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At least 991 records · Page 55

An MPMD approach coupling electromagnetic continuum mechanics approximations in ALEGRA

In this work, two complementary approximations for describing aspects of continuum electromagnetics in moving media are discussed: electroquasistatic and magnetoquasistatic. Each has been implemented in the finite element shock code ALEGRA for modeling dynamic electromechanical phenomena on typical engineering time scales, with fully integrated circuit coupling. The approximations can be obtained by consistent asymptotic balancing of Maxwell’s equations relative to timescales associated with magnetic diffusion, charge relaxation, and electromagnetic wave propagation. In ALEGRA, the electroquasistatic approximation is used for ferroelectric (FE) modeling, while the magnetoquasistatic approximation is used for magnetohydrodynamic (MHD) modeling. In this paper we introduce for the first time a detailed derivation of a useful quasi-steady “low-R m ” variant of the MHD approximation applicable for cases, such as with detonators, where the thermodynamic pressure arising from Joule heating dominates over magnetic forces. An additional purpose of this paper is to present a coupling mode using Multiple Program-Multiple Data (MPMD) message passing communication that allows the user to run 3D FE problems together with 2D and/or 3D MHD problems with the respective simulation domains coupled through a common circuit equation. The MPMD coupling capability is used here to model the dynamic coupling of a notional ferroelectric generator with an RP-87 exploding bridgewire detonator. The simulated bridgewire heats up and bursts under current generated by simulated depoling of the ferroelectric generator, as a demonstration of the MPMD capability.

42 ENGINEERING↗

High-speed 3D shape measurement using the optimized composite fringe patterns and stereo-assisted structured light system

In this study, we propose a high-speed 3D shape measurement technique based on the optimized composite fringe patterns and stereo-assisted structured light system. Stereo phase unwrapping, as a new-fashioned method for absolute phase retrieval based on the multi-view geometric constraints, can eliminate the phase ambiguities and obtain a continuous phase map without projecting any additional patterns. However, in order to ensure the stability of phase unwrapping, the period of fringe is generally around 20, which limits the accuracy of 3D measurement. To solve this problem, we develop an optimized method for designing the composite pattern, in which the speckle pattern is embedded into the conventional 4-step phase-shifting fringe patterns without compromising the fringe modulation, and thus the phase measurement accuracy. We also present a simple and effective evaluation criterion for the correlation quality of the designed speckle pattern in order to improve the matching accuracy significantly. When the embedded speckle pattern is demodulated, the periodic ambiguities in the wrapped phase can be eliminated by combining the adaptive window image correlation with geometry constraint. Finally, some mismatched regions are further corrected based on the proposed regional diffusion compensation technique (RDC). These proposed techniques constitute a complete computational framework that allows to effectively recover an accurate, unambiguous, and distortion-free 3D point cloud with only 4 projected patterns. Experimental results verify that our method can achieve high-speed, high-accuracy, robust 3D shape measurement with dense (64-period) fringe patterns at 5000 frames per second.

42 ENGINEERING↗

Implementation and verification of a user-defined element (UEL) for coupled thermal-hydraulic-mechanical-chemical (THMC) processes in saturated geological media

Efficient and accurate modeling of the coupled thermal-hydraulic-mechanical-chemical (THMC) processes in various rock formations is indispensable for designing energy geo-structures such as underground repositories for high-level nuclear wastes. Here, this work focuses on developing and verifying an implicit finite element solver for generic coupled THMC problems in geological settings. Starting from the mass, momentum, and energy balance laws, a specialized set of governing equations and a thermoporoelastic constitutive model is derived. This system is then solved by an implicit finite element (FE) scheme. Specifically, the residuals and the Jacobians are scripted in a user-defined element (UEL) subroutine which is then combined with the general-purpose FE software Abaqus Standard to solve initial-boundary value problems. Considering the complexity of the system, the UEL development follows a stepwise manner by first solving the coupled hydraulic-mechanical (HM) and thermal-hydraulic-mechanical (THM) equations before moving on to the full THMC problem. Each implementation step consists of at least one verification test by comparing computed results with closed-form analytical solutions to ensure that the various coupling effects are correctly realized. To demonstrate the robustness of the algorithm and to validate the UEL, a three-dimensional case study is performed with reference to the in-situ heating test of ATLAS at Belgium in 1980s. A hypothetical radionuclide leakage event is then simulated by activating the chemical-concentration degree of freedom and prescribing a constant high concentration at the heater's surface. The model predicts a limited contaminated regime after six years considering both diffusion and advection effects on species transport.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A study of deformation and strain induced in bulk by the oxide layers formation on a Fe-Cr-Al alloy in high-temperature liquid Pb-Bi eutectic

