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DOE OSTI2016

LOW X-RAY LUMINOSITY GALAXY CLUSTERS: MAIN GOALS, SAMPLE SELECTION, PHOTOMETRIC AND SPECTROSCOPIC OBSERVATIONS

We present our study of 19 low X-ray luminosity galaxy clusters (L{sub X} ∼ 0.5–45 × 10{sup 43} erg s{sup −1}), selected from the ROSAT Position Sensitive Proportional Counters Pointed Observations and the revised version of Mullis et al. in the redshift range of 0.16–0.7. This is the introductory paper of a series presenting the sample selection, photometric and spectroscopic observations, and data reduction. Photometric data in different passbands were taken for eight galaxy clusters at Las Campanas Observatory; three clusters at Cerro Tololo Interamerican Observatory; and eight clusters at the Gemini Observatory. Spectroscopic data were collected for only four galaxy clusters using Gemini telescopes. Using the photometry, the galaxies were defined based on the star-galaxy separation taking into account photometric parameters. For each galaxy cluster, the catalogs contain the point-spread function and aperture magnitudes of galaxies within the 90% completeness limit. They are used together with structural parameters to study the galaxy morphology and to estimate photometric redshifts. With the spectroscopy, the derived galaxy velocity dispersion of our clusters ranged from 507 km s{sup −1} for [VMF98]022 to 775 km s{sup −1} for [VMF98]097 with signs of substructure. Cluster membership has been extensively discussed taking into account spectroscopic and photometric redshift estimates. In this sense, members are the galaxies within a projected radius of 0.75 Mpc from the X-ray emission peak and with clustercentric velocities smaller than the cluster velocity dispersion or 6000 km s{sup −1}, respectively. These results will be used in forthcoming papers to study, among the main topics, the red cluster sequence, blue cloud and green populations, the galaxy luminosity function, and cluster dynamics.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

A Circularity Assessment for Silicon Solar Panels Based on Dynamic Material Flow Analysis

Solar photovoltaics (PV) are the fastest growing renewable energy technology for clean, inexpensive, and sustainable electricity generation. Along with numerous technical roadmaps to improve system cost, performance and reliability, the PV industry should also plan to handle large volumes of silicon panel waste, which is initially estimated to be ~13 million metric tons (MT) by 2050 in the U.S. alone. Understanding the magnitude of material needs and how material flows throughout the PV panel life cycle could respond to design, operational and different end-of-life (EOL) circular pathways will help transition into a circular, resource-conserving economy. Herein, we introduce a dynamic material flow analysis (DMFA) framework based on electricity generation to quantify time-series stocks and flows of bulk PV materials (e.g., solar glass and aluminum frames) throughout the life cycles of utility-scale silicon PV systems in the U.S. in the period 2000-2100. We apply the model to a range of scenarios to understand how material demands depend on selected PV-related parameters, different material circularity strategies, and recent module design trends (e.g., bifacial, frameless). We found that float glass and aluminum in PV installations would likely reach 100 million MT and 12 million MT by 2100, respectively, in the baseline scenario. The most influential parameters for PV installation and subsequent waste reduction are found to be module lifetime, module efficiency, annual degradation, and material reduction. Module recycling and component remanufacturing were found to be the most effective material circularity strategies for waste minimization. Panel reuse has negligible savings on waste under current module efficiencies compared to replacements with newer generations with higher efficiency. Ongoing trends to produce larger power frameless modules could save 10 million MT of glass and ~9 million MT of aluminum. Our results enable advanced planning for future materials needs and provide insight into potential opportunities to minimize waste.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

A Circularity Assessment for Silicon Solar Panels Based on Dynamic Material Flow Analysis: Preprint

circular economy↗

DOE OSTI2023

Emissions minimization on road networks via Generic Second Order Models

In this paper we consider the problem of estimating emissions due to vehicular traffic on complex networks, and minimizing their effect by regulating traffic at junctions. For the traffic evolution, we consider a Generic Second Order Model, which encompasses the majority of two-equations (i.e., second-order) models available in the literature, and extend it to road networks with merge and diverge junctions. The dynamics on the whole network is determined by selecting a solution to the Riemann Problems at junctions, i.e., the Cauchy problems with constant initial data on each incident road. The latter are solved by assuming the maximization of the flow and assigning a traffic distribution coefficient for outgoing roads of diverges, and a priority rule for incoming roads of merges. A general emission model is considered and its parameters are tuned to the $ {\mathrm{NO_{x}}} $ emission rate. The minimization of emissions is then formulated in terms of the traffic distribution and priority parameters, taking into account travel times. A comparison is provided between roundabouts with optimized parameters and traffic lights, which correspond to time-varying traffic priorities. Our approach can be adapted to manage traffic in complex networks in order to reduce emissions while keeping travel time at acceptable levels.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2016

