Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Functional data analysis”

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 577 records · Page 32

Determination of a Two-Phase Structure of Nanocrystals: GaN and SiC

The properties of nano-crystalline materials are critically dependent on the structure of the constituent grains. Experimental conditions necessary to perform structural analysis of nanocrystalline materials as a two-phase core-surface shell system are discussed. It is shown, that a standard X-ray diffraction measurements and analysis are insufficient and may lead to incorrect conclusions as to the real structure of the materials. A new method of evaluation of powder diffraction data based on the analysis of the shift of the Bragg reflections from their perfect-lattice positions was developed. "Apparent lattice parameters" quantity, alp, was introduced and calculated from the actual positions of each individual Bragg reflection. The alp values plotted versus diffraction vector (Q) show characteristic features that are used for evaluation of the experimental results. The study was based on modeling of nano-grains and simulations of theoretical intensity profiles using the Debye functions. The method was applied to the analysis of synchrotron X-ray diffraction data of GaN and SiC nanocrystals. A presence of strained surface shell and a considerable internal pressure (GaN) in the nanoparticles was concluded.

Palosz, W.↗

The growth, propagation and decay of global scale Rossby waves during FGGE

A portrait of the evolution of global scale Rossby waves for the FGGE year is presented. Emphasis is placed on the temporal evolution of the amplitude and phase of Hough mode projections, rather than on characteristics of the time spectra of these waves. On the basis of previous work, it was felt that it would be adequate to consider the 500 mb level in isolation from the others, and that the Hough functions (which are vector functions of the horizontal wind components and the height field) were good approximations to the "true' eigenfunctions. Thus, the first steps of the analysis consisted of projecting the 500 mb height and wind data (obtained from the ECMWF analyses) onto Hough functions for each synoptic time. The seasonal cycle and time mean were removed separately for each season, and all remaining eastward propagating components removed on a seasonal basis; all remaining westward propagating components were retained.

Lindzen, R. S.↗

GIScience in the era of Artificial Intelligence: a research agenda towards Autonomous GIS

The advent of generative AI exemplified by large language models (LLMs) opens new ways to represent and compute geographic information and transcends the process of geographic knowledge production, driving geographic information systems (GIS) towards autonomous GIS. Leveraging LLMs as the decision core, autonomous GIS can independently generate and execute geoprocessing workflows to perform spatial analysis. In this vision paper, we further elaborate on the concept of autonomous GIS and present a conceptual framework that defines its five autonomous goals, five levels of autonomy, five core functions, and three operational scales. We demonstrate how autonomous GIS could perform geospatial data retrieval, spatial analysis, and map making with four proof-of-concept GIS agents. We conclude by identifying critical challenges and future research directions, including fine-tuning and self-growing decision-cores, autonomous modelling, and examining the societal and practical implications of autonomous GIS. By establishing the groundwork for a paradigm shift in GIScience, this paper envisions a future where GIS moves beyond traditional workflows to autonomously reason, derive, innovate, and advance geospatial solutions to pressing global challenges. Meanwhile, we emphasize that as we design and deploy increasingly intelligent geospatial systems, we carry a responsibility to ensure they are developed in socially responsible ways, serve the public good, and support the continued value of human geographic insight in an AI-augmented future.

Autonomous GI↗

Impedance Scan of Inverter-Based Resources and Diesel Generator for Stability Analysis

Impedance-based methods are widely used for power system stability analysis with inverter-based resources (IBRs), e.g., assessing dynamic interactions between the power grid and an IBR, control interactions between multiple IBRs, and the sub-synchronous oscillation and damping phenomenon. Since it is difficult to get a numerical model 100% matching with the hardware IBR, using the hardware inverter directly to obtain its output impedance has become a prominent approach nowadays. Therefore, this article presents the impedance scan using hardware IBRs, and also a hardware diesel generator as it still stays with the grid before the grid completely goes to renewable. The devices under test (DuTs) for the impedance scan includes two 3-..phi.., 480 V, 60 Hz commercial grid-forming IBRs (one of 250 kVA and another of 125 kVA rating) in series with ..delta..-Y transformers, one 3-..phi.., 480 V, 60 Hz commercial grid-following IBR (of 125 kVA rating), and a 3-..phi.., 480 V, 60 Hz commercial diesel generator (of 187.5 kVA rating). Using voltage signals perturbed with sub-, inter-, and higher harmonic components, and measuring the current response, the positive-sequence impedances are computed via an offline-based post-analysis. Moreover, best-fit transfer functions are estimated that closely resemble the measured data points of the positive-sequence impedances. Based on the observations from various outcomes of the hardware experiments, this article also provides some fundamental insights on the equivalent positive-sequence impedance of a combination of multiple hardware components by comparing the estimated and the empirically computed impedances. A comparative insight on the damping capability of the DuTs using the positive-sequence impedances of the hardware is also discussed.

