Three-Dimensional Numerical Analysis on Blade Response of a Vertical-Axis Tidal Current Turbine Under Operational Conditions
Abstract not provided
16 TIDAL AND WAVE POWER↗
SEARCH · Engineering Papers
Results for “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.
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Parametric sensitivity analysis for stochastic molecular systems using information theoretic metrics
In this paper, we present a parametric sensitivity analysis (SA) methodology for continuous time and continuous space Markov processes represented by stochastic differential equations. Particularly, we focus on stochastic molecular dynamics as described by the Langevin equation. The utilized SA method is based on the computation of the information-theoretic (and thermodynamic) quantity of relative entropy rate (RER) and the associated Fisher information matrix (FIM) between path distributions, and it is an extension of the work proposed by Y. Pantazis and M. A. Katsoulakis [J. Chem. Phys. 138, 054115 (2013)]. A major advantage of the pathwise SA method is that both RER and pathwise FIM depend only on averages of the force field; therefore, they are tractable and computable as ergodic averages from a single run of the molecular dynamics simulation both in equilibrium and in non-equilibrium steady state regimes. We validate the performance of the extended SA method to two different molecular stochastic systems, a standard Lennard-Jones fluid and an all-atom methane liquid, and compare the obtained parameter sensitivities with parameter sensitivities on three popular and well-studied observable functions, namely, the radial distribution function, the mean squared displacement, and the pressure. Results show that the RER-based sensitivities are highly correlated with the observable-based sensitivities.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A novel vacuum spectrometer for total reflection x-ray fluorescence analysis with two exchangeable low power x-ray sources for the analysis of low, medium, and high Z elements in sequence
The extension of the detectable elemental range with Total Reflection X-ray Fluorescence (TXRF) analysis is a challenging task. In this paper, it is demonstrated how a TXRF spectrometer is modified to analyze elements from carbon to uranium. Based on the existing design of a vacuum TXRF spectrometer with a 12 specimen sample changer, the following components were renewed: the silicon drift detector with 20 mm{sup 2} active area and having a special ultra-thin polymer window allowing the detection of elements from carbon upwards. Two exchangeable X-ray sources guarantee the efficient excitation of both low and high Z elements. These X-ray sources were two light-weighted easily mountable 35 W air-cooled low-power tubes with Cr and Rh anodes, respectively. The air cooled tubes and the Peltier-cooled detector allowed to construct a transportable tabletop spectrometer with compact dimensions, as neither liquid nitrogen cooling for the detector nor a water cooling circuit and a bulky high voltage generator for the X-ray tubes are required. Due to the excellent background conditions as a result of the TXRF geometry, detection limits of 150 ng for C, 12 ng for F, and 3.3 ng for Na have been obtained using Cr excitation in vacuum. For Rh excitation, the detection limits of 90 pg could be achieved for Sr. Taking 10 to 20 μl of sample volume, extrapolated detection limits in the ng/g (ppb) range are resulting in terms of concentration.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Possible signatures of dissipation from time-series analysis techniques using a turbulent laboratory magnetohydrodynamic plasma
The frequency spectrum of magnetic fluctuations as measured on the Swarthmore Spheromak Experiment is broadband and exhibits a nearly Kolmogorov 5/3 scaling. It features a steepening region which is indicative of dissipation of magnetic fluctuation energy similar to that observed in fluid and magnetohydrodynamic turbulence systems. Two non-spectrum based time-series analysis techniques are implemented on this data set in order to seek other possible signatures of turbulent dissipation beyond just the steepening of fluctuation spectra. Presented here are results for the flatness, permutation entropy, and statistical complexity, each of which exhibits a particular character at spectral steepening scales which can then be compared to the behavior of the frequency spectrum.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Data mining graphene: Correlative analysis of structure and electronic degrees of freedom in graphenic monolayers with defects
The link between changes in the material crystal structure and its mechanical, electronic, magnetic, and optical functionalities known as the structure-property relationship is the cornerstone of the contemporary materials science research. The recent advances in scanning transmission electron and scanning probe microscopies (STEM and SPM) have opened an unprecedented path towards examining the materials structure property relationships on the single-impurity and atomic-configuration levels. Lacking, however, are the statistics-based approaches for cross-correlation of structure and property variables obtained in different information channels of the STEM and SPM experiments. Here we have designed an approach based on a combination of sliding window Fast Fourier Transform, Pearson correlation matrix, linear and kernel canonical correlation, to study a relationship between lattice distortions and electron scattering from the SPM data on graphene with defects. Our analysis revealed that the strength of coupling to strain is altered between different scattering channels which can explain coexistence of several quasiparticle interference patterns in the nanoscale regions of interest. In addition, the application of the kernel functions allowed us extracting a non-linear component of the relationship between the lattice strain and scattering intensity in graphene. Lastly, the outlined approach can be further utilized to analyzing correlations in various multi-modal imaging techniques where the information of interest is spatially distributed and has usually a complex multidimensional nature.