TIME-VARIABLE ALUMINUM ABSORPTION IN THE POLAR AR URSAE MAJORIS, AND AN UPDATED ESTIMATE FOR THE MASS OF THE WHITE DWARF

We present spectra of the extreme polar AR Ursae Majoris (AR UMa), which display a clear Al i absorption doublet, alongside spectra taken less than a year earlier in which that feature is not present. Re-examination of earlier SDSS spectra indicates that the Al i absorption doublet was also present ≈8 years before our first non-detection. We conclude that this absorbing material is unlikely to be on the surface of either the white dwarf (WD) or the donor star. We suggest that this Al i absorption feature arises in circumstellar material, perhaps produced by the evaporation of asteroids as they approach the hot WD. The presence of any remaining reservoir of rocky material in AR UMa might help to constrain the prior evolution of this unusual binary system. We also apply spectral decomposition to find the stellar parameters of the M dwarf companion, and attempt to dynamically measure the mass of the WD in AR UMa by considering both the radial velocity curves of the H {sub β} emission line and the Na i absorption line. Thereby we infer a mass range for the WD in AR UMa of 0.91 M {sub ⊙} < M {sub WD} < 1.24 M {sub ⊙}.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

A new ionospheric electron precipitation module coupled with RAM-SCB within the geospace general circulation model

Electron precipitation down to the atmosphere due to wave-particle scattering in the magnetosphere contributes significantly to the auroral ionospheric conductivity. In order to obtain the auroral conductivity in global MHD models that are incapable of capturing kinetic physics in the magnetosphere, MHD parameters are often used to estimate electron precipitation flux for the conductivity calculation. Such an MHD approach, however, lacks self-consistency in representing the magnetosphere-ionosphere coupling processes. In this study we improve the coupling processes in global models with a more physical method. We calculate the physics-based electron precipitation from the ring current and map it to the ionospheric altitude for solving the ionospheric electrodynamics. In particular, we use the BATS-R-US (Block Adaptive Tree Scheme-Roe type-Upstream) MHD model coupled with the kinetic ring current model RAM-SCB (Ring current-Atmosphere interaction Model with Self-Consistent Magnetic field (B)) that solves pitch angle-dependent electron distribution functions, to study the global circulation dynamics during the 25–26 January 2013 storm event. Since the electron precipitation loss is mostly governed by wave-particle resonant scattering in the magnetosphere, we further investigate two loss methods of specifying electron precipitation loss associated with wave-particle interactions: (1) using pitch angle diffusion coefficients D αα (E,α) determined from the quasi-linear theory, with wave spectral and plasma density obtained from statistical observations (named as “diffusion coefficient method”) and (2) using electron lifetimes τ(E) independent on pitch angles inferred from the above diffusion coefficients (named as “lifetime method”). We found that both loss methods demonstrate similar temporal evolution of the trapped ring current electrons, indicating that the impact of using different kinds of loss rates is small on the trapped electron population. Furthermore, for the precipitated electrons, the lifetime method hardly captures any precipitation in the large L shell (i.e., 4 < L < 6.5) region, while the diffusion coefficient method produces much better agreement with NOAA/POES measurements, including the spatial distribution and temporal evolution of electron precipitation in the region from the premidnight through the dawn to the dayside. Further comparisons of the precipitation energy flux to DMSP observations indicates that the new physics-based precipitation approach using diffusion coefficients for the ring current electron loss can explain the diffuse electron precipitation in the dawn sector, such as the enhanced precipitation flux at auroral latitudes and flux drop near the subauroral latitudes, but the traditional MHD approach largely overestimates the precipitation flux at lower latitudes.