current measurement↗

Windowing artefacts likely account for recent claimed detection of oscillating cosmic scale factor

ABSTRACT Using the Pantheon data set of Type Ia supernovae, a recent publication (R20 in this work) reports a 2σ detection of oscillations in the expansion history of the Universe. The study conducted by R20 is wholly worthwhile. However, we demonstrate that there is a $\gt 10{{\ \rm per\ cent}}$ chance of statistical fluctuations in the Pantheon data producing a false oscillatory signal larger than the oscillatory signal that R20 report. Their results are a less than 2σ detection. Applying the R20 methodology to simulated Pantheon data, we determine that these oscillations could arise due to analysis artefacts. The uneven spacing of Type Ia supernovae in redshift space and the complicated analysis method of R20 impose a structured throughput function. When analysed with the R20 prescription, about $11{{\ \rm per\ cent}}$ of artificial ΛCDM data sets produce a stronger oscillatory signal than the actual Pantheon data. Our results underscore the importance of understanding the false ‘signals’ that can be introduced by complicated data analyses.

79 ASTRONOMY AND ASTROPHYSICS↗

DYNC1H1 regulates NSCLC cell growth and metastasis by IFN-γ-JAK-STAT signaling and is associated with an aberrant immune response

Highlights: • DYNC1H1 is upregulated and its high expression predicted poor outcomes in NSCLC. • Loss of function of DYNC1H1 inhibits cell growth and metastasis of NSCLC cells in vitro. • DYNC1H1 knockdown inhibited metastasis of NSCLC cells in vivo. • DYNC1H1 loss of function suppresses IFN-γ-JAK-STAT signaling pathway in NSCLC. • DYNC1H1 expression is correlated with aberrant immune response in NSCLC indicated by analysis of TCGA immune data. It is urgent to identify new biomarkers and therapeutic targets to ameliorate the clinical prognosis of patients with lung cancer. The functional significance and molecular mechanism of dynein cytoplasmic 1 heavy chain 1 (DYNC1H1) in nonsmall cell lung cancer (NSCLC) progression is still elusive. In our current study, publicly available data and Western blotting experiments confirmed that DYNC1H1 expression was upregulated in lung cancer samples compared with noncancerous samples. Quantitative real-time PCR (qPCR) results indicated that high DYNC1H1 expression in lung cancer tissues was significantly associated with clinical tumor stage and distal metastasis; moreover, its high expression was negatively correlated with prognosis. Functional experiments demonstrated that DYNC1H1 loss of function caused a significant decrease in cell viability and cell proliferative ability, inhibition of the cell cycle, and promotion of both migration potential and invasion potential in vitro. Animal experiments by tail vein injection of lung cancer cells showed that DYNC1H1 knockdown significantly decreased lung cancer metastasis. Mechanistically, the results from a human protein array showed changes in the IFN-γ-JAK-STAT signaling pathway, and analysis of The Cancer Genome Atlas (TCGA) immune data demonstrated that disturbance of the immune microenvironment might be involved in the impaired growth and metastatic ability mediated by DYNC1H1 loss in NSCLC. DYNC1H1 might serve as a promising biological marker of prognosis and a potential clinical therapeutic target for patients with NSCLC.

