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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Improving Cloud Optical Property Retrievals for Partly Cloudy Pixels Using Coincident Higher-Resolution Single Band Measurements: A Feasibility Study Using ASTER Observations

Clear-sky contamination is a challenging and long-lasting problem for cloud optical thickness (τ) and effective droplet radius (r eff ) retrievals using passive satellite sensors. This study explores the feasibility of improving both τ and r eff retrievals for partly cloudy (PCL) pixels by using available subpixel samples in a visible to near-infrared band, which many satellite sensors offer. Data are provided by high-resolution reflectance (R ) observations and cloud property retrievals by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) at horizontal resolutions between 30-960m. For partly cloudy 960-m observations, the clear-sky component of the pixels induces significant underestimations of up to 58% for τ, while overestimations in r eff can exceed 41%. This yields underestimations in the derived liquid water path and cloud droplet number concentration of up to 68% and 72%, respectively. By means of three different assumptions it is shown that subpixel R observations in the visible to near-infrared band can be used to estimate higher-resolution R for the second band in the retrieval scheme, as well as the subpixel cloud cover. Here, the estimated values compare well to actually observed ASTER results and are used to retrieve cloud properties, which are unbiased by the clear-sky component of PCL pixels. While the presented retrieval approach is only evaluated for marine boundary layer clouds, it is computationally efficient and can be easily applied to observations from different imagers. As an example, the PCL retrieval scheme is applied to data by the Moderate Resolution Imaging Spectroradiometer, where similar biases for PCL pixels are observed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Propagating information content: an example with advection

The mathematical algorithm to derive geophysical information from remote sensing observations is called a retrieval. The mathematics of many retrieval problems are ill-posed, and thus a priori information is used to help constrain the derived geophysical variable to realistic values. One quantity of interest, therefore, is the information content of the observation. Perfect information content in the observation would be achieved if the retrieval were able to capture any perturbation in the desired geophysical variable with the proper magnitude. Many new data products can be derived by combining geophysical variables retrieved from multiple different remote sensors. This paper explores, for the first time, how to derive the information content of these derived products. The approach uses traditional error propagation techniques to derive the uncertainty of the derived field twice, both when the observations are used in the retrieval and also when only the a priori information from each remote sensor is propagated. These two uncertainties are then used to provide an estimate of the information content of the derived geophysical variable. This study demonstrates how to propagate the uncertainties from six different instruments to provide the information content for water vapor and temperature advection. A multi-month analysis demonstrates that, in a mean sense, the information content for temperature advection is nearly unity for all heights below 700 m while, the information content for water vapor advection is somewhat more variable but still larger than 0.6 in the convective boundary layer.

Turner, David D. [National Oceanic and Atmospheric↗
DOE OSTI2021

Calibration of the Diffusivity Predictions of Centipede Using Approximate Bayesian Computation and Applications in Nyx (Engineering Scale) and Xolotl-MARMOT (Meso-Scale) Simulations

