SEARCH · Search NASA

Results for “Methods: 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.

SourceResearch connectionFrom yearThrough year

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

At least 109 records · Page 6

All sources NASA NTRS DOE OSTI

DOE OSTI2019

Standard methods for heat capacity measurements on a Quantum Design Physical Property Measurement System

The commercial availability of the Physical Property Measurement System (PPMS) by Quantum Design has significantly increased access to heat capacity measurements on a wide variety of materials. Although the PPMS can routinely measure the heat capacities of thermally conducting materials with high accuracy, specialized sample mounting techniques must be used for insulating powders, and the analysis of first order transitions also requires non-standard methods. The concern is that many users are not aware of these constraints when measuring the heat capacity of a diverse array of materials, and therefore, the heat capacity data reported in the literature can be unreliable. In this paper, we provide an extensive and critical review of the heat capacity data reported in the literature measured using the Quantum Design PPMS. The purpose is to provide a de facto standard for sample mounting and data analysis methods suitable for the reporting of accurate thermodynamic data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2013

BD+15 2940 AND HD 233604: TWO GIANTS WITH PLANETS CLOSE TO THE ENGULFMENT ZONE

We report the discovery of planetary-mass companions to two red giants by the ongoing Penn State-Torun Planet Search (PTPS) conducted with the 9.2 m Hobby-Eberly Telescope. The 1.1 M{sub Sun} K0-giant, BD+15 2940, has a 1.1 M{sub J} minimum mass companion orbiting the star at a 137.5 day period in a 0.54 AU orbit what makes it the closest-in planet around a giant and possible subject of engulfment as the consequence of stellar evolution. HD 233604, a 1.5 M{sub Sun} K5-giant, is orbited by a 6.6 M{sub J} minimum mass planet which has a period of 192 days and a semi-major axis of only 0.75 AU making it one of the least distant planets to a giant star. The chemical composition analysis of HD 233604 reveals a relatively high {sup 7}Li abundance which may be a sign of its early evolutionary stage or recent engulfment of another planet in the system. We also present independent detections of planetary-mass companions to HD 209458 and HD 88133, and stellar activity-induced radial velocity variations in HD 166435, as part of the discussion of the observing and data analysis methods used in the PTPS project.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

Pause sequences facilitate entry into long-lived paused states by reducing RNA polymerase transcription rates

Transcription by RNA polymerase (RNAP) is interspersed with sequence-dependent pausing. The processes through which paused states are accessed and stabilized occur at spatiotemporal scales beyond the resolution of previous methods, and are poorly understood. Here, we combine high-resolution optical trapping with improved data analysis methods to investigate the formation of paused states at enhanced temporal resolution. We find that pause sites reduce the forward transcription rate of nearly all RNAP molecules, rather than just affecting the subset of molecules that enter long-lived pauses. We propose that the reduced rates at pause sites allow time for the elongation complex to undergo conformational changes required to enter long-lived pauses. We also find that backtracking occurs stepwise, with states backtracked by at most one base pair forming quickly, and further backtracking occurring slowly. Finally, we find that nascent RNA structures act as modulators that either enhance or attenuate pausing, depending on the sequence context.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

PBjam: A Python Package for Automating Asteroseismology of Solar-like Oscillators

Asteroseismology is an exceptional tool for studying stars using the properties of observed modes of oscillation. So far the process of performing an asteroseismic analysis of a star has remained somewhat esoteric and inaccessible to nonexperts. In this software paper we describe PBjam, an open-source Python package for analyzing the frequency spectra of solar-like oscillators in a simple but principled and automated way. The aim of PBjam is to provide a set of easy-to-use tools to extract information about the radial and quadropole oscillations in stars that oscillate like the Sun, which may then be used to infer bulk properties such as stellar mass, radius, age, or even structure. Asteroseismology and its data analysis methods are becoming increasingly important as space-based photometric observatories are producing a wealth of new data, allowing asteroseismology to be applied in a wide range of contexts such as exoplanet, stellar structure and evolution, and Galactic population studies.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Reliable machine prognostic health management in the presence of missing data

