species. Tre also induces changes in DPPC bilayer behaviour as evidenced by a gel to liquid crystalline phase transition temperature that increases with increasing Tre concentration. This result suggests that Tre associates with the DPPC headgroups in very specific ways leading to partial dehydration. Together, these results support the cooperative adsorption mechanism under some circumstances, namely that there is a minimum aqueous phase Tre concentration required to induce observable structural changes in a lipid monolayer, and that these effects are most pronounced with DPPC monolayers in their liquid condensed state compared to a tightly packed 2-dimensional solid.

Link, Katie A.↗
NASA NTRS1980

Greenhouse models of Venus' high surface temperature, as constrained by Pioneer Venus measurements

Recent measurements conducted from the Pioneer Venus probes and orbiter have provided a significantly improved definition of the solar net flux profile, the gaseous composition, temperature structure, and cloud properties of Venus' lower atmosphere. Using these data, we have carried out a series of one-dimensional radiative-convective equilibrium calculations to determine the viability of the greenhouse model of Venus' high surface temperature and to assess the chief contributors to the greenhouse effect. New sources of infrared opacity include the permitted transitions of SO2, CO, and HCl as well as opacity due to several pressure-induced transitions of CO2. We find that the observed surface temperature and lapse rate structure of the lower atmosphere can be reproduced quite closely with a greenhouse model that contains the water vapor abundance reported by the Venera spectrophotometer experiment. Thus the greenhouse effect can account for essentially all of Venus' high surface temperature. The prime sources of infrared opacity are, in order of importance, CO2, H2O, cloud particles, and SO2, with CO and HCl playing very minor roles.

Pollack, J. B.↗
DOE OSTI2025

Explainable AI for Multivariate Time Series Pattern Exploration: Latent Space Visual Analytics With Temporal Fusion Transformer and Variational Autoencoders in Power Grid Event Diagnosis

Detecting and analyzing complex patterns in multivariate time-series data is crucial for decision-making in urban and environmental system operations. However, challenges arise from the high dimensionality, intricate complexity, and interconnected nature of complex patterns, which hinder the understanding of their underlying physical processes. Existing AI methods often face limitations in interpretability, computational efficiency, and scalability, reducing their applicability in real-world scenarios. This paper proposes a novel visual analytics framework that integrates two generative AI models, Temporal Fusion Transformer (TFT) and Variational Autoencoders (VAEs), to reduce complex patterns into lower-dimensional latent spaces and visualize them in 2D using dimensionality reduction techniques such as PCA, t-SNE, and UMAP with DBSCAN. These visualizations, presented through coordinated and interactive views and tailored glyphs, enable intuitive exploration of complex multivariate temporal patterns, identifying patterns’ similarities and uncover their potential correlations for a better interpretability of the AI outputs. The framework is demonstrated through a case study on power grid signal data, where it identifies multi-label grid event signatures, including faults and anomalies with diverse root causes. Additionally, novel metrics and visualizations are introduced to validate the models and assess the performance, efficiency, and consistency of latent maps generated by VAE, which have been utilized in prior studies for latent space cartography and used as a benchmark in this study, and the emerging TFT architecture under various configurations. These analyses provide actionable insights for model parameter tuning and reliability improvements. Comparative results highlight that TFT achieves shorter run times and superior scalability to diverse time-series data shapes compared to VAE. This work advances fault diagnosis in multivariate time series, fostering explainable AI to support critical system operations.

Explainable AI↗
NASA NTRS1973

Application of phase-change technique to thin sections with heating on both surfaces

A numerical digital computer program was developed to calculate the heat-transfer coefficients for both sides of a one-dimensional finite slab subject to the boundary conditions ascribed to the phase-change coating heat-transfer technique. In a typical tunnel test situation where a thin wing was exposed to heating on both sides, the data reduction procedures for a semi-infinite slab gave heat-transfer coefficients as much as 375 percent too high on the side with the lowest heating. The results from the one-dimensional finite-slab procedure are presented in the form of correction factors to the solution for a semi-infinite slab in terms of parameters normally used with the phase-change heat-transfer technique. These correlations are not restricted to slab thickness or thermophysical properties and are easily used to obtain accurate data on thin model sections.