Fission gas evolution and release in UO 2 nuclear fuel are important fuel performance metrics and occur in several distinct stages: 1) nucleation, growth and resolution of intra-granular bubbles, 2) diffusion to grain boundaries and 3) nucleation and growth of bubbles at grain boundaries, which eventually form a connected network (percolation) enabling release of gas from grain boundaries through connections to triple junctions, grain edges or free surfaces. The NE-SciDAC project is developing several computational tools to model this problem, which are connected in a hierarchical multi-scale framework. The information transfer in the multi-scale framework is a critical step that, in addition to best-estimates, should include uncertainty quantification. Despite taking a first-principles multi-scale approach, there is a need to perform parameter calibration to ensure consistency with available experimental data. In the present study, uncertainty quantification (UQ) and parameter calibration is demonstrated for one of the lower length scale codes in the multi-scale framework (Centipede) and then the results, including instances of the propagated uncertainties, are used in other codes within the framework, specifically Nyx and Xolotl-MARMOT. We calibrated the model parameters in Centipede, a computer code used to predict diffusivities of uranium (U) and xenon (Xe) in the context of the simulation of fission gas in uranium oxide (UO 2 ) nuclear fuel. The Centipede code depends on 183 parameters, all of which are subject to uncertainty. The three data sets used in our calibration effort are taken from the literature. This data is available as a set of measurements, including measurement errors. Our goal is to calibrate a statistical model that predicts both the value of the measurement and the uncertainty associated with the measurement. We perform a Bayesian calibration of the model parameters using a dedicated approximate Bayesian computation (ABC) likelihood function. To avoid excessive computational costs, we replace the expensive Centipede simulation code by a higher-order surrogate model, constructed using only the 9 most important parameters. These important parameters are identified by a preliminary global sensitivity analysis (GSA) study. Among the important parameters are T0 (the temperature at which UO 2 is perfectly stoichiometric) and Hf_pO2 (the temperature dependence of the oxygen (O) partial pressure) that should be considered as operating conditions to be estimated along with the other parameters. We consider two different cases: one where we define one set of these operating conditions for all data sets, and one where we define distinct operating condition parameters for each data set. The Xe diffusivities predicted by the latter case show distinct features that could not be observed in the former. Next, we use the diffusivity predictions by Centipede as input to Nyx, a reduced order fuel performance code focused on gas behavior alone, in order to estimate quantities associated with inter-granular bubble formation at conditions specified by the experiments. Finally, the diffusivities obtained from the calibrated Centipede runs were used in coupled Xolotl-MARMOT simulations of intra- and inter-granular gas evolution. The results are compared to simulations using the baseline diffusivities from Turnbull et al.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Parameter estimation with maximal updated densities

A recently developed measure-theoretic framework solves a stochastic inverse problem (SIP) for models where uncertainties in model output data are predominantly due to aleatoric (i.e., irreducible) uncertainties in model inputs (i.e., parameters). The subsequent inferential target is a distribution on parameters. Another type of inverse problem is to quantify uncertainties in estimates of “true” parameter values under the assumption that such uncertainties should be reduced as more data are incorporated into the problem, i.e., the uncertainty is considered epistemic. A major contribution of this work is the formulation and solution of such a parameter identification problem (PIP) within the measure-theoretic framework developed for the SIP. The approach is novel in that it utilizes a solution to a stochastic forward problem (SFP) to update an initial density only in the parameter directions informed by the model output data. In other words, this method performs “selective regularization” only in the parameter directions not informed by data. Further, the solution is defined by a maximal updated density (MUD) point where the updated density defines the measure-theoretic solution to the PIP. Another significant contribution of this work is the full theory of existence and uniqueness of MUD points for linear maps with Gaussian distributions. Data-constructed Quantity of Interest (QoI) maps are also presented and analyzed for solving the PIP within this measure-theoretic framework as a means of reducing uncertainties in the MUD estimate. We conclude with a demonstration of the general applicability of the method on two problems involving either spatial or temporal data for estimating uncertain model parameters. The first problem utilizes spatial data from a stationary partial differential equation to produce a MUD estimate of an uncertain boundary condition. The second problem utilizes temporal data obtained from the state-of-the-art ADvanced CIRCulation (ADCIRC) model to obtain a MUD estimate of uncertain wind drag coefficients for a simulated extreme weather event near the Shinnecock Inlet located in the Outer Barrier of Long Island, NY, USA.