Prognostics and health management enables the prediction of future degradation and remaining useful life (RUL) for in-service systems based on historical and contemporary data, showing promise for many practical applications. One major challenge for prognostics is the common occurrence of missing values in time-series data, often caused by disruptions in sensor communication or hardware/software failures. Another major concern is that the sufficient prior knowledge of critical component degradation with a clear failure threshold is often not readily available in practice. These issues can significantly hinder the application of advanced signal and data analysis methods and consequently degrade the health management performance. In this article, we propose a novel data-driven framework that is capable of providing accurate and reliable predictions of degradation and RUL. In this approach, one-hot health state indicators are appended to the historical time series so that the model learns end-of-life automatically. A modified gate recurrent unit based variational autoencoder is employed in generative adversarial networks to model the temporal irregularity of the incomplete time series. Furthermore, experiments on multivariate time-series datasets collected from real-world aeroengines verify that significant performance improvement can be achieved using the proposed model for robust long-term prognostics.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2015

Book Review: Reiner Salzer and Heinz W. Siesler (Eds.): Infrared and Raman spectroscopic imaging, 2nd ed.

This second edition of "Infrared and Raman Spectroscopic Imaging" propels practitioners in that wide-ranging field, as well as other readers, to the current state of the art in a well-produced and full-color, completely revised and updated, volume. This new edition chronicles the expanded application of vibrational spectroscopic imaging from yesterday's time-consuming point-by-point buildup of a hyperspectral image cube, through the improvements afforded by the addition of focal plane arrays and line scan imaging, to methods applicable beyond the diffraction limit, instructs the reader on the improved instrumentation and image and data analysis methods, and expounds on their application to fundamental biomedical knowledge, food and agricultural surveys, materials science, process and quality control, and many others.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2017

Using Receiver Operating Characteristic Curves to Optimize Discovery-Based Software with Comprehensive Two-Dimensional Gas Chromatography with Time-of-Flight Mass Spectrometry

We report a quantitative approach to optimize implementation of discovery-based software for comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC × GC – TOFMS). The software performs a tile-based Fisher ratio (F-ratio) analysis, and facilitates a supervised non-targeted analysis based upon the experimental design to aid in the discovery of analytes whose variances are statistically different between sample classes. The quantitative approach for software optimization uses receiver operating characteristic (ROC) curves. The area under the curve (AUC) of each ROC curve serves as a quantitative metric to optimize two key algorithm parameters: the signal-to-noise ratio (S/N) threshold of the baseline corrected and normalized data prior to calculating F-ratios at each m/z mass channel, and the number of these F-ratios per m/z to include in the calculation of the average F-ratio of a tile. A total of 25 combinations of S/N threshold by number of m/z were studied. Fifty analytes were spiked into a diesel fuel at two concentration spike levels to produce two sample classes that should in principle produce 50 positive instances in the ROC curves (30 native/20 non-native compounds, at spike levels of 200/20 and100/10 ppm native/non-native, respectively). The “sweet spot” for F-ratio analysis was determined to be a S/N threshold of 10 coupled with a maximum of the 10 most chemically selective m/z (requiring a minimum of 3 m/z), corresponding to a ~ 21% improvement in the discovery rate of true positives relative to prior studies. Furthermore, it was observed that optimization of these software parameters did not depend upon a priori determination of the statistically correct number of positive instances in the sample classes. The AUC metric appears to be suitable for the evaluation of all data analysis methods that utilize the proper experimental design.

3D-GS/TOFMS, Data discovery, ROC curves, Fisher ra↗

DOE OSTI2015

Dual-spacecraft reconstruction of a three-dimensional magnetic flux rope at the Earth's magnetopause

