A field-particle correlation analysis of magnetic pumping
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This program has been designed to assist with the tracking of a sample from one analytical instrument to another such as SEM, microscopes, micro x-ray diffraction and other instruments where particular positions/locations on the sample are examined, photographed, etc. The software is designed to easily enter the position of fiducials and locations of interest such that in a future session in the same of different instrument the positions of interest can be re-found through using the known location fiducials in the current and reference session to transform the point into the current sessions coordinate system. The software is dialog box driven guiding the user through the necessary data entry and program choices. Information is stored in a series of text based extensible markup language (XML) files.
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Abstract — Metal halide perovskites (MHPs) are an exciting research topic as they have the potential to make solar cells that are both more efficient than current siliconbased designs and have a wider range of applications. In this work the crystallization of CsPbBr2Hal (Hal = Cl, Br, I) halide perovskite melts were studied by the differential thermal analysis method. It was established that the crystallization of CsPbBr2Hal (Hal = Cl, Br, I) melts can be “hot” (i.e., at temperatures above the point of the alloy’s start-melting temperature) or with supercooling. The replacement of the bromine atom with another halogen atom leads to a shift of the dwell temperature range, at which “hot” crystallization takes place, from 830-846 K for CsPbBr3 to 807-832 K for CsPbBr2Cl and 741-768 K for CsPbBr2I. The activation energy of “hot” crystallization decreases in the same order. A linear dependence between the pre-exponential factor (ln(𝑽𝑽𝒄𝒄𝒄𝒄𝒄𝒄𝒔𝒔𝒕𝒕 𝟎𝟎 )) and the activation energy (Ea) of the crystallization process is revealed from the experimental data, proving the compensation effect.
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Turbulent electron temperature fluctuation measurement using a correlation electron cyclotron emission (CECE) radiometer has become an important diagnostic for studying energy transport in fusion plasmas, and its use is widespread in tokamaks (DIII-D, ASDEX Upgrade, Alcator C-Mod, Tore Supra, EAST, TCV, HL-2A, etc.). The CECE diagnostic typically performs correlation analysis between two closely spaced (within the turbulent correlation length) ECE channels that are dominated by uncorrelated thermal noise emission. This allows electron temperature fluctuations embedded in the thermal noise to be revealed and fluctuation level and spectra determined. We have demonstrated a new, improved CECE coherency-based analysis for calculating the temperature fluctuation frequency spectrum and level, which has been verified both numerically through the simulation of synthetic ECE radiometer data and through analysis of experimental data from the CECE system on DIII-D. The new formulation places coherency-based analysis on a firm foundational footing and corrects some currently published methodologies. This new method accurately accounts for bias error in the coherence function and correctly calculates noise levels for a fixed data record length. It provides excellent accuracy in determining temperature fluctuation level (e.g., <10% error) even for a small realization number in the ensemble average. The method also has a smaller uncertainty (i.e., error bar) in the power spectrum when compared to the more standard cross-power method when evaluated at low coherency. Direct calculation of system noise level using correlation between randomized intermediate frequency signals is recommended.
Purpose: The association of Ki-67 staining index (Ki67-SI) with overall survival (OS), disease-specific mortality (DSM), distant metastasis (DM), and biochemical failure (BF) was examined in men with favorable- to intermediate-risk prostate cancer receiving radiation therapy (RT) alone or with short-term androgen deprivation (ADT) in Radiation Therapy Oncology Group (RTOG) 94-08. Methods and Materials: 468 patients (23.6%) on RTOG 94-08 had sufficient tissue for Ki67-SI analysis. The median follow-up time was 7.9 years. Ki67-SI was determined by immunohistochemistry and quantified manually and by image analysis. Correlative analysis versus clinical outcome was performed using the third quartile (≥Q3) cutpoint. A proportional hazards multivariable analysis (MVA) dichotomized covariates in accordance with trial stratification and randomization criteria. Results: In MVAs adjusted for all treatment covariates, high Ki67-SI (≥Q3) was correlated with increased DSM (hazard ratio [HR] 2.48, P=.03), DM (HR 3.5, P=.002), and BF (HR 3.55, P<.0001). MVA revealed similar Ki67-associated hazard ratios in each separate treatment arm for DSM, DM, and BF; these reached significance only for DM in the RT-alone arm and for BF in both arms. Ki67-SI was not a significant predictor of intraprostatic recurrence assessed by repeated biopsy 2 years after treatment. Patients with a high or low Ki67-SI seemed to experience a similar relative benefit from the addition of ADT to radiation. Conclusions: High Ki67-SI independently predicts for increased DSM, DM, and protocol BF in primarily intermediate-risk prostate cancer patients treated with RT with or without ADT on RTOG 94-08 but does not predict for local recurrence or for increased relative benefit from ADT. This and prior studies lend support for the use of Ki67-SI as a stratification factor in future trials.
