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DOE OSTI2024

Visible core spectroscopy at Wendelstein 7-X

This paper presents an overview of recent hardware extensions and data analysis developments to the Wendelstein 7-X visible core spectroscopy systems. These include upgrades to prepare the in-vessel components for long-pulse operation, nine additional spectrometers, a new line of sight array for passive spectroscopy, and a coherence imaging charge exchange spectroscopy diagnostic. Progress in data analysis includes ion temperatures and densities from multiple impurity species, a statistical comparison with x-ray crystal spectrometer measurements, neutral density measurements from thermal passive Balmer-alpha emission, and a Bayesian analysis of active hydrogen emission, which is able to infer electron density and main ion temperature profiles.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2016

High-frequency electromagnetic scarring in three-dimensional axisymmetric convex cavities

Here, this article examines the localization of high-frequency electromagnetic fields in three-dimensional axisymmetric cavities along periodic paths between opposing sides of the cavity. When these orbits lead to unstable localized modes, they are known as scars. This article treats the case where the opposing sides, or mirrors, are convex. Particular attention is focused on the normalization through the electromagnetic energy theorem. Both projections of the field along the scarred orbit as well as field point statistics are examined. Statistical comparisons are made with a numerical calculation of the scars run with an axisymmetric simulation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2011

BINARY FORMATION MECHANISMS: CONSTRAINTS FROM THE COMPANION MASS RATIO DISTRIBUTION

We present a statistical comparison of the mass ratio distribution of companions, as observed in different multiplicity surveys, to the most recent estimate of the single-object mass function. The main goal of our analysis is to test whether or not the observed companion mass ratio distribution (CMRD) as a function of primary star mass and star formation environment is consistent with having been drawn from the field star initial mass function (IMF). We consider samples of companions for M dwarfs, solar-type stars, and intermediate-mass stars, both in the field as well as clusters or associations, and compare them with populations of binaries generated by random pairing from the assumed IMF for a fixed primary mass. With regard to the field we can reject the hypothesis that the CMRD was drawn from the IMF for different primary mass ranges: the observed CMRDs show a larger number of equal-mass systems than predicted by the IMF. This is in agreement with fragmentation theories of binary formation. For the open clusters {alpha} Persei and the Pleiades we also reject the IMF random-pairing hypothesis. Concerning young star-forming regions, currently we can rule out a connection between the CMRD and the field IMF in Taurus but not in Chamaeleon I. Larger and different samples are needed to better constrain the result as a function of the environment. We also consider other companion mass functions and we compare them with observations. Moreover the CMRD both in the field and clusters or associations appears to be independent of separation in the range covered by the observations. Combining therefore the CMRDs of M (1-2400 AU) and G (28-1590 AU) primaries in the field and intermediate-mass primary binaries in Sco OB2 (29-1612 AU) for mass ratios, q = M{sub 2}/M{sub 1}, from 0.2 to 1, we find that the best chi-square fit follows a power law dN/dq{proportional_to}q {sup {beta}}, with {beta} = -0.50 {+-} 0.29, consistent with previous results. Finally, we note that the Kolmogorov-Smirnov test gives a {approx}1% probability of the observed CMRD in the Pleiades and Taurus being consistent with that observed for solar-type primaries in the field over comparable primary mass range. This highlights the value of using CMRDs to understand which star formation events contribute most to the field.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2011