We present the first results of a data analysis method, developed by Sonnerup and Hasegawa (2011), for reconstructing three-dimensional (3-D), magnetohydrostatic structures from data taken as two closely spaced satellites traverse the structures. The method is applied to a magnetic flux transfer event (FTE), which was encountered on 27 June 2007 by at least three (TH-C, TH-D, and TH-E) of the five THEMIS probes near the subsolar magnetopause. The FTE was sandwiched between two oppositely directed reconnection jets under a southward interplanetary magnetic field condition, consistent with its generation by multiple X-line reconnection. The recovered 3-D field indicates that a magnetic flux rope with a diameter of ~ 3000 km was embedded in the magnetopause. The FTE flux rope had a significant 3-D structure, because the 3-D field reconstructed from the data from TH-C and TH-D (separated by ~ 390 km) better predicts magnetic field variations actually measured along the TH-E path than does the 2-D Grad–Shafranov reconstruction using the data from TH-C (which was closer to TH-E than TH-D and was at ~ 1250 km from TH-E). Such a 3-D nature suggests that the field lines reconnected at the two X-lines on both sides of the flux rope are entangled in a complicated way through their interaction with each other. The generation process of the observed 3-D flux rope is discussed on the basis of the reconstruction results and the pitch-angle distribution of electrons observed in and around the FTE.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS1957

Determination of Longitudinal Stability and Control Characteristics from Free-Flight Model Tests with Results at Transonic Speeds for Three Airplane Configurations

A test technique and data analysis method has been developed for determining the longitudinal aerodynamic characteristics from free-flight tests of rocket-propelled models. The technique makes use of accelerometers and an angle-of-attack indicator to permit instantaneous measurements of lift, drag, and pitching moments. The data, obtained during transient oscillations resulting from control-surface disturbances, are analyzed by essentially nonlinear direct methods (such as cross plots of the variation of lift coefficient with angle of attack) and by linear indirect methods by using the equations of motion for a transient oscillation. The analysis procedure has been set forth in some detail and the feasibility of the method has been demonstrated by data measured through the transonic speed range on several airplane configurations. It was shown that the flight conditions and dynamic similitude factors for the tests described were reasonably close to typical full-scale airplane conditions.

Gillis, Clarence L↗

DOE OSTI2024

X-ray scattering based scanning tomography for imaging and structural characterization of cellulose in plants

X-ray and neutron scattering have long been used for structural characterization of cellulose in plants. Due to averaging over the illuminated sample volume, these measurements traditionally overlooked the compositional and morphological heterogeneity within the sample. Here, a scanning tomographic imaging method is described, using contrast derived from the X-ray scattering intensity, for virtually sectioning the sample to reveal its internal structure at a resolution of a few micrometres. This method provides a means for retrieving the local scattering signal that corresponds to any voxel within the virtual section, enabling characterization of the local structure using traditional data-analysis methods. This is accomplished through tomographic reconstruction of the spatial distribution of a handful of mathematical components identified by non-negative matrix factorization from the large dataset of X-ray scattering intensity. Joint analysis of multiple datasets, to find similarity between voxels by clustering of the decomposed data, could help elucidate systematic differences between samples, such as those expected from genetic modifications, chemical treatments or fungal decay. The spatial distribution of the microfibril angle can also be analyzed, based on the tomographically reconstructed scattering intensity as a function of the azimuthal angle.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Analysing lessons from experience as part of a project to prepare/train teams to manage potentially stressful crisis situations - 164

Following the presentation of the methodology for making use of Operating Experience (OE) data, implemented as part of a study on preparing teams to manage potentially stressful crisis situations, this paper discusses and enhances the 'Implementing a Learning Organisation (ILO)' model, the aim of which is to organise operating experience for learning purposes. By way of introduction, we first present this model, which is divided into four fields of investigation for organising an OE mechanism to support learning, to pose the question we aim to answer in this paper: how does the field relating to the use of OE in the ILO model help us to turn the experience acquired to good account? With this in mind, we then present the different stages of the methodology for making use of OE. The first stage involves defining the area under examination in line with current best practices. This definition is then used in the second stage, as a basis for developing a framework to guide the analysis of OE. Finally, the third stage of the methodology involves selecting the OE data to be analysed. The findings obtained in the chosen case are then presented and several points are discussed based on this experience. These relate to the following: the acquisition of knowledge on current working situations enabled by OE; the stored data analysis method; and the conditions facilitating the use of OE. (authors)

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS2002

Application of Accelerometer Data to Mars Odyssey Aerobraking and Atmospheric Modeling