42 ENGINEERING↗
DOE OSTI2018

Mathematical Analysis of the Solidification Behavior of Plain Steel Based on Solute- and Heat-Transfer Equations in the Liquid–Solid Zone

An analytical approximate solution to non-linear solute- and heat-transfer equations in the unsteady-state mushy zone of Fe-C plain steel has been obtained, assuming a linear relationship between the solid fraction and the temperature of the mushy zone. The heat transfer equations for both the solid and liquid zone along with the boundary conditions have been linked with the equations to solve the whole equations. The model predictions (e.g., the solidification constants and the effective partition ratio) agree with the generally accepted values and with a separately performed numerical analysis. The solidus temperature predicted by the model is in the intermediate range of the reported formulas. The model and Neuman’s solution are consistent in the low carbon range. A conventional numerical heat analysis (i.e., an equivalent specific heat method using the solidus temperature predicted by the model) is consistent with the model predictions for Fe-C plain steels. The model presented herein simplifies the computations to solve the solute- and heat-transfer simultaneous equations while searching for a solidus temperature as a part of the solution. Thus, this model can reduce the complexity of analyses considering the heat- and solute-transfer phenomena in the mushy zone.

36 MATERIALS SCIENCE↗
DOE OSTI2014

A nodal domain theorem for integrable billiards in two dimensions

Eigenfunctions of integrable planar billiards are studied — in particular, the number of nodal domains, ν of the eigenfunctions with Dirichlet boundary conditions are considered. The billiards for which the time-independent Schrödinger equation (Helmholtz equation) is separable admit trivial expressions for the number of domains. Here, we discover that for all separable and non-separable integrable billiards, ν satisfies certain difference equations. This has been possible because the eigenfunctions can be classified in families labelled by the same value of mmodkn, given a particular k, for a set of quantum numbers, m,n. Further, we observe that the patterns in a family are similar and the algebraic representation of the geometrical nodal patterns is found. Instances of this representation are explained in detail to understand the beauty of the patterns. This paper therefore presents a mathematical connection between integrable systems and difference equations. - Highlights: • We find that the number of nodal domains of eigenfunctions of integrable, planar billiards satisfy a class of difference equations. • The eigenfunctions labelled by quantum numbers (m,n) can be classified in terms of mmodkn. • A theorem is presented, realising algebraic representations of geometrical patterns exhibited by the domains. • This work presents a connection between integrable systems and difference equations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Tropical and subtropical cloud transitions in weather and climate prediction models: the GCSS/WGNE Pacific Cross-Section Intercomparison (GPCI)

A model evaluation approach is proposed where weather and climate prediction models are analyzed along a Pacific Ocean cross-section, from the stratocumulus regions off the coast of California, across the shallow convection dominated trade-winds, to the deep convection regions of the ITCZ: the GCSS/WGNE Pacific Cross-section Intercomparison (GPCI). The main goal of GPCI is to evaluate, and help understand and improve the representation of tropical and sub-tropical cloud processes in weather and climate prediction models. In this paper, a detailed analysis of cloud regime transitions along the cross-section from the sub-tropics to the tropics for the season JJA of 1998 is presented. This GPCI study confirms many of the typical weather and climate prediction model problems in the representation of clouds: underestimation of clouds in the stratocumulus regime by most models with the corresponding consequences in terms of shortwave radiation biases; overestimation of clouds by the ECMWF Re-Analysis (ERA40) in the deep tropics (in particular) with the corresponding impact in the outgoing longwave radiation; large spread between the different models in terms of cloud cover, liquid water path and shortwave radiation; significant differences between the models in terms of vertical crosssections of cloud properties (in particular), vertical velocity and relative humidity. An alternative analysis of cloud cover mean statistics is proposed where sharp gradients in cloud cover along the GPCI transect are taken into account. This analysis shows that the negative cloud bias of some models and ERA40 in the stratocumulus regions (as compared to ISCCP) is associated not only with lower values of cloud cover in these regimes, but also with a stratocumulus-to-cumulus transition that occurs too early along the trade-wind Lagrangian trajectory. Histograms of cloud cover along the cross-section differ significantly between models. Some models exhibit a quasi-bimodal structure with cloud cover being either very large (close to 100%) or very small, while other models show a more continuous transition. The ISCCP observations suggest that reality is in-between these two extreme examples. These different patterns reflect the diverse nature of the cloud, boundary layer, and convection parameterizations in the participating weather and climate prediction models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Compressional boundaries in the Earth's foreshock