At elevated temperatures, heavy liquid metals and their alloys are known to create a highly corrosive environment that causes irreversible degradation of most iron-based materials. In this paper, it has been found that an appropriate concentration of oxygen in the liquid alloy can significantly reduce this issue by creating a passivating oxide scale that controls diffusion, especially if Al is present in Fe-based materials (by Al-oxide formation). However, the increase of the temperature and of oxygen content in liquid phase leads to the increase of oxygen diffusion into bulk, and to promotion of the internal Al oxidation. This can cause a strain in bulk near the oxide layer, due either to mismatch between the thermal expansion coefficients of the oxides and bulk material, or to misfit of the crystal lattices (bulk vs. oxides). This work investigates the strain induced into proximal bulk of a Fe-Cr-Al alloy by oxide layers formation in liquid lead-bismuth eutectic utilizing synchrotron X-ray Laue microdiffraction. Finally, it is found that internal oxidation is the most likely cause for the strain in the metal rather than thermal expansion mismatch as a two-layer problem.

36 MATERIALS SCIENCE↗

Entropy–viscosity method for the single material Euler equations in Lagrangian frame

In this work, a new finite element method for solving the Euler equations in Lagrangian coordinates is proposed. The method is stabilized by adding artificial diffusion terms compatible with positivity of mass and internal energy, a minimum principle on the specific entropy, and all generalized entropy inequalities. Two options of first-order artificial diffusion are considered. One is in the spirit of the Eulerian based method (Guermond et al., 2011 [23, 22]; Zingan et al., 2013) and the other is similar to existing viscosity stabilizations in Lagrangian frame, e.g., Dobrev et al. (2012). The method is verified to be high-order for smooth solutions even with active viscosity terms. This is achieved by using high-order finite element spaces and an entropy-based viscosity stabilization that degenerates the first-order viscous terms. This stabilization automatically distinguishes smooth and singular regions. The formal accuracy and convergence properties of the proposed methods are tested on a series of benchmark problems. This is the first result extending the entropy–viscosity methodology to the Lagrangian hydrodynamics.

97 MATHEMATICS AND COMPUTING↗

Environmental controls on the light use efficiency of terrestrial gross primary production

Abstract Gross primary production (GPP) by terrestrial ecosystems is a key quantity in the global carbon cycle. The instantaneous controls of leaf‐level photosynthesis are well established, but there is still no consensus on the mechanisms by which canopy‐level GPP depends on spatial and temporal variation in the environment. The standard model of photosynthesis provides a robust mechanistic representation for C 3 species; however, additional assumptions are required to “scale up” from leaf to canopy. As a consequence, competing models make inconsistent predictions about how GPP will respond to continuing environmental change. This problem is addressed here by means of an empirical analysis of the light use efficiency (LUE) of GPP inferred from eddy covariance carbon dioxide flux measurements, in situ measurements of photosynthetically active radiation (PAR), and remotely sensed estimates of the fraction of PAR (fAPAR) absorbed by the vegetation canopy. Focusing on LUE allows potential drivers of GPP to be separated from its overriding dependence on light. GPP data from over 100 sites, collated over 20 years and located in a range of biomes and climate zones, were extracted from the FLUXNET2015 database and combined with remotely sensed fAPAR data to estimate daily LUE. Daytime air temperature, vapor pressure deficit, diffuse fraction of solar radiation, and soil moisture were shown to be salient predictors of LUE in a generalized linear mixed‐effects model. The same model design was fitted to site‐based LUE estimates generated by 16 terrestrial ecosystem models. The published models showed wide variation in the shape, the strength, and even the sign of the environmental effects on modeled LUE. These findings highlight important model deficiencies and suggest a need to progress beyond simple “goodness of fit” comparisons of inferred and predicted carbon fluxes toward an approach focused on the functional responses of the underlying dependencies.