58 GEOSCIENCES↗

DOE OSTI2016

A critical appraisal of the zero-multipole method: Structural, thermodynamic, dielectric, and dynamical properties of a water system

We performed extensive and strict tests for the reliability of the zero-multipole (summation) method (ZMM), which is a method for estimating the electrostatic interactions among charged particles in a classical physical system, by investigating a set of various physical quantities. This set covers a broad range of water properties, including the thermodynamic properties (pressure, excess chemical potential, constant volume/pressure heat capacity, isothermal compressibility, and thermal expansion coefficient), dielectric properties (dielectric constant and Kirkwood-G factor), dynamical properties (diffusion constant and viscosity), and the structural property (radial distribution function). We selected a bulk water system, the most important solvent, and applied the widely used TIP3P model to this test. In result, the ZMM works well for almost all cases, compared with the smooth particle mesh Ewald (SPME) method that was carefully optimized. In particular, at cut-off radius of 1.2 nm, the recommended choices of ZMM parameters for the TIP3P system are α ≤ 1 nm{sup −1} for the splitting parameter and l = 2 or l = 3 for the order of the multipole moment. We discussed the origin of the deviations of the ZMM and found that they are intimately related to the deviations of the equilibrated densities between the ZMM and SPME, while the magnitude of the density deviations is very small.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2013

Investigation on the Core Bypass Flow in a Very High Temperature Reactor

Uncertainties associated with the core bypass flow are some of the key issues that directly influence the coolant mass flow distribution and magnitude, and thus the operational core temperature profiles, in the very high-temperature reactor (VHTR). Designers will attempt to configure the core geometry so the core cooling flow rate magnitude and distribution conform to the design values. The objective of this project is to study the bypass flow both experimentally and computationally. Researchers will develop experimental data using state-of-the-art particle image velocimetry in a small test facility. The team will attempt to obtain full field temperature distribution using racks of thermocouples. The experimental data are intended to benchmark computational fluid dynamics (CFD) codes by providing detailed information. These experimental data are urgently needed for validation of the CFD codes. The following are the project tasks: (1) Construct a small-scale bench-top experiment to resemble the bypass flow between the graphite blocks, varying parameters to address their impact on bypass flow. Wall roughness of the graphite block walls, spacing between the blocks, and temperature of the blocks are some of the parameters to be tested. (2) Perform CFD to evaluate pre- and post-test calculations and turbulence models, including sensitivity studies to achieve high accuracy. (3) Develop the state-of-the art large eddy simulation (LES) using appropriate subgrid modeling. (4) Develop models to be used in systems thermal hydraulics codes to account and estimate the bypass flows. These computer programs include, among others, RELAP3D, MELCOR, GAMMA, and GAS-NET. Actual core bypass flow rate may vary considerably from the design value. Although the uncertainty of the bypass flow rate is not known, some sources have stated that the bypass flow rates in the Fort St. Vrain reactor were between 8 and 25 percent of the total reactor mass flow rate. If bypass flow rates are on the high side, the quantity of cooling flow through the core may be considerably less than the nominal design value, causing some regions of the core to operate at temperatures in excess of the design values. These effects are postulated to lead to localized hot regions in the core that must be considered when evaluating the VHTR operational and accident scenarios.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2013

Analysis of High Order Modes in 1.3 GHZ CW SRF Electron Linac for a Light Source

Design of a Light Source (LS) based on the continuous wave superconducting RF (CW SRF) electron linac is currently underway. This facility will provide soft coherent X-ray radiation for a braod spectrum of basic research applications. Quality of the X-ray laser radiation is affected by the electron beam parameters such as the stability of the transverse beam position and longitudinal and transverse beam emittances. High order modes (HOMs) excited in the SRF structures by a passing beam may deteriorate the beam quality and affect the beam stability. Deposition of HOM energy in the walls of SRF cavities adds to the heat load of he cryogenic system and leads to the increased cost of building and operation of the linac. In this paper we evaluate effects of HOMs in an LS CW SRF linac based on Tesla-type 9-cell 1.3 GHz cavities. We analyze non-coherent losses and resonance excitation of HOMs. We estimate heat load due to the very high frequency HOMs. We study influence of the HOMs on the transverse beam dynamics.