36 MATERIALS SCIENCE↗
The clustering of the SDSS-IV extended Baryon Oscillation Spectroscopic Survey DR14 quasar sample: anisotropic clustering analysis in configuration space
We explore the cosmological implications of anisotropic clustering measurements of the quasar sample from Data Release 14 (DR14) of the Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey (eBOSS) in configuration space. The similar to 147000 quasar sample observed by eBOSS offers a direct tracer of the density field and bridges the gap of previous baryon acoustic oscillation measurements between redshift 0.8 < z < 2.2. By analysing the two-point correlation function characterized by clustering wedges xi(wi)(s) and multipolesi xi(l)(S), we measure the angular diameter distance, Hubble parameter, and cosmic structure growth rate. We define a systematic error budget for our measurements based on the analysis of N-body simulations and mock catalogues. Based on the DR14 large-scale structure quasar sample at the effective redshift z(eff) = 1.52, we find the growth rate of cosmic structure f sigma(8)(z(eff)) = 0.396 +/- 0.079, and the geometric parameters Dv(z)/r(d) = 26.47 +/- 1.23, and F-AP(Z) = 2.53 +/- 0.22, where the uncertainties include both statistical and systematic errors. These values are in excellent agreement with the best-fitting standard A cold dark matter model to the latest cosmic microwave background data from Planck.
cosmology↗
Structure analysis of supported disordered molybdenum oxides using pair distribution function analysis and automated cluster modelling
Molybdenum oxides and sulfides on various low-cost high-surface-area supports are excellent catalysts for several industrially relevant reactions. The surface layer structure of these materials is, however, difficult to characterize due to small and disordered MoO x domains. Here, it is shown how X-ray total scattering can be applied to gain insights into the structure through differential pair distribution function (d-PDF) analysis, where the scattering signal from the support material is subtracted to obtain structural information on the supported structure. MoO x catalysts supported on alumina nanoparticles and on zeolites are investigated, and it is shown that the structure of the hydrated molybdenum oxide layer is closely related to that of disordered and polydisperse polyoxometalates. By analysing the PDFs with a large number of automatically generated cluster structures, which are constructed in an iterative manner from known polyoxometalate clusters, information is derived on the structural motifs in supported MoO x .