54 ENVIRONMENTAL SCIENCES↗

The High Energy X-ray Probe (HEX-P): supernova remnants, pulsar wind nebulae, and nuclear astrophysics

HEX-P is a probe-class mission concept that will combine high spatial resolution X-ray imaging (< 10" full width at half maximum) and broad spectral coverage (0.2–80 keV) with an effective area far superior to current facilities (including XMM-Newton and NuSTAR) to enable revolutionary new insights into a variety of important astrophysical problems. HEX-P is ideally suited to address important problems in the physics and astrophysics of supernova remnants (SNRs) and pulsar wind nebulae (PWNe). For shell SNRs, HEX-P can greatly improve our understanding via more accurate spectral characterization and localization of non-thermal X-ray emission from both non-thermal-dominated SNRs and those containing both thermal and non-thermal components, and can discover previously unknown non-thermal components in SNRs. Multi-epoch HEX-P observations of several young SNRs (e.g., Cas A and Tycho) are expected to detect year-scale variabilities of X-ray filaments and knots, thus enabling us to determine fundamental parameters related to diffusive shock acceleration, such as local magnetic field strengths and maximum electron energies. For PWNe, HEX-P will provide spatially-resolved, broadband X-ray spectral data separately from their pulsar emission, allowing us to study how particle acceleration, cooling, and propagation operate in different evolution stages of PWNe. HEX-P is also poised to make unique and significant contributions to nuclear astrophysics of Galactic radioactive sources by improving detections of, or limits on, 44Ti in the youngest SNRs and by potentially discovering rare nuclear lines as evidence of double neutron star mergers. Throughout the paper, we present simulations of each class of objects, demonstrating the power of both the imaging and spectral capabilities of HEX-P to advance our knowledge of SNRs, PWNe, and nuclear astrophysics.

79 ASTRONOMY AND ASTROPHYSICS↗

MPAS-Albany Land Ice (MALI): a variable-resolution ice sheet model for Earth system modeling using Voronoi grids

Abstract. We introduce MPAS-Albany Land Ice (MALI) v6.0, a new variable-resolution land ice model that uses unstructured Voronoi grids on a plane or sphere. MALI is built using the Model for Prediction Across Scales (MPAS) framework for developing variable-resolution Earth system model components and the Albany multi-physics code base for the solution of coupled systems of partial differential equations, which itself makes use of Trilinos solver libraries. MALI includes a three-dimensional first-order momentum balance solver (Blatter–Pattyn) by linking to the Albany-LI ice sheet velocity solver and an explicit shallow ice velocity solver. The evolution of ice geometry and tracers is handled through an explicit first-order horizontal advection scheme with vertical remapping. The evolution of ice temperature is treated using operator splitting of vertical diffusion and horizontal advection and can be configured to use either a temperature or enthalpy formulation. MALI includes a mass-conserving subglacial hydrology model that supports distributed and/or channelized drainage and can optionally be coupled to ice dynamics. Options for calving include eigencalving , which assumes that the calving rate is proportional to extensional strain rates. MALI is evaluated against commonly used exact solutions and community benchmark experiments and shows the expected accuracy. Results for the MISMIP3d benchmark experiments with MALI's Blatter–Pattyn solver fall between published results from Stokes and L1L2 models as expected. We use the model to simulate a semi-realistic Antarctic ice sheet problem following the initMIP protocol and using 2 km resolution in marine ice sheet regions. MALI is the glacier component of the Energy Exascale Earth System Model (E3SM) version 1, and we describe current and planned coupling to other E3SM components.

54 ENVIRONMENTAL SCIENCES↗

Developing Soret Transport Coefficients for Lanthanides from Experimental Results

Understanding the nature of lanthanide transport in metallic fuels and its relation to fuel clad chemical interaction (FCCI) has been has been a topic that is long on interest and short on data. Recent experiments have shown a strong temperature-gradient based diffusion (Soret diffusion) and have thus provided vitally important information for modelers. However, details about the actual coefficients and many of the relevant processes that crucially participate in the cerium migration and precipitation process have not yet been disclosed. Using a combination of computing tools (primarily python and BISON) we are exploring methods that may extract useful information from visual data. In this specific example, we are using what is formally called 'blob detection' algorithms to analyzed the precipitate distribution of cerium in a U-Zr metal that has had a fixed temperature gradient enforced upon it for a specified period of time. These algorithms, once properly adapted to the problem at hand, may be useful at extracting information from radial and axial scans of metallic fuels which are much more abundant than direct measurements of lanthanides. We have developed a model that qualitatively works to move mass along a temperature gradient and precipitate heavily in the cold regions. Additionally, we have observed that the solubility of cerium in U-Zr held under this kind of temperature gradient is subject to some amount of U-Zr constituent redistribution. Our results predict movement of the Zr toward the hot end of the rod followed by a U-rich layer with the cooler 3/5 of the rod staying close the the initial U-Zr distribution. A more complete analysis will define groups of correlated parameters that correctly simulate the resulting distribution of precipitates. This restricted parameters space will give smaller bounds to modelers and will expedite the analysis of future works as new and more accurate data are made available. A follow-up experiment that started with 1/10 of the initial concentration of cerium may provide valuable additional information with regard to the effect of the rates of precipitation and dissolution as well as demonstrating the potential rapidity of migration in a lower burnup scenario. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Nanostructured Fe-Cr Alloys for Advanced Nuclear Energy Applications