43 PARTICLE ACCELERATORS↗

DOE OSTI2020

Active- and transfer-learning applied to microscale-macroscale coupling to simulate viscoelastic flows

Active- and transfer-learning are applied to microscale dynamics of polymer flows for the multiscale discovery of effective constitutive approximations required in viscoelastic flow simulation. The result is macroscopic rheology directly connected to a microstructural model. Micro and macroscale simulations are adaptively coupled by means of Gaussian process regression (GPR) to run the expensive microscale computations only as necessary. This multiscale method is demonstrated with flows of a polymer solution as a model system. At the microscale level dissipative particle dynamics (DPD) is employed to model the fluid as a suspension of bead-spring micro-structures subjected to steady shear flow. The results yield the non-Newtonian viscosity and the first normal stress difference at strain rates as training data used in a GPR model. DPD parameters are calibrated with respect to experimental data for a real polymer solution. Compliance with these data requires adjustment of the DPD model's cutoff radius, which then becomes a function of the second invariant of the strain rate tensor. The FENE-P model is chosen for the macroscale description using the spectral element method (SEM) to simulate channel flow and flow past a circular cylinder. The DPD results at the lowest possible shear strain rate yield an estimate of the zero-shear rate viscosity, which allows the initiation of the macroscale flow by SEM as a Newtonian fluid. The resulting strain-rate field is surveyed to determine additional shear strain rate sampling points for the DPD system. This new information allows an initial fitting of parameters of the constitutive equation followed by new SEM simulations at the macroscale. Additionally, guided by active-learning GPR to select new sampling points, this process continues until convergence is achieved. The effectiveness of this new simulation paradigm for viscoelastic flows is tested with different macroscale operating conditions. The effective closure learned in the channel simulation is then transferred directly to the flow past a circular cylinder at low Reynolds number, where the results show that only two additional DPD simulations are required to achieve a satisfactory constitutive model. With an increase of the Reynolds number, the active-learning scheme automatically detects the inaccuracy of the learned constitutive model, and initiates additional DPD simulations for the extra data needed to once again close the microscale-macroscale coupled system. This new paradigm of active- and transfer-learning for multiscale modeling is readily applicable to other microscale-macroscale coupled simulations of complex fluids and other materials. Furthermore, the coupling between microscale and macroscale solvers can be seamlessly implemented with our open source multiscale universal interface (MUI) library.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Estimating the color lifetime of energetic quarks

Using a simple geometric framework with a realistic nuclear density distribution, we fit published HERMES data to determine fundamental properties of hadronization using the nuclear medium as a spatial analyzer. Our approach uses a fit to the transverse momentum broadening observable and the hadronic multiplicity ratio; the simultaneous fit to two different observables strongly constrains the outcome. Using the known sizes of the target nuclei, we extract the color lifetime, finding a z h -dependent range of values from 2 to 8 fm/c for these data. We also extract estimates for the qˆ transport coefficient characterizing the strength of the interaction between the quark and the cold nuclear medium, finding an average value of 0.035±0.011 GeV 2 /fm. With a three-parameter model we obtain satisfactory fits to the data with a goodness-of-fit parameter χ 2 /dof of 1.1 or less. In a secondary fit of the results from that model we independently find a value for the Lund String Model string tension of 1.00±0.05 GeV/fm. We evaluated the sensitivity for extracting quark energy loss and effective in-medium hadronic cross sections using four-parameter variants of the model, finding large uncertainties in both cases. Our results suggest that hadronic interaction of forming hadrons in the nuclear medium is the primary dynamical cause of meson attenuation in the HERMES data, with quark energy loss playing a more minor role.

Electron-ion collider↗

DOE OSTI2017

Scaling from gauge and scalar radiation in Abelian-Higgs string networks

In this work, we investigate cosmic string networks in the Abelian Higgs model using data from a campaign of large-scale numerical simulations on lattices of up to 409 6 3 grid points. We observe scaling or self-similarity of the networks over a wide range of scales and estimate the asymptotic values of the mean string separation in horizon length units ξ ˙ and of the mean square string velocity v ¯ 2 in the continuum and large time limits. The scaling occurs because the strings lose energy into classical radiation of the scalar and gauge fields of the Abelian Higgs model. We quantify the energy loss with a dimensionless radiative efficiency parameter and show that it does not vary significantly with lattice spacing or string separation. This implies that the radiative energy loss underlying the scaling behavior is not a lattice artifact, and justifies the extrapolation of measured network properties to large times for computations of cosmological perturbations. We also show that the core growth method, which increases the defect core width with time to extend the dynamic range of simulations, does not introduce significant systematic error. We compare ξ ˙ and v ¯ 2 to values measured in simulations using the Nambu-Goto approximation, finding that the latter underestimate the mean string separation by about 25%, and overestimate v ¯ 2 by about 10%. The scaling of the string separation implies that string loops decay by the emission of massive radiation within a Hubble time in field theory simulations, in contrast to the Nambu-Goto scenario which neglects this energy loss mechanism. String loops surviving for only one Hubble time emit much less gravitational radiation than in the Nambu-Goto scenario and are consequently subject to much weaker gravitational wave constraints on their tension.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Simulating organic aerosol in Delhi with WRF-Chem using the volatility-basis-set approach: exploring model uncertainty with a Gaussian process emulator