Cleanup efforts have been ongoing since the late 1990s to remediate contaminated waste sites and groundwater in the 100 Areas at the U.S. Department of Energy (DOE) Hanford Site. One of the primary contaminants of concern is hexavalent chromium (Cr(VI)), which was used as a corrosion inhibitor in cooling water for nuclear reactors that formerly operated along the shoreline of the Columbia River. Cleanup efforts have included 1) removal, treatment (as needed), and disposal of contaminated sediments; 2) in situ redox manipulation as a permeable reactive barrier; 3) pump-and-treat; 4) soil flushing; and 5) monitored natural attenuation. DOE’s annual groundwater monitoring reports document the significant reductions in Cr(VI) plume areas that have occurred over the past 10 years or more as a result of these cleanup efforts. The Record of Decision for the 100-HR-3 operable unit specified a cleanup level (CUL) for Cr(VI) in groundwater of 48 µg/L to protect human receptors, and a surface water CUL of 10 µg/L to protect aquatic organisms in the Columbia River. The Record of Decision did not specify point-of-compliance locations for the surface water CUL. Data for 2019 from the six groundwater operable units (OUs) in the 100 Areas indicate that the 48 μg/L groundwater CUL has been achieved in 100% of the wells in the 100-BC and 100-NR OUs, and in 89- 97% of the wells in the other OUs (100-KR, 100-HR-D, 100-HR-H, 100-FR). Data for 2019 indicate that 100% of the aquifer tubes monitored for Cr(VI) in the 100 Areas have concentrations below the 48 μg/L groundwater CUL. However, the 10 μg/L standard has not yet been consistently achieved for both inland groundwater monitoring wells and shoreline aquifer tubes. This report describes a series of data analyses performed to identify consistent relationships, if any, between inland well and shoreline Cr(VI) concentrations within the 100 Areas. To this end, select monitoring data for Cr(VI) measured in groundwater and aquifer tubes at the 100 Areas were analyzed for a 10-year period—2010 to 2019. Relationships between inland groundwater plumes and surface-water points of discharge in and along the Columbia River were examined through several analyses that included inland well and aquifer tube concentrations as a function of distance from the shoreline, evaluation of cumulative probability plots, trend analysis, correlation analysis, cluster analysis, and identification of plume trajectories for each of the 100 Areas. The analyses did not identify consistent relationships between inland groundwater Cr(VI) concentrations and shoreline concentrations within the 100 Areas due to several confounding factors influencing groundwater flow directions and Cr(VI) concentrations. The proximity of groundwater Cr(VI) plumes to the river, and the highly dynamic nature of the river, influence the transport behavior of the plumes and create challenges for quantifying attenuation of Cr(VI) between the inland monitoring wells and shoreline concentrations. Other factors contributing to temporal and spatial Cr(VI) concentrations, as supported by some of the data analyses, include the presence of vadose zone sources, variable sorption behavior, and complexities associated with Cr(VI) mass transfer between the upper and lower aquifers and their interactions with the river. Hence, monitoring to assess compliance with target CULs will need to be determined for each area individually since several factors influence Cr(VI) concentrations in the 100 Areas.
Blast furnace (BF) in ironmaking is a nonlinear dynamic process with complicated physical-chemical reactions, where multi-phase and multi-field coupling and large time delay occur during its operation. In BF operation, the molten iron temperature (MIT) as well as Si, P and S contents of molten iron are the most essential molten iron quality (MIQ) indices, whose measurement, modeling and control have always been important issues in metallurgic engineering and automation field. This paper develops a novel data-driven nonlinear state space modeling for the prediction and control of multivariate MIQ indices by integrating hybrid modeling and control techniques. First, to improve modeling efficiency, a data-driven hybrid method combining canonical correlation analysis and correlation analysis is proposed to identify the most influential controllable variables as the modeling inputs from multitudinous factors would affect the MIQ indices. Then, a Hammerstein model for the prediction of MIQ indices is established using the LS-SVM based nonlinear subspace identification method. Such a model is further simplified by using piecewise cubic Hermite interpolating polynomial method to fit the complex nonlinear kernel function. Compared to the original Hammerstein model, this simplified model can not only significantly reduce the computational complexity, but also has almost the same reliability and accuracy for a stable prediction of MIQ indices. Last, in order to verify the practicability of the developed model, it is applied in designing a genetic algorithm based nonlinear predictive controller for multivariate MIQ indices by directly taking the established model as a predictor. Industrial experiments show the advantages and effectiveness of the proposed approach.
Wind tunnel tests were conducted to determine the aerodynamic heating created by gaps in the reusable surface insulation (RSI) thermal protection system (TPS) for the space shuttle. The effects of various parameters of the RSI on convective heating characteristics are described. The wind tunnel tests provided a data base for accurate assessment of gap heating. Analysis and correlation of the data provide methods for predicting heating in the RSI gaps on the space shuttle.