Aerobraking was an enabling technology for the Mars Odyssey mission even though it involved risk due primarily to the variability of the Mars upper atmosphere. Consequently, numerous analyses based on various data types were performed during operations to reduce these risk and among these data were measurements from spacecraft accelerometers. This paper reports on the use of accelerometer data for determining atmospheric density during Odyssey aerobraking operations. Acceleration was measured along three orthogonal axes, although only data from the component along the axis nominally into the flow was used during operations. For a one second count time, the RMS noise level varied from 0.07 to 0.5 mm/s2 permitting density recovery to between 0.15 and 1.1 kg per cu km or about 2% of the mean density at periapsis during aerobraking. Accelerometer data were analyzed in near real time to provide estimates of density at periapsis, maximum density, density scale height, latitudinal gradient, longitudinal wave variations and location of the polar vortex. Summaries are given of the aerobraking phase of the mission, the accelerometer data analysis methods and operational procedures, some applications to determining thermospheric properties, and some remaining issues on interpretation of the data. Pre-flight estimates of natural variability based on Mars Global Surveyor accelerometer measurements proved reliable in the mid-latitudes, but overestimated the variability inside the polar vortex.

Tolson, R. H.↗

NASA NTRS1982

An evaluation of vertical drag and ground effect using the RSRA rotor balance system

A flight test program utilizing the Rotor Systems Research Aircraft (RSRA) main rotor balance system was conducted to obtain data for the helicopter configuration. The test program is discussed along with the employed data reduction methods, and the results. NASA 740, the RSRA used for the vertical drag test, was in the standard helicopter configuration. The 31-foot radius blades have a linear twist of eight degrees and NACA 0012 airfoil sections. Aspects of instrumentation are considered, taking into account the data recording system, the static calibration facility, and aspects of data calibration and processing. Attention is given to the test procedure, data analysis methods, balance measurements, the ground effect, and vertical drag. It is found that the RSRA rotor balance system is capable of providing high quality performance data. The vertical drag of the RSRA is 4%, compared to 2.9% predicted.

Flemming, R. J.↗

DOE OSTI2018

Model-independent Exoplanet Transit Spectroscopy

We propose a new data analysis method for obtaining transmission spectra of exoplanet atmospheres and brightness variation across the stellar disk from transit observations. The new method is capable of recovering exoplanet atmosphere absorption spectra and stellar specific intensities without relying on theoretical models of stars and planets. We simultaneously fit both stellar specific intensity and planetary radius directly to transit light curves. This allows stellar models to be removed from the data analysis. Furthermore, we use a data quality weighted filtering technique to achieve an optimal trade-off between spectral resolution and reconstruction fidelity homogenizing the signal-to-noise ratio across the wavelength range. Such an approach is more efficient than conventional data binning onto a low-resolution wavelength grid. We demonstrate that our analysis is capable of reproducing results achieved by using an explicit quadratic limb-darkening equation and that the filtering technique helps eliminate spurious spectral features in regions with strong telluric absorption. The method is applied to the VLT FORS2 observations of the exoplanets GJ 1214 b and WASP-49 b, and our results are in agreement with previous studies. Comparisons between obtained stellar specific intensity and numerical models indicates that the method is capable of accurately reconstructing the specific intensity. The proposed method enables more robust characterization of exoplanetary atmospheres by separating derivation of planetary transmission and stellar specific intensity spectra (that is model-independent) from chemical and physical interpretation.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Python and HPC for High Energy Physics Data Analyses

High level abstractions in Python that can utilize computing hardware well seem to be an attractive option for writing data reduction and analysis tasks. In this paper, we explore the features available in Python which are useful and efficient for end user analysis in High Energy Physics (HEP). A typical vertical slice of an HEP data analysis is somewhat fragmented: the state of the reduction/analysis process must be saved at certain stages to allow for selective reprocessing of only parts of a generally time-consuming workflow. Also, algorithms tend to to be modular because of the heterogeneous nature of most detectors and the need to analyze different parts of the detector separately before combining the information. This fragmentation causes difficulties for interactive data analysis, and as data sets increase in size and complexity (O10 TiB for a “small” neutrino experiment to the O10 PiB currently held by the CMS experiment at the LHC), data analysis methods traditional to the field must evolve to make optimum use of emerging HPC technologies and platforms. Mainstream big data tools, while suggesting a direction in terms of what can be done if an entire data set can be available across a system and analysed with high-level programming abstractions, are not designed with either scientific computing generally, or modern HPC platform features in particular, such as data caching levels, in mind. Our example HPC use case is a search for a new elementary particle which might explain the phenomenon known as “Dark Matter”. Here, using data from the CMS detector, we will use HDF5 as our input data format, and MPI with Python to implement our use case.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