THE SUBSTELLAR POPULATION OF {sigma} ORIONIS: A DEEP WIDE SURVEY

We present a deep I, Z photometric survey covering a total area of 1.12 deg{sup 2} of the {sigma} Orionis cluster and reaching completeness magnitudes of I = 22 and Z = 21.5 mag. From I, I - Z color-magnitude diagrams we have selected 153 candidates that fit the previously known sequence of the cluster. They have magnitudes in the range I = 16-23 mag, which corresponds to a mass interval from 0.1 down to 0.008 M{sub Sun} at the most probable age of {sigma} Orionis (2-4 Myr). Using J-band photometry, we find that 124 of the 151 candidates within the completeness of the optical survey (82%) follow the previously known infrared photometric sequence of the cluster and are probably members. We have studied the spatial distribution of the very low mass stars and brown dwarf population of the cluster and found that there are objects located at distances greater than 30 arcmin to the north and west of {sigma} Orionis that probably belong to different populations of the Orion's Belt. For the 102 bona fide {sigma} Orionis cluster member candidates, we find that the radial surface density can be represented by a decreasing exponential function ({sigma}={sigma}{sub 0}e{sup -r/r{sub 0}}) with a central density of {sigma}{sub 0} = 0.23 {+-} 0.03 objects arcmin{sup -2} and a characteristic radius of r{sub 0} = 9.5 {+-} 0.7 arcmin. From a statistical comparison with Monte Carlo simulations, we conclude that the spatial distribution of the objects located at the same distance from the center of the cluster is compatible with a Poissonian distribution and, hence, that very low mass stars and brown dwarfs are not mainly forming aggregations or sub-clustering. Using near-infrared JHK-band data from Two Micron All Sky Survey and UKIRT Deep Infrared Sky Survey and mid-infrared data from Infrared Array Camera/Spitzer, we find that about 5%-9% of the brown dwarf candidates in the {sigma} Orionis cluster have K-band excesses and 30% {+-} 7% of them show mid-infrared excesses at wavelengths longer than 5.8 {mu}m. These are probably related to the presence of disks, most of which are 'transition disks'. We have also calculated the initial mass spectrum (dN/dm) of {sigma} Orionis from very low mass stars ({approx}0.10 M{sub Sun }) to the deuterium-burning mass limit (0.012-0.013 M{sub Sun }), i.e., complete in the entire brown dwarf regime. This mass spectrum is a rising function toward lower masses and can be represented by a power-law distribution (dN/dm {proportional_to} m{sup -{alpha}}) with an exponent {alpha} of 0.7 {+-} 0.3 for an age of 3 Myr.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

THE MASS DEPENDENCE BETWEEN PROTOPLANETARY DISKS AND THEIR STELLAR HOSTS

We present a substantial extension of the millimeter (mm) wave continuum photometry catalog for circumstellar dust disks in the Taurus star-forming region, based on a new ''snapshot'' {lambda} = 1.3 mm survey with the Submillimeter Array. Combining these new data with measurements in the literature, we construct a mm-wave luminosity distribution, f(L{sub mm}), for Class II disks that is statistically complete for stellar hosts with spectral types earlier than M8.5 and has a 3{sigma} depth of roughly 3 mJy. The resulting census eliminates a longstanding selection bias against disks with late-type hosts, and thereby demonstrates that there is a strong correlation between L{sub mm} and the host spectral type. By translating the locations of individual stars in the Hertzsprung-Russell diagram into masses and ages, and adopting a simple conversion between L{sub mm} and the disk mass, M{sub d} , we confirm that this correlation corresponds to a statistically robust relationship between the masses of dust disks and the stars that host them. A Bayesian regression technique is used to characterize these relationships in the presence of measurement errors, data censoring, and significant intrinsic scatter: the best-fit results indicate a typical 1.3 mm flux density of {approx}25 mJy for 1 M{sub Sun} hosts and a power-law scaling L{sub mm}{proportional_to}M{sub *}{sup 1.5-2.0}. We suggest that a reasonable treatment of dust temperature in the conversion from L{sub mm} to M{sub d} favors an inherently linear M{sub d} {proportional_to}M{sub *} scaling, with a typical disk-to-star mass ratio of {approx}0.2%-0.6%. The measured rms dispersion around this regression curve is {+-}0.7 dex, suggesting that the combined effects of diverse evolutionary states, dust opacities, and temperatures in these disks imprint a full width at half-maximum range of a factor of {approx}40 on the inferred M{sub d} (or L{sub mm}) at any given host mass. We argue that this relationship between M{sub d} and M{sub *} likely represents the origin of the inferred correlation between giant planet frequency and host star mass in the exoplanet population, and provides some basic support for the core accretion model for planet formation. Moreover, we caution that the effects of incompleteness and selection bias must be considered in comparative studies of disk evolution, and illustrate that fact with statistical comparisons of f(L{sub mm}) between the Taurus catalog presented here and incomplete subsamples in the Ophiuchus, IC 348, and Upper Sco young clusters.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

Dissecting galaxy formation models with sensitivity analysis—a new approach to constrain the Milky Way formation history