The terrestrial foreshock is a highly dynamic region populated by particles, waves and non-linear structures such as shocklets, SLAMS, hot flow anomalies, cavities and cavitons. Recently a new structure named foreshock compressional boundary (FCB) was reported in global hybrid simulations by Omidi et al. (2009). This structure represents a transition region that separates the highly disturbed foreshock plasma from pristine solar wind or from the region of field-aligned ion beams. The FCB is associated with a strong compression of magnetic field and density. Besides the enhancements in the field and density, the FCB also shows a region where these two quantities decrease below the ambient solar wind (SW) values. Here, we study a FCB observed by Cluster-1. This FCB shows that although sometimes FCBs are transition regions between the pristine solar wind plasma and the foreshock plasma, in this case the FCB separates a region with large amplitude waves from regions with high frequency (f{approx}1.7 Hz) small amplitude waves. We analyze the FCB properties, ion distributions inside them, and the waves near the structure.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Nonlinear instability in simulations of Large Plasma Device turbulence

Several simulations of turbulence in the Large Plasma Device (LAPD) [Gekelman et al., Rev. Sci. Instrum. 62, 2875 (1991)] are energetically analyzed and compared with each other and with the experiment. The simulations use the same model, but different axial boundary conditions. They employ either periodic, zero-value, zero-derivative, or sheath axial boundaries. The linear stability physics is different between the scenarios because the various boundary conditions allow the drift wave instability to access different axial structures, and the sheath boundary simulation contains a conducting wall mode instability which is just as unstable as the drift waves. Nevertheless, the turbulence in all the simulations is relatively similar because it is primarily driven by a robust nonlinear instability that is the same for all cases. The nonlinear instability preferentially drives k{sub ∥}=0 potential energy fluctuations, which then three-wave couple to k{sub ∥}≠0 potential energy fluctuations in order to access the adiabatic response to transfer their energy to kinetic energy fluctuations. The turbulence self-organizes to drive this nonlinear instability, which destroys the linear eigenmode structures, making the linear instabilities ineffective.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

A stochastic perturbation method to generate inflow turbulence in large-eddy simulation models: Application to neutrally stratified atmospheric boundary layers

Despite the variety of existing methods, efficient generation of turbulent inflow conditions for large-eddy simulation (LES) models remains a challenging and active research area. Herein, we extend our previous research on the cell perturbation method, which uses a novel stochastic approach based upon finite amplitude perturbations of the potential temperature field applied within a region near the inflow boundaries of the LES domain [Muñoz-Esparza et al., “Bridging the transition from mesoscale to microscale turbulence in numerical weather prediction models,” Boundary-Layer Meteorol., 153, 409–440 (2014)]. The objective was twofold: (i) to identify the governing parameters of the method and their optimum values and (ii) to generalize the results over a broad range of atmospheric large-scale forcing conditions, U{sub g} = 5 − 25 m s{sup −1}, where U{sub g} is the geostrophic wind. We identified the perturbation Eckert number, Ec=U{sub g}{sup 2}/ρc{sub p}θ{sup ~}{sub pm}, to be the parameter governing the flow transition to turbulence in neutrally stratified boundary layers. Here, θ{sup ~}{sub pm} is the maximum perturbation amplitude applied, c{sub p} is the specific heat capacity at constant pressure, and ρ is the density. The optimal Eckert number was found for nonlinear perturbations allowed by Ec ≈ 0.16, which instigate formation of hairpin-like vortices that most rapidly transition to a developed turbulent state. Larger Ec numbers (linear small-amplitude perturbations) result in streaky structures requiring larger fetches to reach the quasi-equilibrium solution, while smaller Ec numbers lead to buoyancy dominated perturbations exhibiting difficulties for hairpin-like vortices to emerge. Cell perturbations with wavelengths within the inertial range of three-dimensional turbulence achieved identical quasi-equilibrium values of resolved turbulent kinetic energy, q, and Reynolds-shear stress, . In contrast, large-scale perturbations acting at the production range exhibited reduced levels of , due to the formation of coherent streamwise structures, while q was maintained, requiring larger fetches for the turbulent solution to stabilize. Additionally, the cell perturbation method was compared to a synthetic turbulence generator. The proposed stochastic approach provided at least the same efficiency in developing realistic turbulence, while accelerating the formation of large-scales associated with production of turbulent kinetic energy. Also, it is computationally inexpensive and does not require any turbulent information.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Adaptive Sparse-Grid Stochastic Collocation Uncertainty Quantification Convergence for Multigroup Diffusion