The nature and origin of organic aerosol in the atmosphere remain unclear. The gas–particle partitioning of semi-volatile organic compounds (SVOCs) that constitute primary organic aerosols (POAs) and the multigenerational chemical aging of SVOCs are particularly poorly understood. The volatility basis set (VBS) approach, implemented in air quality models such as WRF-Chem (Weather Research and Forecasting model with Chemistry), can be a useful tool to describe emissions of POA and its chemical evolution. However, the evaluation of model uncertainty and the optimal model parameterization may be expensive to probe using only WRF-Chem simulations. Gaussian process emulators, trained on simulations from relatively few WRF-Chem simulations, are capable of reproducing model results and estimating the sources of model uncertainty within a defined range of model parameters. In this study, a WRF-Chem VBS parameterization is proposed; we then generate a perturbed parameter ensemble of 111 model runs, perturbing 10 parameters of the WRF-Chem model relating to organic aerosol emissions and the VBS oxidation reactions. This allowed us to cover the model's uncertainty space and to compare outputs from each run to aerosol mass spectrometer observations of organic aerosol concentrations and O:C ratios measured in New Delhi, India. The simulations spanned the organic aerosol concentrations measured with the aerosol mass spectrometer (AMS). However, they also highlighted potential structural errors in the model that may be related to unsuitable diurnal cycles in the emissions and/or failure to adequately represent the dynamics of the planetary boundary layer. While the structural errors prevented us from clearly identifying an optimized VBS approach in WRF-Chem, we were able to apply the emulator in the following two periods: the full period (1–29 May) and a subperiod period of 14:00–16:00 h LT (local time) on 1–29 May. The combination of emulator analysis and model evaluation metrics allowed us to identify plausible parameter combinations for the analyzed periods. We demonstrate that the methodology presented in this study can be used to determine the model uncertainty and to identify the appropriate parameter combination for the VBS approach and hence to provide valuable information to improve our understanding of OA production.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

{sup 18}F-FLT uptake kinetics in head and neck squamous cell carcinoma: A PET imaging study