We present a group-galaxy cross-correlation analysis using a group catalog produced from the 16,500 spectra from the optical zCOSMOS galaxy survey. Our aim is to perform a consistency test in the redshift range 0.2 {<=} z {<=} 0.8 between the clustering strength of the groups and mass estimates that are based on the richness of the groups. We measure the linear bias of the groups by means of a group-galaxy cross-correlation analysis and convert it into mass using the bias-mass relation for a given cosmology, checking the systematic errors using realistic group and galaxy mock catalogs. The measured bias for the zCOSMOS groups increases with group richness as expected by the theory of cosmic structure formation and yields masses that are reasonably consistent with the masses estimated from the richness directly, considering the scatter that is obtained from the 24 mock catalogs. Some exceptions are the richest groups at high redshift (estimated to be more massive than 10{sup 13.5} M{sub Sun }), for which the measured bias is significantly larger than for any of the 24 mock catalogs (corresponding to a 3{sigma} effect), which is attributed to the extremely large structure that is present in the COSMOS field at z {approx} 0.7. Our results are in general agreement with previous studies that reported unusually strong clustering in the COSMOS field.
Analysis and correlation of thermodynamic cycles for spacecraft power systems using maximum cycle irreversibility concept and second law of thermodynamics
Using infrared, radio, and {gamma}-ray data, we investigate the propagation characteristics of cosmic-ray (CR) electrons and nuclei in the 30 Doradus (30 Dor) star-forming region in the Large Magellanic Cloud (LMC) using a phenomenological model based on the radio-far-infrared correlation within galaxies. Employing a correlation analysis, we derive an average propagation length of {approx}100-140 pc for {approx}3 GeV CR electrons resident in 30 Dor from consideration of the radio and infrared data. Assuming that the observed {gamma}-ray emission toward 30 Dor is associated with the star-forming region, and applying the same methodology to the infrared and {gamma}-ray data, we estimate a {approx}20 GeV propagation length of 200-320 pc for the CR nuclei. This is approximately twice as large as for {approx}3 GeV CR electrons, corresponding to a spatial diffusion coefficient that is {approx}4 times higher, scaling as (R/GV){sup {delta}} with {delta} Almost-Equal-To 0.7-0.8 depending on the smearing kernel used in the correlation analysis. This value is in agreement with the results found by extending the correlation analysis to include {approx}70 GeV CR nuclei traced by the 3-10 GeV {gamma}-ray data ({delta} Almost-Equal-To 0.66 {+-} 0.23). Using the mean age of the stellar populations in 30 Dor and the results from our correlation analysis, we estimate a diffusion coefficient D{sub R} Almost-Equal-To (0.9-1.0) Multiplication-Sign 10{sup 27}(R/GV){sup 0.7} cm{sup 2} s{sup -1}. We compare the values of the CR electron propagation length and surface brightness for 30 Dor and the LMC as a whole with those of entire disk galaxies. We find that the trend of decreasing average CR propagation distance with increasing disk-averaged star formation activity holds for the LMC, and extends down to single star-forming regions, at least for the case of 30 Dor.
A simple computational procedure is synthesized to process changes in the microwave-antenna pathlength-error measure when there are changes in the antenna structure model. The procedure employs structural modification reanalysis methods combined with new extensions of correlation analysis to provide the revised rms pathlength error. Mainframe finite-element-method processing of the structure model is required only for the initial unmodified structure, and elementary postprocessor computations develop and deal with the effects of the changes. Several illustrative computational examples are included. The procedure adapts readily to processing spectra of changes for parameter studies or sensitivity analyses.
Slycat™ is a web-based system for analysis of large, high-dimensional data such as that produced by High Performance Computing (HPC) platforms. The Slycat™ server integrates data ingestion, scalable analysis, data management, and visualization with commodity web clients using a multi-tiered hierarchy of data and model storage. Analysis inputs are pushed or pulled into Slycat™, where models are generated and analysis artifacts are stored in a project database. These artifacts are the basis for visualizations that are delivered to users’ desktops through ordinary web browsers, eliminating the need to build and deploy platform-specific client applications. Slycat™ currently provides four types of analysis: canonical correlation analysis (CCA) to model relationships between inputs and output metrics, time series analysis featuring clustering and comparative visualization of waveforms, parameter space visualization including remote retrieval of images and movies from HPC disks, and VideoSwarm for modeling video similarities over time.
Composite laminates used in space structures are exposed to both thermal and mechanical loads. Cracks in the matrix form, changing the laminate thermoelastic properties. An analytical methodology is developed to predict microcrack density in a general laminate exposed to an arbitrary thermomechanical load history. The analysis uses a shear lag stress solution in conjunction with an energy-based cracking criterion. Experimental investigation was used to verify the analysis. Correlation between analysis and experiment is generally excellent. The analysis does not capture machining-induced cracking, or observed delayed crack initiation in a few ply groups, but these errors do not prevent the model from being a useful preliminary design tool.