Advanced methods in uncertainty quantification for numerical models in computational physics continue to gain acceptance in nuclear modeling. Previously, the efficiency of sparse-grid stochastic collocation in comparison with Monte Carlo for uncertainty quantification through convergence studies was demonstrated. An adaptive method for anisotropic sparse grid collocation and its convergence compared to previous efforts is considered. The physical system in consideration is a two-dimensional quarter-core reactor, consisting of 5 materials distributed in 121 regions. The two-group neutron diffusion criticality approximation is solved. Vacuum boundaries are applied on the top and right, and reflecting boundaries on the bottom and left. The material cross sections, neutron multiplication factors, and diffusion coefficients are potential sources of uncertainty. Uniformly-distributed uncertainty within 5% of the reference values is introduced for material properties. The distribution of the uncertain parameters make up the uncertainty space Γ included in R{sup N}, where N is the number of uncertain parameters. The input parameter uncertainties are independently distributed. As expected, the convergence of Monte Carlo on the benchmark as a function of computational solves is nearly linear and lethargic compared to the other methods. The static isotropic index set, in which each input dimension is treated with equal importance, converges much more efficiently than Monte Carlo, but lacks the benefit of emphasizing some dimensions over others. The anisotropic case is most efficient, where first-order sensitivity information was used to determine anisotropic weights for polynomials to use in the polynomial chaos expansion. Interestingly, the adaptive algorithm converges slightly less efficiently than the anisotropic case, while still performing better than the isotropic case. Because the adaptive case has to determine the importance of each input dimension, it occasionally predicts inaccurately and wastes computation solves compared to the more ideal anisotropic case. However, in circumstances when an ideal anisotropy is not understood a priori, the adaptive algorithm may be optimally efficient in representing the original model. Given the potential loss of efficiency when using a poorly-chosen anisotropic weighting, the adaptive algorithm may be an effective choice for initial uncertainty quantification in problems with a low-dimensionality input space. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2012

Ion-acoustic cnoidal wave and associated non-linear ion flux in dusty plasma

Using reductive perturbation method with appropriate boundary conditions, coupled evolution equations for first and second order potentials are derived for ion-acoustic waves in a collisionless, un-magnetized plasma consisting of hot isothermal electrons, cold ions, and massive mobile charged dust grains. The boundary conditions give rise to renormalization term, which enable us to eliminate secular contribution in higher order terms. Determining the non secular solution of these coupled equations, expressions for wave phase velocity and averaged non-linear ion flux associated with ion-acoustic cnoidal wave are obtained. Variation of the wave phase velocity and averaged non-linear ion flux as a function of modulus (k{sup 2}) dependent wave amplitude are numerically examined for different values of dust concentration, charge on dust grains, and mass ratio of dust grains with plasma ions. It is found that for a given amplitude, the presence of positively (negatively) charged dust grains in plasma decreases (increases) the wave phase velocity. This behavior is more pronounced with increase in dust concentrations or increase in charge on dust grains or decrease in mass ratio of dust grains. The averaged non-linear ion flux associated with wave is positive (negative) for negatively (positively) charged dust grains in the plasma and increases (decreases) with modulus (k{sup 2}) dependent wave amplitude. For given amplitude, it increases (decreases) as dust concentration or charge of negatively (positively) charged dust grains increases in the plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2012