Purpose: To analyze the kinetics of 3{sup ′}-deoxy-3{sup ′}-[F-18]-fluorothymidine (18F-FLT) uptake by head and neck squamous cell carcinomas and involved nodes imaged using positron emission tomography (PET). Methods: Two- and three-tissue compartment models were fitted to 12 tumor time-activity-curves (TACs) obtained for 6 structures (tumors or involved nodes) imaged in ten dynamic PET studies of 1 h duration, carried out for five patients. The ability of the models to describe the data was assessed using a runs test, the Akaike information criterion (AIC) and leave-one-out cross-validation. To generate parametric maps the models were also fitted to TACs of individual voxels. Correlations between maps of different parameters were characterized using Pearson'sr coefficient; in particular the phosphorylation rate-constants k{sub 3-2tiss} and k{sub 5} of the two- and three-tissue models were studied alongside the flux parameters K{sub FLT-2tiss} and K{sub FLT} of these models, and standardized uptake values (SUV). A methodology based on expectation-maximization clustering and the Bayesian information criterion (“EM-BIC clustering”) was used to distil the information from noisy parametric images. Results: Fits of two-tissue models 2C3K and 2C4K and three-tissue models 3C5K and 3C6K comprising three, four, five, and six rate-constants, respectively, pass the runs test for 4, 8, 10, and 11 of 12 tumor TACs. The three-tissue models have lower AIC and cross-validation scores for nine of the 12 tumors. Overall the 3C6K model has the lowest AIC and cross-validation scores and its fitted parameter values are of the same orders of magnitude as literature estimates. Maps ofK{sub FLT} and K{sub FLT-2tiss} are strongly correlated (r = 0.85) and also correlate closely with SUV maps (r = 0.72 for K{sub FLT-2tiss}, 0.64 for K{sub FLT}). Phosphorylation rate-constant maps are moderately correlated with flux maps (r = 0.48 for k{sub 3-2tiss} vs K{sub FLT-2tiss} and r = 0.68 for k{sub 5} vs K{sub FLT}); however, neither phosphorylation rate-constant correlates significantly with SUV. EM-BIC clustering reduces the parametric maps to a small number of levels—on average 5.8, 3.5, 3.4, and 1.4 for K{sub FLT-2tiss}, K{sub FLT}, k{sub 3-2tiss}, and k{sub 5.} This large simplification is potentially useful for radiotherapy dose-painting, but demonstrates the high noise in some maps. Statistical simulations show that voxel level noise degrades TACs generated from the 3C6K model sufficiently that the average AIC score, parameter bias, and total uncertainty of 2C4K model fits are similar to those of 3C6K fits, whereas at the whole tumor level the scores are lower for 3C6K fits. Conclusions: For the patients studied here, whole tumor FLT uptake time-courses are represented better overall by a three-tissue than by a two-tissue model. EM-BIC clustering simplifies noisy parametric maps, providing the best description of the underlying information they contain and is potentially useful for radiotherapy dose-painting. However, the clustering highlights the large degree of noise present in maps of the phosphorylation rate-constantsk{sub 5} and k{sub 3-2tiss}, which are conceptually tightly linked to cellular proliferation. Methods must be found to make these maps more robust—either by constraining other model parameters or modifying dynamic imaging protocols.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2013

Stochastic modeling of sunshine number data

In this paper, we will present a unified statistical modeling framework for estimation and forecasting sunshine number (SSN) data. Sunshine number has been proposed earlier to describe sunshine time series in qualitative terms (Theor Appl Climatol 72 (2002) 127-136) and since then, it was shown to be useful not only for theoretical purposes but also for practical considerations, e.g. those related to the development of photovoltaic energy production. Statistical modeling and prediction of SSN as a binary time series has been challenging problem, however. Our statistical model for SSN time series is based on an underlying stochastic process formulation of Markov chain type. We will show how its transition probabilities can be efficiently estimated within logistic regression framework. In fact, our logistic Markovian model can be relatively easily fitted via maximum likelihood approach. This is optimal in many respects and it also enables us to use formalized statistical inference theory to obtain not only the point estimates of transition probabilities and their functions of interest, but also related uncertainties, as well as to test of various hypotheses of practical interest, etc. It is straightforward to deal with non-homogeneous transition probabilities in this framework. Very importantly from both physical and practical points of view, logistic Markov model class allows us to test hypotheses about how SSN dependents on various external covariates (e.g. elevation angle, solar time, etc.) and about details of the dynamic model (order and functional shape of the Markov kernel, etc.). Therefore, using generalized additive model approach (GAM), we can fit and compare models of various complexity which insist on keeping physical interpretation of the statistical model and its parts. After introducing the Markovian model and general approach for identification of its parameters, we will illustrate its use and performance on high resolution SSN data from the Solar Radiation Monitoring Station of the West University of Timisoara.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2013

CHARACTERIZATION OF INTRACLUSTER MEDIUM TEMPERATURE DISTRIBUTIONS OF 62 GALAXY CLUSTERS WITH XMM-NEWTON

We measure the intracluster medium (ICM) temperature distributions for 62 galaxy clusters in the HIFLUGCS, an X-ray flux-limited sample, with available X-ray data from XMM-Newton. We search for correlations between the width of the temperature distributions and other cluster properties, including median cluster temperature, luminosity, size, presence of a cool core, active galactic nucleus (AGN) activity, and dynamical state. We use a Markov Chain Monte Carlo analysis, which models the ICM as a collection of X-ray emitting smoothed particles of plasma. Each smoothed particle is given its own set of parameters, including temperature, spatial position, redshift, size, and emission measure. This allows us to measure the width of the temperature distribution, median temperature, and total emission measure of each cluster. We find that none of the clusters have a temperature width consistent with isothermality. Counterintuitively, we also find that the temperature distribution widths of disturbed, non-cool-core, and AGN-free clusters tend to be wider than in other clusters. A linear fit to {sigma} {sub kT}-kT {sub med} finds {sigma} {sub kT} {approx} 0.20kT {sub med} + 1.08, with an estimated intrinsic scatter of {approx}0.55 keV, demonstrating a large range in ICM thermal histories.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