We have completed research on the grain-size stabilization of model nanostructured Fe14Cr base alloys at high temperatures by the addition of non-equilibrium solutes. Fe14Cr base alloys are representative for nuclear reactor applications. The neutron flux in a nuclear reactor will generate He atoms that coalesce to form He bubbles. These can lead to premature failure of the reactor components, limiting their lifetime and increasing the cost and capacity for power generation. In order to mitigate such failures, Fe14Cr base alloys have been processed to contain very small nano-size oxide particles (less than 10 nm in size) that trap He atoms and reduce bubble formation. Theoretical and experimental results indicate that the grain boundaries can also be very effective traps for He atoms and bubble formation. An optimum grain size will be less than 100 nm, ie., nanocrystalline alloys must be used. Powder metallurgy methods based on high-energy ball milling can produce Fe-Cr base nanocrystalline alloys that are suitable for nuclear energy applications. The problem with nanocrystalline alloys is that excess grain-boundary energy will cause grains to grow at higher temperatures and their propensity for He trapping will be lost. The nano-size oxide particles in current generation nuclear alloys provide some grain size stabilization by reducing grain-boundary mobility (Zener pinning – a kinetic effect). However the current mitigation strategy minimizing bubble formation is based primarily on He trapping by nano-size oxide particles. An alternate approach to nanoscale grain size stabilization has been proposed. This is based on the addition of small amounts of atoms that are large compared to the base alloy. At higher temperatures these will diffuse to the grain boundaries and will produce an equilibrium state for the grain size at higher temperatures (thermodynamic stabilization – an equilibrium effect). This would be preferred compared to a kinetic effect, which is not based on an equilibrium state. The PI and coworkers have developed thermodynamic-based models that can be used to select appropriate solute additions to Fe14Cr base alloys to achieve a contribution to grain-size stabilization and He bubble mitigation by the thermodynamic effect. All such models require approximations and the proposed research was aimed at alloy selection, processing and detailed atomic-level microstructure evaluations to establish the efficacy of the thermodynamic effect. The outcome of this research shows that appropriate alloy additions can produce a contribution from the thermodynamic stabilization effect. Furthermore, due to the oxygen typically present in nominally high purity elemental powders used for powder metallurgy processing, the optimum results obtained appeared as a synergistic combination of nano-size oxide particle pinning kinetic effect and the grain-boundary segregation thermodynamic effect.

36 MATERIALS SCIENCE↗

Controlling the polysulfide diffusion in lithium-sulfur batteries with a polymer membrane with intrinsic nanoporosity

Polysulfide-shuttle has been a critical concern for the advancement of lithium-sulfur (Li-S) batteries. Celgard membranes that are generally used in Li-S batteries exhibit a porous structure with a pore dimension generally on the micrometer scale. During cell operation, soluble lithium polysulfide species can easily migrate from the cathode through the porous separator and react with the lithium-metal anode. Such an unexpected chemical reaction induces a cascade of negative effects on the overall performance of Li-S batteries. Use of ion-selective membranes with reduced pore size provides a promising approach to suppress the migration of polysulfide species. In this study, a membrane based on a polymer with intrinsic nanoporosity (PIN) with a pore size of < 1.0 nm is explored as a separator in Li-S batteries to mitigate the polysulfide-shuttle problem. The PIN membrane exhibits a unique structure with pore dimensions of less than 1.0 nm, which allows the transport of Li-ions, but effectively blocks the migration of dissolved polysulfides. As a result, the cycling performance of Li-S batteries are significantly improved. In addition to demonstrating a PIN-membrane Li-S battery, the structural characteristics of the PIN membrane have been characterized by a series of experimental methodologies and molecular dynamics (MD) simulations.