We present an application of a statistical tool known as sensitivity analysis to characterize the relationship between input parameters and observational predictions of semi-analytic models of galaxy formation coupled to cosmological N-body simulations. We show how a sensitivity analysis can be performed on our chemo-dynamical model, ChemTreeN, to characterize and quantify its relationship between model input parameters and predicted observable properties. The result of this analysis provides the user with information about which parameters are most important and most likely to affect the prediction of a given observable. It can also be used to simplify models by identifying input parameters that have no effect on the outputs (i.e., observational predictions) of interest. Conversely, sensitivity analysis allows us to identify what model parameters can be most efficiently constrained by the given observational data set. We have applied this technique to real observational data sets associated with the Milky Way, such as the luminosity function of the dwarf satellites. The results from the sensitivity analysis are used to train specific model emulators of ChemTreeN, only involving the most relevant input parameters. This allowed us to efficiently explore the input parameter space. A statistical comparison of model outputs and real observables is used to obtain a 'best-fitting' parameter set. We consider different Milky-Way-like dark matter halos to account for the dependence of the best-fitting parameter selection process on the underlying merger history of the models. For all formation histories considered, running ChemTreeN with best-fitting parameters produced luminosity functions that tightly fit their observed counterpart. However, only one of the resulting stellar halo models was able to reproduce the observed stellar halo mass within 40 kpc of the Galactic center. On the basis of this analysis, it is possible to disregard certain models, and their corresponding merger histories, as good representations of the underlying merger history of the Milky Way.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

THE X-RAY FLUX DISTRIBUTION OF SAGITTARIUS A* AS SEEN BY CHANDRA

We present a statistical analysis of the X-ray flux distribution of Sgr A* from the Chandra X-Ray Observatory's 3 Ms Sgr A* X-ray Visionary Project in 2012. Our analysis indicates that the observed X-ray flux distribution can be decomposed into a steady quiescent component, represented by a Poisson process with rate Q = (5.24 ± 0.08) × 10{sup –3} counts s{sup –1}, and a variable component, represented by a power law process (dN/dF∝F {sup –ξ}, ξ=1.92{sub −0.02}{sup +0.03}). This slope matches our recently reported distribution of flare luminosities. The variability may also be described by a log-normal process with a median unabsorbed 2-8 keV flux of 1.8{sub −0.6}{sup +0.8}×10{sup −14} erg s{sup –1} cm{sup –2} and a shape parameter σ = 2.4 ± 0.2, but the power law provides a superior description of the data. In this decomposition of the flux distribution, all of the intrinsic X-ray variability of Sgr A* (spanning at least three orders of magnitude in flux) can be attributed to flaring activity, likely in the inner accretion flow. We confirm that at the faint end, the variable component contributes ∼10% of the apparent quiescent flux, as previously indicated by our statistical analysis of X-ray flares in these Chandra observations. Our flux distribution provides a new and important observational constraint on theoretical models of Sgr A*, and we use simple radiation models to explore the extent to which a statistical comparison of the X-ray and infrared can provide insights into the physics of the X-ray emission mechanism.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

THE DEGENERACY OF M33 MASS MODELING AND ITS PHYSICAL IMPLICATIONS

The Local Group galaxy M33 exhibits a regular spiral structure and is close enough to permit high resolution analysis of its kinematics, making it an ideal candidate for rotation curve studies of its inner regions. Previous studies have claimed the galaxy has a dark matter halo with an Navarro-Frenk-White profile, based on statistical comparisons with a small number of other profiles. We apply a Bayesian method from our previous paper to place the dark matter density profile in the context of a continuous, and more general, parameter space. For a wide range of initial assumptions we find that models with inner log slope γ{sub in} < 0.9 are strongly excluded by the kinematics of the galaxy unless the mass-to-light ratio of the stellar components in the 3.6 μm band satisfies Y{sub 3.6} ≥ 2. Such a high Y{sub 3.6} is inconsistent with current modeling of the stellar population of M33. This suggests that M33 is a galaxy whose dark matter halo has not been significantly modified by feedback. We discuss possible explanations of this result, including ram pressure stripping during earlier interactions with M31.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

Discovery and follow-up of rotating radio transients with the Green Bank and LOFAR telescopes

