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NASA NTRS2001

Cloud Structure and Cloud-Radiation Interaction: From Smallest Observable Scales (Less than 10 m) to GCM Grid Scales (More than 100 km)

In this presentation we review the fractal nature of internal cloud structure from cm- to km-scales as captured by in-situ probes during long horizontal penetrations by aircraft. We uncover the non-Poissonian spatial distribution of cloud droplets at submeter scales and confirm scale-invariant behavior for large scales. Based on these structural characteristics, we generate simple fractal cloud models that reproduce statistical scaling properties of real clouds. These stochastic models represent a link between nonlinear science, in general, and cloud-radiation interaction, in particular. Next we run three-dimensional radiative transfer computations on these synthetic fractal clouds and compare the structure of the resulting radiation fields with the known structure of the cloud model and with satellite images of real clouds. The different behaviors observed for small and large-scale variabilities will be discussed in detail. We find that while the large-scale fluctuations of the resulting radiation fields resemble those in the original scale-invariant cloud structure, the radiation at small scales is much smoother than its cloud liquid water counterpart. This violates scale-invariance and produces a scale-break at 0.2-0.5 km that is clearly observed in high-resolution satellite data such as from Landsat. Finally, we show how radiative transfer Green function theory in the photon diffusion limit explains (and predicts) the above phenomena of "radiative smoothing."

Marshak, Alexander↗

DOE OSTI2015

Constant-complexity stochastic simulation algorithm with optimal binning

At the molecular level, biochemical processes are governed by random interactions between reactant molecules, and the dynamics of such systems are inherently stochastic. When the copy numbers of reactants are large, a deterministic description is adequate, but when they are small, such systems are often modeled as continuous-time Markov jump processes that can be described by the chemical master equation. Gillespie’s Stochastic Simulation Algorithm (SSA) generates exact trajectories of these systems, but the amount of computational work required for each step of the original SSA is proportional to the number of reaction channels, leading to computational complexity that scales linearly with the problem size. The original SSA is therefore inefficient for large problems, which has prompted the development of several alternative formulations with improved scaling properties. We describe an exact SSA that uses a table data structure with event time binning to achieve constant computational complexity with respect to the number of reaction channels for weakly coupled reaction networks. We present a novel adaptive binning strategy and discuss optimal algorithm parameters. We compare the computational efficiency of the algorithm to existing methods and demonstrate excellent scaling for large problems. This method is well suited for generating exact trajectories of large weakly coupled models, including those that can be described by the reaction-diffusion master equation that arises from spatially discretized reaction-diffusion processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Bringing discrete-time Langevin splitting methods into agreement with thermodynamics

In light of the recently published complete set of statistically correct Grønbech–Jensen (GJ) methods for discrete-time thermodynamics, we revise a differential operator splitting method for the Langevin equation in order to comply with the basic GJ thermodynamic sampling features, namely, the Boltzmann distribution and Einstein diffusion, in linear systems. This revision, which is based on the introduction of time scaling along with flexibility of a discrete-time velocity attenuation parameter, provides a direct link between the ABO splitting formalism and the GJ methods. This link brings about the conclusion that any GJ method has at least weak second order accuracy in the applied time step. It further helps identify a novel half-step velocity, which simultaneously produces both correct kinetic statistics and correct transport measures for any of the statistically sound GJ methods. Explicit algorithmic expressions are given for the integration of the new half-step velocity into the GJ set of methods. Finally, numerical simulations, including quantum-based molecular dynamics (QMD) using the QMD suite Los Alamos Transferable Tight-Binding for Energetics, highlight the discussed properties of the algorithms as well as exhibit the direct application of robust, time-step-independent stochastic integrators to QMD.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Microemulsions in the driven Widom-Rowlinson lattice gas