Hunt, J. L.↗
DOE OSTI2021

Deep Learning Classification of Cheatgrass Invasion in the Western United States Using Biophysical and Remote Sensing Data

Cheatgrass (Bromus tectorum) invasion is driving an emerging cycle of increased fire frequency and irreversible loss of wildlife habitat in the western US. Yet, detailed spatial information about its occurrence is still lacking for much of its presumably invaded range. Deep learning (DL) has demonstrated success for remote sensing applications but is less tested on more challenging tasks like identifying biological invasions using sub-pixel phenomena. We compare two DL architectures and the more conventional Random Forest and Logistic Regression methods to improve upon a previous effort to map cheatgrass occurrence at >2% canopy cover. High-dimensional sets of biophysical, MODIS, and Landsat-7 ETM+ predictor variables are also compared to evaluate different multi-modal data strategies. All model configurations improved results relative to the case study and accuracy generally improved by combining data from both sensors with biophysical data. Cheatgrass occurrence is mapped at 30 m ground sample distance (GSD) with an estimated 78.1% accuracy, compared to 250-m GSD and 71% map accuracy in the case study. Furthermore, DL is shown to be competitive with well-established machine learning methods in a limited data regime, suggesting it can be an effective tool for mapping biological invasions and more broadly for multi-modal remote sensing applications.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

HLPW-4/GMGW-3: Overview and Workshop Summary

The Fourth AIAA CFD High Lift Prediction Workshop and the Third Geometry and Mesh Generation Workshop were held collaboratively with the common goal of assessing the numerical prediction capability of current-generation computational fluid dynamics (CFD) technology for swept, medium/high-aspect-ratio wings in high-lift configurations. A key aspect of this joint endeavor was the use of Technology Focus Groups, an innovative new approach for workshops involving close collaboration between participants. These groups, which included both mesh generation and flow solver experts, worked to accelerate advancements for their particular methodologies by addressing key questions of importance {\em prior} to the workshop. The high-lift version of the NASA Common Research Model (CRM-HL) configuration was the focus of this workshop. Measured experimental wind tunnel data were available for comparison. The workshop also included a two-dimensional turbulence model verification exercise based on the CRM-HL wing shape. Altogether, 44 participants submitted a total of 184 data sets of CFD results. This paper provides a high-level summary of the results and conclusions from the workshop. Like at past workshops, fixed-grid Reynolds-averaged Navier-Stokes continued to be inaccurate and inconsistent for high lift. However, mesh adaptation definitively brought more consistency. Scale-resolving methods appeared most promising for predicting high-lift flow physics.

Christopher L Rumsey↗
DOE OSTI2023

Seeing the whole picture: Methods for getting the most from micro X-ray computed tomography of TRISO nuclear fuel particles

Tristructural isotropic (TRISO) coated fuel particles are a nuclear fuel form under extensive study for use in advanced nuclear reactor concepts. TRISO fuels are subjected to high temperature neutron irradiations and then examined to assess their performance by determining fission product retention and studying morphological changes. Micro X-ray computed tomography is one method of nondestructively studying the effects of TRISO performance. This work addresses the need for image processing to remove X-ray tomographic reconstruction artifacts that prevent the study of TRISO features, as the TRISO particles’ high Z kernel can introduce metal artifacts that degrade the image quality in the surrounding low Z coating layers. These metal artifacts were reduced by imaging the TRISO particles with both high- and low-energy X-rays and applying a mask to the radiographs obtained with low-energy X-rays to digitally remove the dense fuel kernel region. These masked radiographs were then used to produce a tomographic reconstruction which was combined with the tomographic reconstruction of the high-energy data. This enabled the relatively-low-density TRISO buffer layer to be examined in more detail, providing information on irradiation induced dimensional changes of the coatings. This methodology, which helps see the full picture of a TRISO particle, is not limited to nuclear fuels but can be applied to systems that contain highly attenuating material surrounded by less dense materials.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

High-resolution fully vectorial scanning Kerr magnetometer

We report on the development of a high-resolution scanning magnetometer, which fully exploits the vectorial nature of the magneto-optical Kerr effect. The three-dimensional nature of magnetization is at the basis of many micromagnetic phenomena and from these data, we can fully characterize magnetization processes of nanostructures in static and dynamic regimes. Our scanning Kerr magnetometer uses a high numerical aperture microscope objective where the incident light beam can be deterministically deviated from the objective symmetry axis, therefore, both in-plane (via the longitudinal Kerr effect) and out-of-plane (via the polar Kerr effect) components of the magnetization vector may be detected. These components are then separated by exploiting the symmetries of the polar and longitudinal Kerr effects. From four consecutive measurements, we are able to directly obtain the three orthogonal components of the magnetization vector with a resolution of 600 nm. Performance of the apparatus is demonstrated by a measurement of 3D magnetization vector maps showing out-of-plane domains and in-plane domain walls in an yttrium-iron-garnet film and on a study of magnetization reversal in a 4-μm-wide magnetic disk.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Strongly fluctuating moments in the high-temperature magnetic superconductor RbEuFe 4 As 4