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
High-throughput prediction of eucalypt lignin syringyl/guaiacyl content using multivariate analysis: A comparison between mid-infrared, near-infrared, and Raman spectroscopies for model development
Background: In order to rapidly and efficiently screen potential biofuel feedstock candidates for quintessential traits, robust high-throughput analytical techniques must be developed and honed. The traditional methods of measuring lignin syringyl/guaiacyl (S/G) ratio can be laborious, involve hazardous reagents, and/or be destructive. Vibrational spectroscopy can furnish high-throughput instrumentation without the limitations of the traditional techniques. Spectral data from mid-infrared, near-infrared, and Raman spectroscopies was combined with S/G ratios, obtained using pyrolysis molecular beam mass spectrometry, from 245 different eucalypt and Acacia trees across 17 species. Iterations of spectral processing allowed the assembly of robust predictive models using partial least squares (PLS). Results: The PLS models were rigorously evaluated using three different randomly generated calibration and validation sets for each spectral processing approach. Root mean standard errors of prediction for validation sets were lowest for models comprised of Raman (0.13 to 0.16) and mid-infrared (0.13 to 0.15) spectral data, while near-infrared spectroscopy led to more erroneous predictions (0.18 to 0.21). Correlation coefficients (r) for the validation sets followed a similar pattern: Raman (0.89 to 0.91), mid-infrared (0.87 to 0.91), and near-infrared (0.79 to 0.82). These statistics signify that Raman and mid-infrared spectroscopy led to the most accurate predictions of S/G ratio in a diverse consortium of feedstocks. Conclusion: Eucalypts present an attractive option for biofuel and biochemical production. Given the assortment of over 900 different species of Eucalyptus and Corymbia , in addition to various species of Acacia , it is necessary to isolate those possessing ideal biofuel traits. This research has demonstrated the validity of vibrational spectroscopy to efficiently partition different potential biofuel feedstocks according to lignin S/G ratio, significantly reducing experiment and analysis time and expense while providing non-destructive, accurate, global, predictive models encompassing a diverse array of feedstocks.
09 BIOMASS FUELS↗
Shared Genomic Regions Between Derivatives of a Large Segregating Population of Maize Identified Using Bulked Segregant Analysis Sequencing and Traditional Linkage Analysis
Delayed transition from the vegetative stage to the reproductive stage of development and increased plant height have been shown to increase biomass productivity in grasses. The goal of this project was to detect quantitative trait loci using extremes from a large synthetic population, as well as a related recombinant inbred line mapping population for these two traits. Ten thousand individuals from a B73 × Mo17 noninbred population intermated for 14 generations (IBM Syn14) were grown at a density of approximately 16,500 plants ha -1 . Flowering time and plant height were measured within this population. DNA was pooled from the 46 most extreme individuals from each distributional tail for each of the traits measured and used in bulk segregant analysis (BSA) sequencing. Allelic divergence at each of the ~1.1 million SNP loci was estimated as the difference in allele frequencies between the selected extremes. Additionally, 224 intermated B73 × Mo17 recombinant inbred lines were concomitantly grown at a similar density adjacent to the large synthetic population and were assessed for flowering time and plant height. Using the BSA sequencing method, 14 and 13 genomic regions were identified for flowering time and plant height, respectively. Linkage mapping with the RIL population identified eight and three regions for flowering time and plant height, respectively. Of the regions identified, three colocalized between the two populations for flowering time and two colocalized for plant height. This study demonstrates the utility of using BSA sequencing for the dissection of complex quantitative traits important for production of lignocellulosic ethanol.
Genetics & Heredity↗
Interpreting the Terahertz Spectrum of Complex Materials: The Unique Contribution of the Bayesian Analysis
Abstract not provided
De Francesco, Alessio↗
Data Analysis using Psocake at PAL-XFEL
Psocake is a software program designed for high throughput data reduction and analysis of free-electron laser experiments. Its serial crystallography graphical user interface allows browsing of detector images, Bragg peak finding with easy parameter tuning, generate region-of-interest masks, and crystal indexing. It was originally developed for use at the Linac Coherent Light Source, SLAC national accelerator laboratory and has been adopted for use at Pohang accelerator laboratory due to popular demand. Here, we describe the features of psocake available at Pohang and include information about data management that we hope will be useful for users of the facility.