We have discovered 21 Rotating Radio Transients (RRATs) in data from the Green Bank Telescope (GBT) 350 MHz Drift-scan and the Green Bank North Celestial Cap pulsar surveys using a new candidate sifting algorithm. RRATs are pulsars with sporadic emission that are detected through their bright single pulses rather than Fourier domain searches. We have developed RRATtrap, a single-pulse sifting algorithm that can be integrated into pulsar survey data analysis pipelines in order to find RRATs and Fast Radio Bursts. We have conducted follow-up observations of our newly discovered sources at several radio frequencies using the GBT and Low Frequency Array, yielding improved positions and measurements of their periods, dispersion measures (DMs), and burst rates, as well as phase-coherent timing solutions for four of them. The new RRATs have DMs ranging from 15 to 97 pc cm{sup −3}, periods of 240 ms to 3.4 s, and estimated burst rates of 20 to 400 pulses hr{sup −1} at 350 MHz. We use this new sample of RRATs to perform statistical comparisons between RRATs and canonical pulsars in order to shed light on the relationship between the two populations. We find that the DM and spatial distributions of the RRATs agree with those of the pulsars found in the same survey. We find evidence that slower pulsars (i.e., P>200 ms) are preferentially more likely to emit bright single pulses than are faster pulsars (P<200 ms), although this conclusion is tentative. Our results are consistent with the proposed link between RRATs, transient pulsars, and canonical pulsars as sources in various parts of the pulse activity spectrum.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

Impact of the Cotton–Mouton effect on Faraday polarimetry measurements using circular polarization

Here, a comprehensive understanding of the impact of Cotton-Mouton Effect on Faraday polarimetry measurements using counter-rotating circular polarization probe beams has been developed. By using Jones theory, analytic study shows the Cotton-Mouton Effect cancels to first order with coupling into the Faraday measurement only at higher order. Jones-based numerical study shows the coupling effect strongly depends on the Cotton-Mouton Effect, Faraday Effect and wavelength chosen for the measurement. For realistic DIII-D plasma conditions and far-infrared wavelength, numerical calculation suggests the measurement is dominated by Faraday Effect while coupling effect leads to small but finite correction. By statistical comparison between experimental measurement and Jones-based numerical calculation under various plasma parameters, the impact of Cotton-Mouton Effect has been verified. Proper treatment of the coupling effect is essential in data analysis under certain conditions for polarimetric measurement using circular polarization in present devices and beyond.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Single Gaussian process method for arbitrary tokamak regimes with a statistical analysis

Abstract Gaussian process regression is a Bayesian method for inferring profiles based on input data. The technique is increasing in popularity in the fusion community due to its many advantages over traditional fitting techniques including intrinsic uncertainty quantification and robustness to over-fitting. This work investigates the use of a new method, the change-point method, for handling the varying length scales found in different tokamak regimes. The use of the Student’s t-distribution for the Bayesian likelihood probability is also investigated and shown to be advantageous in providing good fits in profiles with many outliers. To compare different methods, synthetic data generated from analytic profiles is used to create a database enabling a quantitative statistical comparison of which methods perform the best. Using a full Bayesian approach with the change-point method, Matérn kernel for the prior probability, and Student’s t-distribution for the likelihood is shown to give the best results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2012

Atmospheric dispersion modeling: Challenges of the Fukushima Daiichi response

In this research, the U.S. Department of Energy’s (DOE) National Atmospheric Release Advisory Center (NARAC) provided a wide range of predictions and analyses as part of the response to the Fukushima Daiichi Nuclear Power Plant accident including: daily Japanese weather forecasts and atmospheric transport predictions to inform planning for field monitoring operations and to provide U.S. government agencies with ongoing situational awareness of meteorological conditions; estimates of possible dose in Japan based on hypothetical U.S. Nuclear Regulatory Commission scenarios of potential radionuclide releases to support protective action planning for U.S. citizens; predictions of possible plume arrival times and dose levels at U.S. locations; and source estimation and plume model refinement based on atmospheric dispersion modeling and available monitoring data.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