60 APPLIED LIFE SCIENCES↗

IDE spatio-temporal impact fluxes and high time-resolution studies of multi-impact events and long-lived debris clouds

During the first 12 months of the Long Duration Exposure Facility (LDEF) mission, the Interplanetary Dust Experiment (IDE) recorded over 15,000 total impacts on six orthogonal faces with a time resolution on the order of 15 to 20 seconds. When combined with the orbital data and the stabilized configuration of the spacecraft, this permits a detailed analysis of the micro-particulate environment. The functional status of each of the 459 detectors was monitored every 2.4 hours, and post-flight analyses of these data has now permitted an evaluation of the effective active detection area as a function of time, panel by panel and separately for the two sensitivity levels. Thus, total impacts were transformed into areal fluxes, and are presented here for the first time. Also discussed are possible effects of these fluxes on previously announced results: apparent debris events, meteor stream detections, and beta meteoroids in observationally significant numbers.

Mulholland, J. Derral↗

Identification and correction of temporal and spatial distortions in scanning transmission electron microscopy

Scanning transmission electron microscopy (STEM) has become the technique of choice for quantitative characterization of atomic structure of materials, where the minute displacements of atomic columns from high-symmetry positions can be used to map strain, polarization, octahedra tilts, and other physical and chemical order parameter fields. The latter can be used as inputs into mesoscopic and atomistic models, providing insight into the correlative relationships and generative physics of materials on the atomic level. However, these quantitative applications of STEM necessitate understanding the microscope induced image distortions and developing the pathways to compensate them both as part of a rapid calibration procedure for in situ imaging, and the post-experimental data analysis stage. Here, we explore the spatiotemporal structure of the microscopic distortions in STEM using multivariate analysis of the atomic trajectories in the image stacks. Based on the behavior of principal component analysis (PCA), we develop the Gaussian process (GP)-based regression method for quantification of the distortion function. The limitations of such an approach and possible strategies for implementation as a part of in-line data acquisition in STEM are discussed. Here, the analysis workflow is summarized in a Jupyter notebook that can be used to retrace the analysis and analyze the reader's data.

36 MATERIALS SCIENCE↗

Narrow bandgap semiconducting silicides: Intrinsic infrared detectors on a silicon chip

Polycrystalline thin films of CrSi2, LaSi2, and ReSi2 were grown on silicon substrates. Normal incidence optical transmittance and reflectance measurements were made as a function of wavelength. It was demonstrated that LaSi2 is a metallic conductor, but that CrSi2 and ReSi2 are, in fact, narrow bandgap semiconductors. For CrSi2, the complex index of refraction was determined by computer analysis of the optical data. From the imaginary part, the optical absorption coefficient was determined as a function of photon energy. It was shown that CrSi2 possesses an indirect forbidden energy gap of slightly less than 0.31 eV, and yet it is a very strong absorber of light above the absorption edge. On the other hand, the ReSi2 films exhibit an absorption edge in the vicinity of 0.2 eV. Measurements of the thermal activation energy of resistivity for ReSi2 indicate a bandgap of 0.18 eV. It is concluded that the semiconducting silicides merit further investigation for development as new silicon-compatible infrared detector materials.

Mahan, John E.↗

NASTRAN variance analysis and plotting of HBDY elements

The NASTRAN Thermal Analyzer has been intended to do variance analysis and plot the thermal boundary elements. The objective of the variance analysis addition is to assess the sensitivity of temperature variances resulting from uncertainties inherent in input parameters for heat conduction analysis. The plotting capability provides the ability to check the geometry (location, size and orientation) of the boundary elements of a model in relation to the conduction elements. Variance analysis is the study of uncertainties of the computed results as a function of uncertainties of the input data. To study this problem using NASTRAN, a solution is made for both the expected values of all inputs, plus another solution for each uncertain variable. A variance analysis module subtracts the results to form derivatives, and then can determine the expected deviations of output quantities.

Harder, R. L.↗

Cluster analysis of multiple planetary flow regimes

A modified cluster analysis method was developed to identify spatial patterns of planetary flow regimes, and to study transitions between them. This method was applied first to a simple deterministic model and second to Northern Hemisphere (NH) 500 mb data. The dynamical model is governed by the fully-nonlinear, equivalent-barotropic vorticity equation on the sphere. Clusters of point in the model's phase space are associated with either a few persistent or with many transient events. Two stationary clusters have patterns similar to unstable stationary model solutions, zonal, or blocked. Transient clusters of wave trains serve as way stations between the stationary ones. For the NH data, cluster analysis was performed in the subspace of the first seven empirical orthogonal functions (EOFs). Stationary clusters are found in the low-frequency band of more than 10 days, and transient clusters in the bandpass frequency window between 2.5 and 6 days. In the low-frequency band three pairs of clusters determine, respectively, EOFs 1, 2, and 3. They exhibit well-known regional features, such as blocking, the Pacific/North American (PNA) pattern and wave trains. Both model and low-pass data show strong bimodality. Clusters in the bandpass window show wave-train patterns in the two jet exit regions. They are related, as in the model, to transitions between stationary clusters.