An investigation of the two-dimensional Widom-Rowlinson lattice gas under an applied drive uncovered a remarkable nonequilibrium steady state in which uniform stripes (reminiscent of an equilibrium lamellar phase) form perpendicular to the drive direction [R. Dickman and R. K. P. Zia, Phys. Rev. E 97, 062126 (2018)]. Here we study this model at low particle densities in two and three dimensions, where we find a disordered phase with a characteristic length scale (a “microemulsion”) along the drive direction. Further we develop a continuum theory of this disordered phase to derive a coarse-grained field-theoretic action for the nonequilibrium dynamics. The action has the form of two coupled driven diffusive systems with different characteristic velocities, generated by an interplay between the particle repulsion and the drive. We then show how fluctuation corrections in the field theory may generate the characteristic features of the microemulsion phase, including a peak in the static structure factor corresponding to the characteristic length scale. This work lays the foundation for understanding the stripe phenomenon more generally.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Optimal white-noise stochastic forcing for linear models of turbulent channel flow

In the present study an optimisation problem is formulated to determine the forcing of an eddy-viscosity-based linearised Navier–Stokes model in channel flow at $Re_\tau \approx 5200$ ( $Re_\tau$ is the friction Reynolds number), where the forcing is white-in-time and spatially decorrelated. The objective functional is prescribed such that the forcing drives a response to best match a set of velocity spectra from direct numerical simulation (DNS), as well as remaining sufficiently smooth. Strong quantitative agreement is obtained between the velocity spectra from the linear model with optimal forcing and from DNS, but only qualitative agreement between the Reynolds shear stress co-spectra from the model and DNS. The forcing spectra exhibit a level of self-similarity, associated with the primary peak in the velocity spectra, but they also reveal a non-negligible amount of energy spent in phenomenologically mimicking the non-self-similar part of the velocity spectra associated with energy cascade. By exploiting linearity, the effect of the individual forcing components is assessed and the contributions from the Orr mechanism and the lift-up effect are also identified. Finally, the effect of the strength of the eddy viscosity on the optimisation performance is investigated. The inclusion of the eddy viscosity diffusion operator is shown to be essential in modelling of the near-wall features, while still allowing the forcing of the self-similar primary peak. In particular, reducing the strength of the eddy viscosity results in a considerable increase in the near-wall forcing of wall-parallel components.

Mechanics↗

DOE OSTI2017

Modeling of dislocation channel width evolution in irradiated metals

Defect-free dislocation channel formation has been reported to promote plastic instability during tensile testing via localized plastic flow, leading to a distinct loss of ductility and strain hardening in many low-temperature irradiated materials. In order to study the underlying mechanisms governing dislocation channel width and formation, the channel formation process is modeled via a simple stochastic dislocation-jog process dependent upon grain size, defect cluster density, and defect size. Dislocations traverse a field of defect clusters and jog stochastically upon defect interaction, forming channels of low defect-density. And based upon prior molecular dynamics (MD) simulations and in-situ experimental transmission electron microscopy (TEM) observations, each dislocation encounter with a dislocation loop or stacking fault tetrahedron (SFT) is assumed to cause complete absorption of the defect cluster, prompting the dislocation to jog up or down by a distance equal to half the defect cluster diameter. Channels are predicted to form rapidly and are comparable to reported TEM measurements for many materials. Predicted channel widths are found to be most strongly dependent on mean defect size and correlated well with a power law dependence on defect diameter and density, and distance from the dislocation source. Due to the dependence of modeled channel width on defect diameter and density, maximum channel width is predicted to slowly increase as accumulated dose increases. The relatively weak predicted dependence of channel formation width with distance, in accordance with a diffusion analogy, implies that after only a few microns from the source, most channels observed via TEM analyses may not appear to vary with distance because of limitations in the field-of-view to a few microns. Furthermore, examinations of the effect of the so-called “source-broadening” mechanism of channel formation showed that its effect is simply to add a minimum thickness to the channel without affecting channel dependence on the given parameters.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Dark-matter halo assembly bias: Environmental dependence in the non-Markovian excursion-set theory