25 ENERGY STORAGE↗

Development of a tomographic reconstruction method for axisymmetric D α emission profiles in the ITER plasma boundary

A tomographic method for reconstructing the axially symmetric D α emission profile in the ITER scrape-off layer and divertor from D α intensity measurements in the fields of view (FoV) of Vis/IR TV and Divertor Impurity Monitor diagnostics is under development. The method takes into account the strong background signal due to stray light from divertor produced by reflections from the metal wall of the vacuum chamber. The method allows to filter out the reflections in D α signals measured in the main chamber. Here, the accuracy of this method is tested within the framework of a synthetic diagnostic, which uses the Raysect and Cherab numerical codes for ray-tracing simulations. The D α emission profiles, simulated with the SOLPS and OEDGE codes, are used as synthetic experimental data. Uncertainty in light reflection properties of the first wall (FW) is the major factor affecting the accuracy of the D α emission reconstruction. The dependence on the uncertainty in the FW surface roughness and on the ratio of diffusive to specular reflection of the error in recovering useful D α signals (the direct light without reflections) in the FoV of the ITER main chamber H-alpha and Visible Spectroscopy Diagnostic is obtained.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Simulation of the Plasma Afterglow in the Discharge Gap of a Subnanosecond Switch Based on an Open Discharge in Helium

The phenomenon of subnanosecond electrical breakdown in a strong electric field observed in an open discharge in helium at pressures of 6–20 Torr can be used to create ultrafast plasma switches triggering into a conducting state for a time shorter than 1 ns. To evaluate the possible repetition rate of such a subnanosecond switch, it is interesting to study the decay dynamics of the plasma remaining in the discharge gap after ultrafast breakdown. In this paper, a kinetic model based on the particle-in-cell Monte Carlo collision method is used to study the dynamics of the plasma afterglow in the discharge gap of a subnanosecond switch operating with helium at a pressure of 6 Torr. The simulation results show that the radiative, collisional-radiative, and three-body collision recombination mechanisms significantly contribute to the afterglow decay only while the plasma density remains higher than 10{sup 12} cm{sup −3}; the main mechanism of the further plasma decay is diffusion of plasma particles onto the wall. Therefore, the effect of recombination in the plasma bulk is observed only during the first 10–20 μs of the afterglow. Over nearly the same time, plasma electrons become thermalized. The afterglow time can be substantially reduced by applying a positive voltage U{sub c} to the cathode. Since diffusive losses are limited by the ion mobility, the additional ion drift toward the wall significantly accelerates plasma decay. As U{sub c} increases from 0 to +500 V, the characteristic time of plasma decay is reduced from 35 to 10 μs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Conservative tightly-coupled simulations of stochastic multiscale systems

Multiphysics problems often involve components whose macroscopic dynamics is driven by microscopic random fluctuations. The fidelity of simulations of such systems depends on their ability to propagate these random fluctuations throughout a computational domain, including subdomains represented by deterministic solvers. When the constituent processes take place in nonoverlapping subdomains, system behavior can be modeled via a domain-decomposition approach that couples separate components at the interfaces between these subdomains. Its coupling algorithm has to maintain a stable and efficient numerical time integration even at high noise strength. We propose a conservative domain-decomposition algorithm in which tight coupling is achieved by employing either Picard's or Newton's iterative method. Coupled diffusion equations, one of which has a Gaussian white-noise source term, provide a computational testbed for analysis of these two coupling strategies. Fully-converged (“implicit”) coupling with Newton's method typically outperforms its Picard counterpart, especially at high noise levels. This is because the number of Newton iterations scales linearly with the amplitude of the Gaussian noise, while the number of Picard iterations can scale superlinearly. At large time intervals between two subsequent inter-solver communications, the solution error for single-iteration (“explicit”) Picard's coupling can be several orders of magnitude higher than that for implicit coupling. Increasing the explicit coupling's communication frequency reduces this difference, but the resulting increase in computational cost can make it less efficient than implicit coupling at similar levels of solution error, depending on the communication frequency of the latter and the noise strength. This trend carries over into higher dimensions, although at high noise strength explicit coupling may be the only computationally viable option.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Towards fast, accurate predictions of RF simulations via data-driven modeling: Forward and lateral models