The iron-based superconductor RbEuFe 4 As 4 undergoes a magnetic phase transition deep in the superconducting state. In this work, we investigate the calorimetric response of RbEuFe 4 As 4 single crystals of the magnetic and the superconducting phase and its anisotropy to in-plane and out-of-plane magnetic fields. Whereas the unusual cusplike anomaly associated with the magnetic transition is suppressed to lower temperatures for fields along the crystallographic c axis, it rapidly transforms to a broad shoulder shifting to higher temperatures for in-plane fields. We identify the cusp in the specific-heat data as a Berezinskii-Kosterlitz-Thouless transition with fine features caused by the three-dimensional effects. The high-temperature shoulder in high magnetic fields marks a crossover from a paramagnetically disordered to an ordered state. Lastly, this observation is further supported by Monte Carlo simulations of an easy-plane two-dimensional Heisenberg model and a fourth-order high-temperature expansion, both of which agree qualitatively and quantitatively with the experimental findings.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Chemistry imaging and distribution analysis of rare earth elements in coal using LIBS and LA-ICP-MS instruments

Currently, demand for rare earth elements (REEs) increased significantly. Coal is actively evaluated as potential economic sources for extraction of REEs. Here, in this work, laser-induced breakdown spectroscopy (LIBS) was evaluated for rapid estimation of REEs content and their distribution in the natural coal samples. The results were compared with similar laser ablation–inductively coupled plasma–mass spectrometry (LA-ICP-MS) measurements. Thirteen coal samples (nine standard samples and five natural samples) were used in this study. Powder samples were pressed into pellets while coal chunks were directly ablated for data recording. Pellets of the powder standard samples were used to optimize the data acquisition system and then data recorded with this optimized system was used to identify the proper data acquisition and analysis models. After establishing the proper data acquisition system and analysis model using the standard samples, natural coal samples in powder form and their chunks were utilized to record LIBS and LA-ICP-MS spectra. Multivariate calibration models were developed using four of the natural samples, which were evaluated by predicting the REE content in the fifth sample. Principal component analysis was performed on the LIBS data obtained from the natural samples and it classified all the samples with high accuracy. Two-dimensional (2D) elemental mapping on coal chunk samples was also performed using both LIBS and LA-ICP-MS to study the distribution of REEs in the samples. The resulting elemental images and their correlations can be used to infer mineral distributions.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Coarse-Graining Conformational Dynamics with Multidimensional Generalized Langevin Equation: How, When, and Why

A data-driven ab initio generalized Langevin equation (AIGLE) approach is developed to learn and simulate high-dimensional, heterogeneous, coarse-grained (CG) conformational dynamics. Constrained by the fluctuation–dissipation theorem, the approach can build CG models in dynamical consistency (DC) with all-atom molecular dynamics. Here, we also propose practical criteria for AIGLE to enforce long-term DC. Case studies of a toy polymer, with 20 CG sites, and the alanine dipeptide, with two dihedral angles, elucidate why one should adopt AIGLE or its Markovian limit for modeling CG conformational dynamics in practice.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Quantitative impact characterization of aeronautical CFRP materials with non-destructive testing methods

In recent years, an increasing number of safety-relevant structures are designed and manufactured from carbon fiber reinforced polymers (CFRP) in order to reduce weight of airplanes by taking the advantage of their specific strength into account. Non-destructive testing (NDT) methods for quantitative defect analysis of damages are liquid- or air-coupled ultrasonic testing (UT), phased array ultrasonic techniques, and active thermography (IR). The advantage of these testing methods is the applicability on large areas. However, their quantitative information is often limited on impact localization and size. In addition to these techniques, Airbus Group Innovations operates a micro x-ray computed tomography (μ-XCT) system, which was developed for CFRP characterization. It is an open system which allows different kinds of acquisition, reconstruction, and data evaluation. One main advantage of this μ-XCT system is its high resolution with 3-dimensional analysis and visualization opportunities, which enables to gain important quantitative information for composite part design and stress analysis. Within this study, different NDT methods will be compared at CFRP samples with specified artificial impact damages. The results can be used to select the most suitable NDT-method for specific application cases. Furthermore, novel evaluation and visualization methods for impact analyzes are developed and will be presented.

42 ENGINEERING↗
DOE OSTI2022

Orbital-induced crossover of the Fulde-Ferrell-Larkin-Ovchinnikov phase into Abrikosov-like states.

The Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) state can emerge in superconductors for which the orbital critical field exceeds the Pauli limit. Here, we present angular-resolved specific-heat data of the quasi-two-dimensional organic superconductor ??-(ET)2Cu(NCS )2 , with a focus on high fields in the regime of the FFLO transition. For an increasing out-of-plane tilt of the applied magnetic field, which leads to an increase of orbital contributions, we found that the nature of the superconducting transition changes from second to first order and that a further transition appears within the high-field superconducting phase. However, the superconducting state above the Pauli limit is stable for field tilt of several degrees. Since any finite perpendicular component of the magnetic field necessarily leads to quantization of the orbital motion, the resulting vortex lattice states compete with the modulated order parameter of the FFLO state leading to complex high-field superconducting phases. By solving the linearized self-consistency equation within weak-coupling BCS theory, we show that our results are clear experimental evidence of an orbital-induced transformation of the FFLO order parameter into Abrikosov-like states of higher Landau levels.

Kotte, Tommy↗