43 PARTICLE ACCELERATORS↗
An investigation of the aerodynamic characteristics of a 25 deg sphere-cone including a pressure distribution analysis at angles of attack, and a trajectory analysis during a typical reentry trajectory
Aerodynamic characteristics of reentry body - pressure distribution at angles of attack and trajectory analysis
TRAJECTORY ANALYSIS↗
Comparative studies of conceptual design and qualification procedures for a Mars probe/lander. Volume V - Subsystem and technical analysis. Book 1 - Trajectory analysis Final report
Trajectory analysis for Mars probe for entry from approach hyperbola or from Mars orbit
MARS PROBE↗
Automatic malfunction analysis by discrete network simulation. Appendix C - Programmers reference manual automatic malfunction analysis programs
Computer programs for automatic malfunction analysis by discrete network simulation
COMPUTER PROGRAM↗
An Enhanced Spectral Analysis Tool (SAT) for Radio Frequency Interference Analysis and Spectrum Management
A microcomputer based software for analysis of radio frequency interference is presented in this paper.
AST radio frequency interference Analysis and Spec↗
Spatiotemporal Filtering Using Principal Component Analysis and Karhunen-Loeve Expansion Approaches for Regional GPS Network Analysis
Spatial filtering is an effective way to improve the precision of coordinate time series for regional GPS networks by reducing so-called common mode errors, thereby providing better resolution for detecting weak or transient deformation signals. The commonly used approach to regional filtering assumes that the common mode error is spatially uniform, which is a good approximation for networks of hundreds of kilometers extent, but breaks down as the spatial extent increases. A more rigorous approach should remove the assumption of spatially uniform distribution and let the data themselves reveal the spatial distribution of the common mode error. The principal component analysis (PCA) and the Karhunen-Loeve expansion (KLE) both decompose network time series into a set of temporally varying modes and their spatial responses. Therefore they provide a mathematical framework to perform spatiotemporal filtering.We apply the combination of PCA and KLE to daily station coordinate time series of the Southern California Integrated GPS Network (SCIGN) for the period 2000 to 2004. We demonstrate that spatially and temporally correlated common mode errors are the dominant error source in daily GPS solutions. The spatial characteristics of the common mode errors are close to uniform for all east, north, and vertical components, which implies a very long wavelength source for the common mode errors, compared to the spatial extent of the GPS network in southern California. Furthermore, the common mode errors exhibit temporally nonrandom patterns.
displacement↗
High Precision Thermal, Structural and Optical Analysis of an External Occulter Using a Common Model and the General Purpose Multi-Physics Analysis Tool Cielo
The efficient simulation of multidisciplinary thermo-opto-mechanical effects in precision deployable systems has for years been limited by numerical toolsets that do not necessarily share the same finite element basis, level of mesh discretization, data formats, or compute platforms. Cielo, a general purpose integrated modeling tool funded by the Jet Propulsion Laboratory and the Exoplanet Exploration Program, addresses shortcomings in the current state of the art via features that enable the use of a single, common model for thermal, structural and optical aberration analysis, producing results of greater accuracy, without the need for results interpolation or mapping. This paper will highlight some of these advances, and will demonstrate them within the context of detailed external occulter analyses, focusing on in-plane deformations of the petal edges for both steady-state and transient conditions, with subsequent optical performance metrics including intensity distributions at the pupil and image plane.
integrated modeling↗
Wavelet analysis of polar vortex variability over the twentieth century: WAVELET ANALYSIS OF POLAR VORTEX
We observe recent increases in extreme weather events in the Northern Hemisphere have been linked to amplified planetary waves. Changes in planetary wave properties are linked to changes in climate; hence, finding a mechanism that links the planetary wave variability under climatic forcing and midlatitude blocking events has engendered a great deal of interest. In this study, wavelet analysis is applied to time series of planetary wave phase speeds at high latitudes as a first step to assessing the potential for identifying these mechanisms in the observational record. A circumpolar multiannual cycle increase is found but signals also demonstrate a complex westward propagation pattern with periods of intense wave variability. Significant correlations between wavelet power at all time scales and albedo, snow cover, atmospheric ozone levels, and surface air temperature are demonstrated.
54 ENVIRONMENTAL SCIENCES↗