Three machine learning techniques (multilayer perceptron, random forest, and Gaussian process) provide fast surrogate models for lower hybrid current drive (LHCD) simulations. A single GENRAY/CQL3D simulation without radial diffusion of fast electrons requires several minutes of wall-clock time to complete, which is acceptable for many purposes, but too slow for integrated modeling and real-time control applications. More accurate simulations with fast electron diffusion are even slower, requiring multiple hours of run time with parallel processing. The machine learning models use a database of 16,000+ GEN-RAY/CQL3D simulations for training, validation, and testing. Latin hypercube sampling methods implemented in πScope ensure that the database covers the range of 9 input parameters (n e0 , T e0 , I p , B t , R 0 , n ∥︀ , Z e f f , V loop , P LHCD ) with sufficient density in all regions of parameter space. The surrogate models reduce the computation time from minutes-hours to ms with high accuracy across the input parameter space. Data-driven surrogate models also allow for solving inverse and “lateral” problems. A surrogate model for the inverse problem maps from a desired current drive or power deposition profile to a set of input parameters that would result in such a profile, while a surrogate model for the lateral problem maps from a measured experimental quantity such as hard x-ray emission to a current drive or power deposition profile. In conclusion, the πScope database creation workflow is flexible and applicable to other RF simulation codes such as TORIC.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Data-driven efficient network and surveillance-based immunization

Given a contact network and coarse-grained diagnostic information such as electronic Healthcare Reimbursement Claims (eHRC) data, can we develop efficient intervention policies from data to control an epidemic? Immunization is an important problem in multiple areas, especially epidemiology and public health. However, most existing studies rely on assuming prior epidemiological models to develop pre-emptive strategies, which may fail to adapt to the change in new epidemiological patterns and the availability of rich data such as eHRC. In practice, disease spread is usually complicated, hence assuming an underlying model may deviate from true spreading patterns, leading to possibly inaccurate interventions. Additionally, the abundance of health care surveillance data (such as eHRC) makes it possible to study data-driven strategies without too many restrictive assumptions. Therefore, such a data-driven intervention approach can help public-health experts take more practical decisions. In this work, we take into account propagation log and contact networks for controlling propagation. Furthermore, different from previous model-based approaches, our solutions are solely data driven in a sense that we develop immunization strategies directly from the network and eHRC without assuming classical epidemiological models. In particular, we formulate the novel and challenging data-driven immunization problem. To solve it, we first propose an efficient sampling approach to align surveillance data with contact networks, then develop an efficient algorithm with the provably approximate guarantee for immunization. Finally, we show the effectiveness and scalability of our methods via extensive experiments on multiple datasets, and conduct case studies on nation-wide real medical surveillance data.

60 APPLIED LIFE SCIENCES↗

Improvements to a class of hybrid methods for radiation transport: Nyström reconstruction and defect correction methods

In this study, two modifications are introduced for improving the accuracy, versatility, and robustness of a class of hybrid methods for radiation transport. In general, such methods are constructed by splitting the radiative flux into collided and uncollided components to which low- and high-resolution angular approximations are applied, respectively. In this work we focus on discrete ordinates discretizations of high and low order. The first modification we introduce changes the way in which the collided component is mapped into the uncollided component at the end of each time step in a simulation. The new mapping is a Nyström-type reconstruction that is applicable to arbitrary discrete ordinates quadratures, is guaranteed to preserve positivity of the solution provided that all ordinate weights are positive, is significantly more accurate than previous methods, and can be readily extended to other discretizations such as moment methods, finite element methods, and diffusion approximations. The second modification leverages integral deferred correction (IDC) to iteratively correct for the splitting error introduced by the inconsistency in angular discretization between the collided and uncollided components, in addition to improving the accuracy of the low-order temporal error that is treated by traditional IDC methods. Numerical tests in one- and two-dimensional geometries are used to demonstrate the increased accuracy and efficiency of the proposed modifications. It is found that the two techniques combined yield methods with solution accuracy and memory requirements comparable to that of monolithic discrete ordinates methods while reducing runtime by as much as a factor of between two and ten, depending on the problem.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Composition and Band Structure of the Native Oxide Nanolayer on the Ion Beam Treated Surface of the GaAs Wafer

Detailed information on GaAs oxide properties is important for solving the problem of passivating and dielectric layers in the GaAs-based electronics. The elemental and chemical compositions of the native oxide layer grown on the atomically clean surface of an n-GaAs (100) wafer etched by Ar{sup +} ions have been studied by synchrotron-based photoelectron spectroscopy. It has been revealed that the oxide layer is essentially enriched in the Ga{sub 2}O{sub 3} phase which is known to be a quite good dielectric as compared to As{sub 2}O{sub 3}. The gallium to arsenic ratio reaches the value as high as [Ga]/[As] = 1.5 in the course of oxidation. The Ga-enrichment occurs supposedly due to diffusion away of As released in preferential oxidation of Ga atoms. A band diagram was constructed for the native oxide nanolayer on the n-GaAs wafer. It has been shown that this natural nanostructure has features of a p–n heterojunction.

36 MATERIALS SCIENCE↗