Steady state RANS simulations of temperature fluctuations in single phase turbulent mixing

Single phase turbulent mixing in nuclear power plant circuits where a strong temperature gradient is present is known to precipitate pipe failure due to thermal fatigue. Experiments in a square mixing channel offer the opportunity to study the phenomenon under simple and easily reproducible boundary conditions. Measurements of this kind have been performed extensively at the Paul Scherrer Inst. in Switzerland with a high density of instrumentation in the Generic Mixing Experiment (GEMIX). As a fundamental mixing phenomena study closely related to the thermal fatigue problem, the experimental results from GEMIX are valuable for the validation of CFD codes striving to accurately simulate both the temperature and velocity fields in single phase turbulent mixing. In the experiments two iso-kinetic streams meet at a shallow angle of 3 degrees and mix in a straight channel of square cross-section under various degrees of density, temperature, and viscosity stratification over a range of Reynolds numbers ranging from 5*10{sup 3} to 1*10{sup 5}. Conductivity measurements, using wire-mesh and wall sensors, as well as optical measurements, using particle image velocimetry, were conducted with high temporal and spatial resolutions (up to 2.5 kHz and 1 mm in the case of the wire mesh sensor) in the mixing zone, downstream of a splitter plate. The present paper communicates the results of RANS modeling of selected GEMIX tests. Steady-state CFD calculations using a RANS turbulence model represent an inexpensive method for analyzing large and complex components in commercial nuclear reactors, such as the downcomer and reactor pressure vessel heads. Crucial to real world applicability, however, is the ability to model turbulent heat fluctuations in the flow; the Turbulent Heat Flux Transport model developed by ANSYS CFX is capable, by implementation of a transport equation for turbulent heat fluxes, of readily modeling these values. Furthermore, the closure of the turbulent heat flux transport equation evokes a transport equation for the variance of the enthalpy. It is therefore possible to compare the modeled fluctuations of the liquid temperature directly with the scalar fluctuations recorded experimentally with the wire-mesh. Combined with a working Turbulent Heat Flux Transport model, complex mixing problems in large geometries could be better understood. We aim for the validation of Reynolds Stress based RANS simulations extended by the Turbulent Heat Flux Transport model by modeling the GEMIX experiments in detail. Numerical modeling has been performed using both BSL and SSG Reynolds Stress Models in a test matrix comprising experimental trials at the GEMIX facility. We expand on the turbulent mixing RANS CFD results of (Manera 2009) in a few ways. In the GEMIX facility we introduce density stratification in the flow while removing the characteristic large scale vorticity encountered in T-junctions and therefore find better conditions to check the diffusive conditions in the model. Furthermore, we study the performance of the model in a very different, simpler scalar fluctuation spectrum. The paper discusses the performance of the model regarding the dissipation of the turbulent kinetic energy and dissipation of the enthalpy variance. A novel element is the analyses of cases with density stratification. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2012

CIRCUMBINARY CHAOS: USING PLUTO'S NEWEST MOON TO CONSTRAIN THE MASSES OF NIX AND HYDRA

The Pluto system provides a unique local laboratory for the study of binaries with multiple low-mass companions. In this paper, we study the orbital stability of P4, the most recently discovered moon in the Pluto system. This newfound companion orbits near the plane of the Pluto-Charon (PC) binary, roughly halfway between the two minor moons Nix and Hydra. We use a suite of few body integrations to constrain the masses of Nix and Hydra, and the orbital parameters of P4. For the system to remain stable over the age of the solar system, the masses of Nix and Hydra likely do not exceed 5 Multiplication-Sign 10{sup 16} kg and 9 Multiplication-Sign 10{sup 16} kg, respectively. These upper limits assume a fixed mass ratio between Nix and Hydra at the value implied by their median optical brightness. Our study finds that stability is more sensitive to their total mass and that a downward revision of Charon's eccentricity (from our adopted value of 0.0035) is unlikely to significantly affect our conclusions. Our upper limits are an order of magnitude below existing astrometric limits on the masses of Nix and Hydra. For a density at least that of ice, the albedos of Nix and Hydra would exceed 0.3. This constraint implies they are icy, as predicted by giant impact models. Even with these low masses, P4 only remains stable if its eccentricity e {approx}< 0.02. The 5:1 commensurability with Charon is particularly unstable, combining stability constraints with the observed mean motion places the preferred orbit for P4 just exterior to the 5:1 resonance. These predictions will be tested when the New Horizons satellite visits Pluto. Based on the results for the PC system, we expect that circumbinary, multi-planet systems will be more widely spaced than their singleton counterparts. Further, circumbinary exoplanets close to the three-body stability boundary, such as those found by Kepler, are less likely to have other companions nearby.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