New constraints on warm dark matter from the Lyman- α forest power spectrum

The forest of Lyman-α absorption lines detected in the spectra of distant quasars encodes information on the nature and properties of dark matter and the thermodynamics of diffuse baryonic material. Its main observable—the 1D flux power spectrum (FPS)—should exhibit a suppression on small scales and an enhancement on large scales in warm dark matter (WDM) cosmologies compared to standard Λ⁢CDM. Here, we present an unprecedented suite of 1080 high-resolution cosmological hydrodynamical simulations run with the graphics processing unit-accelerated code cholla to study the evolution of the Lyman-α forest under a wide range of physically motivated gas thermal histories along with different free-streaming lengths of WDM thermal relics in the early Universe. A statistical comparison of synthetic data with the forest FPS measured down to the smallest velocity scales ever probed at redshifts 4.0≲z≲5.2 [E. Boera et al., Revealing reionization with the thermal history of the intergalactic medium: New constraints from the Ly⁢α flux power spectrum, Astrophys. J. 872, 101 (2019)] yields a lower-limit m WDM >3.1 keV (95% C.L.) for the WDM particle mass and constrains the amplitude and spectrum of the photoheating and photoionizing background produced by star-forming galaxies and active galactic nuclei at these redshifts. Interestingly, our Bayesian inference analysis appears to weakly favor WDM models with a peak likelihood value at the thermal relic mass of m WDM =4.5 keV. In conclusion, we find that the suppression of the FPS from free-streaming saturates at k≳0.1 s km -1 because of peculiar velocity smearing, and this saturated suppression combined with a slightly lower gas temperature provides a moderately better fit to the observed small-scale FPS for WDM cosmologies.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

DNA Viral Diversity, Abundance, and Functional Potential Vary across Grassland Soils with a Range of Historical Moisture Regimes

Soil viruses are abundant, but the influence of the environment and climate on soil viruses remains poorly understood. Here, we addressed this gap by comparing the diversity, abundance, lifestyle, and metabolic potential of DNA viruses in three grassland soils with historical differences in average annual precipitation, low in eastern Washington (WA), high in Iowa (IA), and intermediate in Kansas (KS). Bioinformatics analyses were applied to identify a total of 2,631 viral contigs, including 14 complete viral genomes from three deep metagenomes (1 terabase [Tb] each) that were sequenced from bulk soil DNA. An additional three replicate metagenomes (~0.5 Tb each) were obtained from each location for statistical comparisons. Identified viruses were primarily bacteriophages targeting dominant bacterial taxa. Both viral and host diversity were higher in soil with lower precipitation. Viral abundance was also significantly higher in the arid WA location than in IA and KS. More lysogenic markers and fewer clustered regularly interspaced short palindromic repeats (CRISPR) spacer hits were found in WA, reflecting more lysogeny in historically drier soil. More putative auxiliary metabolic genes (AMGs) were also detected in WA than in the historically wetter locations. The AMGs occurring in 18 pathways could potentially contribute to carbon metabolism and energy acquisition in their hosts. Structural equation modeling (SEM) suggested that historical precipitation influenced viral life cycle and selection of AMGs. The observed and predicted relationships between soil viruses and various biotic and abiotic variables have value for predicting viral responses to environmental change.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

AI-Batt (Autonomous Identification of Battery Life Models) [SWR 21-36]

Autonomous Identification of Battery Life Models (AI-Batt) AI-Batt is a MATLAB code base for developing lifetime models for batteries from accelerated aging data. The code base provides many functions for processing, visualizing, and modeling battery aging data, making the data processing, exploration, and modeling workflow substantially faster. These tools are tailored for working with battery aging data sets, which usually consist of many separate time-series for each cell, with many test conditions and possible replicates at each condition, which makes it difficult to simply process or visualize the data set. Complex modeling tasks, such as cross-validation, sensitivity analysis, and uncertainty quantification have been implemented to enable thorough statistical investigation of model predictions. Additionally, several machine-learning algorithms are implemented to autonomously identify suitable models via symbolic regression. Data processing functions automatically cast data from the struct data type, which is commonly used to store experimental data, but is not an acceptable input for most algorithms, to the table data type, which can be easily used as input to any optimization algorithm. Also, the data can be separated into time-invariant and time-variant data tables, which is helpful for exploring the data set as well as developing separate models for time-variant and time-invariant aging mechanisms. For example, in aging tests with constant temperature, temperature is a time-invariant experimental condition. Visualization tools enable plotting of data, model fits, and model simulations possible with single-line function calls, empowering data exploration of complex data sets with both time-varying and time-invariant trends. Plots can be automatically generated for the whole data set, or separated by data group (groups of test replicates) or individual data series. Data points or data series can be automatically colored by the value of a variable with a variety of color maps, and model predictions can also be colored by the value of a fit statistic. Comparisons between data sets and the predictions/simulations of different models on the same data set can be easily plotted as well. Distributions of parameter values from bootstrap resampling can be plotted to visualize the reliability of parameter estimation, or determine any correlations between parameters. Modeling tools handle the complex task of creating and parsing symbolic equations for modeling battery lifetime. Equations are parsed to grab relevant data variables, parameter values, or specified sub-models for input into optimization, evaluation, or simulation functions. Models can be optimized locally (one set of parameters for each data series), bi-level (some parameters shared across the data set), or globally (single set of parameters for all data). Functions implementing symbolic regression algorithms help users to discover effective model equations, even in poorly sampled, high-dimensional data.