Modeling Complex Relationships in Large-Scale Data using Hypergraphs (LDRD Final Report)

This SAND report documents the findings of the LDRD project, "Modeling Complex Relationships in Large-Scale Data using Hypergraphs". The project ran from October 2017 through September 2019. The focus of the project was the development and application of hypergraph data analytics to Sandia relational data applications. In this project, we attempted to apply a hypergraph data analysis method—specifically, hypergraph eigenvector centrality—to Sandia mission problems to identify influential entities (people, location, times, etc.) in the data. Unfortunately, the application data led to graph and hypergraph representations containing disconnected components. To date, there are no well-established techniques for applying eigenvector centrality to such graphs and hypergraphs. In this report, we present several heuristics for computing eigenvector centrality for disconnected graphs. We believe this is an important start to understanding how to approach the similar problem for hypergraphs, but this project concluded before we made progress on that problem. The ideas, methods, and suggestions presented here can be used for further research into this challenging problem. We also present our ideas for generating graphs with known degree and centrality distributions. The goal in presenting this work is to identify a procedure for analyzing such graphs once the problem of addressing disconnected components has been addressed. When working with a single data set, this generator can be used to create many instances of graphs that can be used to analyze the robustness of the centrality computations for the original data set. Although the results did not match perfectly in the case of the Facebook Ego dataset used in the experiments presented here, this again represents a good start in the direction of a graph generator for such problems. We note that there are potential trade-offs between how the degree and centrality distributions are fit to the original data and suggested several possible avenues for follow-on research efforts.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

A review of advantages of high-efficiency X-ray spectrum imaging for analysis of nanostructured ferritic alloys

Nanostructured ferritic alloys (NFAs) exhibit complex microstructures consisting of 100-500 nm ferrite grains, grain boundary solute enrichment, and multiple populations of precipitates and nanoclusters (NCs). Understanding these materials' excellent creep and radiation-tolerance properties requires a combination of multiple atomic-scale experimental techniques. Recent advances in scanning transmission electron microscopy (STEM) hardware and data analysis methods have the potential to revolutionize nanometer to micrometer scale materials analysis. The application of these methods is applied to NFAs as a test case and is compared to both conventional STEM methods as well as complementary methods such as scanning electron microscopy and atom probe tomography. In this paper, we review past results and present new results illustrating the effectiveness of latest-generation STEM instrumentation and data analysis.

36 MATERIALS SCIENCE↗

DOE OSTI2022

The maximum extent of the filaments and sheets in the cosmic web: an analysis of the SDSS DR17

Filaments and sheets are striking visual patterns in cosmic web. The maximum extent of these large-scale structures are difficult to determine due to their structural variety and complexity. We construct a volume-limited sample of galaxies in a cubic region from the SDSS, divide it into smaller subcubes and shuffle them around. We quantify the average filamentarity and planarity in the 3D galaxy distribution as a function of the density threshold and compare them with those from the shuffled realizations of the original data. The analysis is repeated for different shuffling lengths by varying the size of the subcubes. The average filamentarity and planarity in the shuffled data show a significant reduction when the shuffling scales are smaller than the maximum size of the genuine filaments and sheets. We observe a statistically significant reduction in these statistical measures even at a shuffling scale of $\sim 130 \, {{\, \rm Mpc}}$, indicating that the filaments and sheets in three dimensions can extend up to this length scale. They may extend to somewhat larger length scales that are missed by our analysis due to the limited size of the SDSS data cube. We expect to determine these length scales by applying this method to deeper and larger surveys in future.

79 ASTRONOMY AND ASTROPHYSICS↗