DOUBLE POWER-LAW DISTRIBUTION OF MAGNETIC ENERGY IN THE SOLAR CORONA OVER AN ACTIVE REGION

In this paper, we study the magnetic energy (ME) structure contained in the solar corona over the active region NOAA 11158. The time period is chosen as from 0:00 to 06:00 UT on 2011 February 15, during which an X-class flare occurred. The nonlinear force-free field (NLFFF) and the potential field extrapolation are carried out to model the coronal magnetic field over this active region, using high-quality photospheric vector magnetograms observed by the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory as boundary conditions. We find that the volume distribution for the density of the ME (B {sup 2}/8{pi}) and the ohmic dissipation power (ODP, j {sup 2}/{sigma}), in which j is the electric current density (c/4{pi}{nabla} Multiplication-Sign B) and {sigma} is the conductivity in the corona, can be readily fitted by a broken-down double-power law. The turn-over density for the spectrum of the ME and ODP is found to be fixed at {approx}1.0 Multiplication-Sign 10{sup 4} erg cm{sup -3} and {approx}2.0 Multiplication-Sign 10{sup -15} W cm{sup -3} (assuming {sigma} = 10{sup 5} {Omega}{sup -1} m{sup -1}), respectively. Compared with their first power-law spectra (fitted below the corresponding turn-over value) which remain unchanged, the second power-law spectra (fitted above the corresponding turn-over value) for the NLFFF's ME and ODP show flare-associated changes. The potential field remains steady. These results indicate that a magnetic field with energy density larger than the turn-over energy density plays a dominant role in powering the flare.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Evaporative thermal resistance and its influence on microlayer evaporation

The ability to predict various aspects of boiling is important for both safety and design of water-cooled reactors. Component-scale modelling is necessarily done by semi-mechanistic, semi-empirical approaches, generally based on heat flux partitioning. This needs to be informed by multiple detailed experimental observations of boiling behavior. Such measurements are difficult to make, and much effort is being applied to microscopic computational modelling of the detailed boiling process. Aims of such activities include the mechanistic prediction of growth and detachment of one bubble during nucleate boiling, and the quantification of the associated heat transfer partitioning (evaporation, micro-convection, quenching). We here study a subset of the full problem, and focus on the thermal response of the boiling substrate to the early growth of a single vapour bubble during pool boiling of water at atmospheric pressure. In such conditions, a thin liquid film ('microlayer') is left behind beneath the bubble as this expands. The microlayer evaporates due to the temperature difference between the solid-liquid and vapour-liquid interface. Its thickness being small, of order of microns, the local evaporation rate per unit area of bubble base can be high, up to one kilogram per second. Microlayer evaporation can therefore be important in early stages of bubble growth. In this contribution, thermal response of the boiling substrate to microlayer evaporation is studied with a two-dimensional, axisymmetric transient conduction model, coupled with an algebraic sub-model of the liquid film. The flow of heat through the microlayer is modelled as conduction in the liquid and with a pseudo-convective 'evaporative' heat transfer coefficient at the liquid-vapor interface, accounting for the interface superheat driving the evaporation process. Thermal coupling (conjugate heat transfer) between microlayer and solid substrate is obtained with a time dependent non-homogeneous Neumann boundary condition, derived from the algebraic microlayer sub-model and applied at the top surface of the solid computational domain. The thermal resistance associated to the evaporative heat transfer mechanism is shown to depend on a highly uncertain parameter, termed an 'evaporation coefficient'. After some exploratory calculations of the likely importance of the evaporative resistance in the present context, the model is employed to interpret some recent microlayer measurements. Satisfactory agreement between computed and measured evolution of the microlayer profile is obtained if small values (between 0.01 and 0.10) of the evaporation coefficient are used. The order of magnitude of the predicted evaporation rate from the microlayer is consistent with experimental observations. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Low-energy probes of no-scale SU(5) super-GUTs