Smith, Kandler↗

DOE OSTI2022

Three-Dimensional Convective–Stratiform Echo-Type Classification and Convectivity Retrieval from Radar Reflectivity

The Echo Classification from COnvectivity (ECCO) algorithm identifies convective and stratiform types of radar echo in three dimensions. It is based on the calculation of reflectivity texture—a combination of the intensity and the heterogeneity of the radar echoes on each horizontal plane in a 3D Cartesian volume. Reflectivity texture is translated into convectivity, which is designed to be a quantitative measure of the convective nature of each 3D radar grid point. It ranges from 0 (100% stratiform) to 1 (100% convective). By thresholding convectivity, a more traditional qualitative categorization is obtained, which classifies radar echoes as convective, mixed, or stratiform. In contrast to previous algorithms, these echo-type classifications are provided on the full 3D grid of the reflectivity field. The vertically resolved classifications, in combination with temperature data, allow for subclassifications into shallow, mid-, deep, and elevated convective features, and low, mid-, and high stratiform regions—again in three dimensions. The algorithm was validated using datasets collected over the U.S. Great Plains during the PECAN field campaign. An analysis of lightning counts shows ~90% of lightning occurring in regions classified as convective by ECCO. A statistical comparison of ECCO echo types with the well-established GPM radar precipitation-type categories show 84% (88%) of GPM stratiform (convective) echo being classified as stratiform (convective) or mixed by ECCO. ECCO was applied to radar grids for the continental United States, the United Arab Emirates, Australia, and Europe, illustrating its robustness and adaptability to different radar grid characteristics and climatic regions.

Radars/Radar observations↗

DOE OSTI2017

Peering through the flames: imaging techniques for reacting aluminum powders

Combusting metals burn at high temperatures and emit high-intensity radiation in the visible spectrum which can over-saturate regular imaging sensors and obscure the field of view. Filtering the luminescence can result in limited information and hinder thorough combustion characterization. A method for “seeing through the flames” of a highly luminescent aluminum powder reaction is presented using copper vapor laser (CVL) illumination synchronized with a high-speed camera. A statistical comparison of combusting aluminum particle agglomerate between filtered halogen and CVL illumination shows the effectiveness of this diagnostic approach. When ignited by an electrically induced plasma, aluminum particles are entrained as solid agglomerates that rotate about their centers of mass and are surrounded by emitted, burning gases. Furthermore, the average agglomerate diameter appears to be 160 micrometers when viewed with standard illumination and a high-speed camera. But, a significantly lower diameter of 50 micrometers is recorded when imaged with CVL illumination. Our results advocate that alternative imaging techniques are required to resolve the complexities of metal particle combustion.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Three-Dimensional Electromagnetic High Frequency Axisymmetric Cavity Scars

This report examines the localization of high frequency electromagnetic fields in three-dimensional axisymmetric cavities along periodic paths between opposing sides of the cavity. The cases where these orbits lead to unstable localized modes are known as scars. This report treats both the case where the opposing sides, or mirrors, are convex, where there are no interior foci, and the case where they are concave, leading to interior foci. The scalar problem is treated first but the approximations required to treat the vector field components are also examined. Particular attention is focused on the normalization through the electromagnetic energy theorem. Both projections of the field along the scarred orbit as well as point statistics are examined. Statistical comparisons are made with a numerical calculation of the scars run with an axisymmetric simulation. This axisymmetric case forms the opposite extreme (where the two mirror radii at each end of the ray orbit are equal) from the two-dimensional solution examined previously (where one mirror radius is vastly different from the other). The enhancement of the field on the orbit axis can be larger here than in the two-dimensional case.

Warne, Larry Kevin↗