Mo, Kingtse↗

Parametric Analysis of Surveillance Quality and Level and Quality of Intent Information and Their Impact on Conflict Detection Performance

A loss-of-separation (LOS) is said to occur when two aircraft are spatially too close to one another. A LOS is the fundamental unsafe event to be avoided in air traffic management and conflict detection (CD) is the function that attempts to predict these LOS events. In general, the effectiveness of conflict detection relates to the overall safety and performance of an air traffic management concept. An abstract, parametric analysis was conducted to investigate the impact of surveillance quality, level of intent information, and quality of intent information on conflict detection performance. The data collected in this analysis can be used to estimate the conflict detection performance under alternative future scenarios or alternative allocations of the conflict detection function, based on the quality of the surveillance and intent information under those conditions.Alternatively, this data could also be used to estimate the surveillance and intent information quality required to achieve some desired CD performance as part of the design of a new separation assurance system.

Guerreiro, Nelson M.↗

Effective Materials Property Information Management for the 21st Century

This paper discusses key principles for the development of materials property information management software systems. There are growing needs for automated materials information management in various organizations. In part these are fueled by the demands for higher efficiency in material testing, product design and engineering analysis. But equally important, organizations are being driven by the need for consistency, quality and traceability of data, as well as control of access to sensitive information such as proprietary data. Further, the use of increasingly sophisticated nonlinear, anisotropic and multi-scale engineering analyses requires both processing of large volumes of test data for development of constitutive models and complex materials data input for Computer-Aided Engineering (CAE) software. And finally, the globalization of economy often generates great needs for sharing a single "gold source" of materials information between members of global engineering teams in extended supply chains. Fortunately, material property management systems have kept pace with the growing user demands and evolved to versatile data management systems that can be customized to specific user needs. The more sophisticated of these provide facilities for: (i) data management functions such as access, version, and quality controls; (ii) a wide range of data import, export and analysis capabilities; (iii) data "pedigree" traceability mechanisms; (iv) data searching, reporting and viewing tools; and (v) access to the information via a wide range of interfaces. In this paper the important requirements for advanced material data management systems, future challenges and opportunities such as automated error checking, data quality characterization, identification of gaps in datasets, as well as functionalities and business models to fuel database growth and maintenance are discussed.

Ren, Weiju↗

Assessment of Local Observation of Atomic Ordering in Alloys via the Radial Distribution Function: A Computational and Experimental Approach

As a powerful analytical technique, atom probe tomography (APT) has the capacity to acquire the spatial distribution of millions of atoms from a complex sample. However, extracting information at the Ångstrom-scale on atomic ordering remains a challenge due to the limits of the APT experiment and data analysis algorithms. The development of new computational tools enable visualization of the data and aid understanding of the physical phenomena such as disorder of complex crystalline structures. Here, we report progress towards this goal using two steps. We describe a computational approach to evaluate atomic ordering in the crystal structure by generating radial distribution functions (RDF). Atomic ordering is rendered as the Fractional Cumulative Radial Distribution Function (FCRDF) which allows for greater visibility of local compositions at short range in the structure. Further, we accommodate in the analysis additional parameters such as uncertainty in the atomic coordinates and the atomic abundance to ascertain short-range ordering in APT data sets. We applied the FCRDF analysis to synthetic and experimental APT data sets for Ni 3 Al. The ability to observe a signal of atomic ordering consistent with the known L1 2 crystal structure is heavily dependent on spatial uncertainty, irrespective of abundance. Detection of atomic ordering is subject to an upper limit of spatial uncertainty of atoms described with Gaussian distributions with a standard deviation of 1.3 Å. The FCRDF analysis was also applied to the APT data set for a six-component alloy, Al 1.3 CoCrCuFeNi. In this case, we are currently able to visualize elemental segregation at the nanoscale, though unambiguous identification of atomic ordering at the Ångstrom (nearest-neighbor) scale remains a goal.