We explore the possible values of the μ → eγ branching ratio, BR(μ → eγ), and the electron dipole moment (eEDM), d e , in no-scale SU(5) super-GUT models with the boundary conditions that soft supersymmetry-breaking matter scalar masses vanish at some high input scale, M in , above the GUT scale, M GUT . We take into account the constraints from the cosmological cold dark matter density, Ω CDM h 2 , the Higgs mass, M h , and the experimental lower limit on the lifetime for p → K + ν¯, the dominant proton decay mode in these super-GUT models. Reconciling this limit with Ω CDM h 2 and M h requires the Higgs field responsible for the charge-2/3 quark masses to be twisted, and possibly also that responsible for the charge-1/3 and charged-lepton masses, with model-dependent soft supersymmetry-breaking masses. We consider six possible models for the super-GUT initial conditions, and two possible choices for quark flavor mixing, contrasting their predictions for proton decay with versions of the models in which mixing effects are neglected. We find that τ(p → K + ν¯) may be accessible to the upcoming Hyper-Kamiokande experiment, whereas all the models predict BR(μ → eγ) and d e below the current and prospective future experimental sensitivities or both flavor choices, when the dark matter density, Higgs mass and current proton decay constraints are taken into account. However, there are limited regions with one of the flavor choices in two of the models where μ → e conversion on a heavy nucleus may be observable in the future. Our results indicate that there is no supersymmetric flavor problem in the class of no-scale models we consider.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Liquid-gas phase transitions and C K symmetry in quantum field theories

A general field-theoretic framework for the treatment of liquid-gas phase transitions is developed. Starting from a fundamental four-dimensional field theory at nonzero temperature and density, an effective three-dimensional field theory is derived. The effective field theory has a sign problem at finite density. Although finite density explicitly breaks charge conjugation C , there remains a symmetry under C K , where K is complex conjugation. Here, we consider four models: relativistic fermions, nonrelativistic fermions, static fermions and classical particles. The interactions are via an attractive potential due to scalar field exchange and a repulsive potential due to massive vector exchange. The field-theoretic representation of the partition function is closely related to the equivalence of the sine-Gordon field theory with a classical gas. The thermodynamic behavior is extracted from C K -symmetric complex saddle points of the effective field theory at tree level. In the cases of nonrelativistic fermions and classical particles, we find complex saddle point solutions but no first-order transitions, and neither model has a ground state at tree level. The relativistic and static fermions show a liquid-gas transition at tree level in the effective field theory. The liquid-gas transition, when it occurs, manifests as a first-order line at low temperature and high density, terminated by a critical end point. The mass matrix controlling the behavior of correlation functions is obtained from fluctuations around the saddle points. Due to the C K symmetry of the models, the eigenvalues of the mass matrix are not always real but can be complex. This then leads to the existence of disorder lines, which mark the boundaries where the eigenvalues go from purely real to complex. The regions where the mass matrix eigenvalues are complex are associated with the critical line. In the case of static fermions, a powerful duality between particles and holes allows for the analytic determination of both the critical line and the disorder lines. Depending on the values of the parameters, either zero, one, or two disorder lines are found. Our numerical results for relativistic fermions give a very similar picture.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