A COMPARISON OF THE INTENSITIES AND ENERGIES OF GRADUAL SOLAR ENERGETIC PARTICLE EVENTS WITH THE DYNAMICAL PROPERTIES OF ASSOCIATED CORONAL MASS EJECTIONS

Gradual solar energetic particle (SEP) events observed at 1 AU are produced by shocks driven by coronal mass ejections (CMEs). Characterizations of the remotely imaged CMEs and of their associated SEP events observed in situ can be used to increase our ability to forecast SEP events and to understand better the physical connections between the two phenomena. We carry out a statistical comparison of the peak intensities Ip20, of 120 western-hemisphere 20 MeV SEP events with those of their associated CMEs observed by the Solar and Heliospheric Observatory/Large Angle and Spectrometric Coronagraph over the past solar cycle. For a subset of 96 events observed with the EPACT instrument on the Wind spacecraft we also compare the SEP 2 MeV peak intensities Ip2, power-law energy spectral exponents {gamma}, total SEP energies Esep, and 2 MeV nuc{sup -1} H/He ratios with CME properties. New analyses of white-light CME images enable us to improve calculations of the CME masses and potential energies and then to determine two values of their kinetic energies based on frontal V (fr) and center-of-mass V (cm) speeds. Despite considerable scatter in the SEP and CME data, the large dynamical ranges of both the SEP and CME parameters allow us to determine statistical trends in the comparisons of the logs of the parameters. Ip2, Ip20, and Esep are significantly correlated with CME kinetic energies, masses, and speeds, while {gamma} trends lower (harder). Those correlations are higher with V (fr) than with V (cm) parameters, indicating a less significant role for the body of the CME than for the CME front in SEP production. The high ratios ({>=}10%) of Esep to CME energies found by Mewaldt et al. are confirmed, and the fits are consistent with a linear relationship between the two energies. The 2 MeV nuc{sup -1} H/He ratios decrease with increasing CME speeds, which may be an effect of shock geometry. We discuss several factors that limit the estimates of both the SEP and CME energies.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

Global energetics of solar flares. II. Thermal energies

We present the second part of a project on the global energetics of solar flares and coronal mass ejections that includes about 400 M- and X-class flares observed with the Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO) during the first 3.5 yr of its mission. In this Paper II we compute the differential emission measure (DEM) distribution functions and associated multithermal energies, using a spatially-synthesized Gaussian DEM forward-fitting method. The multithermal DEM function yields a significantly higher (by an average factor of ≈14), but more comprehensive (multi-)thermal energy than an isothermal energy estimate from the same AIA data. We find a statistical energy ratio of E{sub th}/E{sub diss} ≈ 2–40% between the multithermal energy E{sub th} and the magnetically dissipated energy E{sub diss}, which is an order of magnitude higher than the estimates of Emslie et al. 2012. For the analyzed set of M- and X-class flares we find the following physical parameter ranges: L=10{sup 8.2}−10{sup 9.7} cm for the length scale of the flare areas, T{sub p}=10{sup 5.7}−10{sup 7.4} K for the DEM peak temperature, T{sub w}=10{sup 6.8}−10{sup 7.6} K for the emission measure-weighted temperature, n{sub p}=10{sup 10.3}−10{sup 11.8} cm{sup −3} for the average electron density, EM{sub p}=10{sup 47.3}−10{sup 50.3} cm{sup −3} for the DEM peak emission measure, and E{sub th}=10{sup 26.8}−10{sup 32.0} erg for the multithermal energies. The deduced multithermal energies are consistent with the RTV scaling law E{sub th,RTV}=7.3×10{sup −10} T{sub p}{sup 3}L{sub p}{sup 2}, which predicts extremal values of E{sub th,max}≈1.5×10{sup 33} erg for the largest flare and E{sub th,min}≈1×10{sup 24} erg for the smallest coronal nanoflare. The size distributions of the spatial parameters exhibit powerlaw tails that are consistent with the predictions of the fractal-diffusive self-organized criticality model combined with the RTV scaling law.

79 ASTRONOMY AND ASTROPHYSICS↗