36 MATERIALS SCIENCE↗

Evaluation of space shuttle main engine fluid dynamic frequency response characteristics

In order to determine the POGO stability characteristics of the space shuttle main engine liquid oxygen (LOX) system, the fluid dynamic frequency response functions between elements in the SSME LOX system was evaluated, both analytically and experimentally. For the experimental data evaluation, a software package was written for the Hewlett-Packard 5451C Fourier analyzer. The POGO analysis software is documented and consists of five separate segments. Each segment is stored on the 5451C disc as an individual program and performs its own unique function. Two separate data reduction methods, a signal calibration, coherence or pulser signal based frequency response function blanking, and automatic plotting features are included in the program. The 5451C allows variable parameter transfer from program to program. This feature is used to advantage and requires only minimal user interface during the data reduction process. Experimental results are included and compared with the analytical predictions in order to adjust the general model and arrive at a realistic simulation of the POGO characteristics.

Gardner, T. G.↗

MOSAIC: a joint modeling methodology for combined circadian and non-circadian analysis of multi-omics data

Abstract Motivation Circadian rhythms are approximately 24-h endogenous cycles that control many biological functions. To identify these rhythms, biological samples are taken over circadian time and analyzed using a single omics type, such as transcriptomics or proteomics. By comparing data from these single omics approaches, it has been shown that transcriptional rhythms are not necessarily conserved at the protein level, implying extensive circadian post-transcriptional regulation. However, as proteomics methods are known to be noisier than transcriptomic methods, this suggests that previously identified arrhythmic proteins with rhythmic transcripts could have been missed due to noise and may not be due to post-transcriptional regulation. Results To determine if one can use information from less-noisy transcriptomic data to inform rhythms in more-noisy proteomic data, and thus more accurately identify rhythms in the proteome, we have created the Multi-Omics Selection with Amplitude Independent Criteria (MOSAIC) application. MOSAIC combines model selection and joint modeling of multiple omics types to recover significant circadian and non-circadian trends. Using both synthetic data and proteomic data from Neurospora crassa, we showed that MOSAIC accurately recovers circadian rhythms at higher rates in not only the proteome but the transcriptome as well, outperforming existing methods for rhythm identification. In addition, by quantifying non-circadian trends in addition to circadian trends in data, our methodology allowed for the recognition of the diversity of circadian regulation as compared to non-circadian regulation. Availability and implementation MOSAIC’s full interface is available at https://github.com/delosh653/MOSAIC. An R package for this functionality, mosaic.find, can be downloaded at https://CRAN.R-project.org/package=mosaic.find. Supplementary information Supplementary data are available at Bioinformatics online.

De los Santos, Hannah↗

Dynamics explorer data analysis

Work in the following areas is discussed: plasma physics of the auroral acceleration region; electrodynamic coupling as a function of substorm phase and interplanetary magnetic field (IMF) direction; and particle injection in the magnetospheric cusp.

Reiff, Patricia H.↗

Application of a Chemical Index to Aerosol Mass Spectrometry: Delta Plots and Functional Group Distributions

A better understanding of the chemical properties of organic aerosol (OA) particles will improve our ability to characterize their sources and predict their lifetime. The high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) is widely used to measure OA in real time using thermal vaporization followed by electron ionization (EI). EI creates fragment ions that can be assigned to functional groups using delta analysis, a method of classifying mass spectra according to the presence of different chemically related ion series. In this study, we demonstrate the application of delta analysis to characterize molecular structures using a new visualization method. We also use delta analysis to quantify the functional group distribution with an average absolute error of ∼5–6% for individual standard molecules, comparable to the error observed for OA mixtures from biomass and coal combustion fit with Fourier transform infrared spectroscopy. Finally, we apply delta functional group analysis to AMS positive matrix factorization (PMF) factors across seven different field campaigns and find a similar composition across the more oxidized factors with about 55% acid and 26% alcohol groups. The analysis method described here can be applied to any HR-ToF-AMS data set to provide quantitative relative functional group distributions for OA mixtures.

aerosol↗