In the standard excursion-set model for the growth of structure, the statistical properties of halos are governed by the halo mass and are independent of the larger-scale environment in which the halos reside. Numerical simulations, however, have found the spatial distributions of halos to depend not only on their mass but also on the details of their assembly history and environment. Here we present a theoretical framework for incorporating this 'assembly bias' into the excursion-set model. Our derivations are based on modifications of the path-integral approach of Maggiore and Riotto that models halo formation as a non-Markovian random-walk process. The perturbed density field is assumed to evolve stochastically with the smoothing scale and exhibits correlated walks in the presence of a density barrier. We write down conditional probabilities for multiple barrier crossings and derive from them analytic expressions for descendant and progenitor halo mass functions and halo merger rates as a function of both halo mass and the linear overdensity δ {sub e} of the larger-scale environment of the halo. Our results predict a higher halo merger rate and higher progenitor halo mass function in regions of higher overdensity, consistent with the behavior seen in N-body simulations.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Conditional Karhunen-Loève expansion for uncertainty quantification and active learning in partial differential equation models

We use a conditional Karhunen-Lo` eve (KL) model to quantify and reduce uncertainty in a stochastic partial differential equation (SPDE) problem with partially-known space-dependent coefficient, Y (x). We assume that a small number of Y (x) measurements are available and model Y (x) with a KL expansion. We achieve reduction in uncertainty by conditioning the KL expansion coefficients on measurements. We consider two approaches for conditioning the KL expansion: In Approach 1, we condition the KL model first and then truncate it. In Approach 2, we first truncate the KL expansion and then condition it. We employ the conditional KL expansion together with Monte Carlo and sparse grid collocation methods to compute the moments of the solution of the SPDE problem. Uncertainty of the problem is further reduced by adaptively selecting additional observation locations using two active learning methods. Method 1 minimizes the variance of the PDE coefficient, while Method 2 minimizes the variance of the solution of the PDE. We demonstrate that conditioning leads to dimension reduction of the KL representation of Y (x). For a linear diffusion SPDE with uncertain log-normal coefficient, we show that Approach 1 provides a more accurate approximation of the conditional log-normal coefficient and solution of the SPDE than Approach 2 for the same number of random dimensions in a conditional KL expansion. Furthermore, Approach 2 provides a good estimate for the number of terms of the truncated KL expansion of the conditional field of Approach 1. Finally, we demonstrate that active learning based on Method 2 is more efficient for uncertainty reduction in the SPDE’s states (i.e., it leads to a larger reduction of the variance) than active learning using Method 2.

Conditioned Karhunen-Lo` eve expanion, machine lea↗

DOE OSTI2018

Stochastic Simulation of Complex Fluid Flows (Progress Report for period 07/01/2016 - 06/30/2018)

At a microscopic scale, fluids are composed of molecules whose positions and velocities are random. This gives rise to thermal fluctuations that span the whole range of scales from the microscopic through the mesoscopic, and even the macroscopic. The inclusion of thermal fluctuations is crucial in multi-scale models, which are an important theme in the research program of the DOE Office of Science, and in particular the ASCR Applied Mathematics program's priority focus area on modeling of complex systems involving processes that span vastly different time and/or length scales. In this five-year Early Career project, the PI Aleksandar Donev and collaborators developed computational algorithms for modeling complex fluid mixtures at small scales using a formulation based on fluctuating hydrodynamics. Novel computational methods were developed to model complex fluids with increasing physical complexity, starting from binary miscible and immiscible mixtures, going through multispecies non-reactive and reactive mixtures, and culminating with reactive electrolytes mixtures of neutral molecules and ions. In close collaboration with the group of John Bell at Lawrence Berkeley National Laboratory, the methods were implemented in a scalable computational framework suitable for modern parallel supercomputers, and made publicly available on github. A number of physical examples in which giant nonequilibrium fluctuations are improtant were studied, with a special focus on instabilities at a liquid-liquid interface driven by gravity, diffusion, reactions, and/or electric fields. The methods and codes developed in this project are expected to enable other novel applications in the DOE Basic Energy Sciences program, and engineering sciences more broadly.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

COMBINING DIFFUSIVE SHOCK ACCELERATION WITH ACCELERATION BY CONTRACTING AND RECONNECTING SMALL-SCALE FLUX ROPES AT HELIOSPHERIC SHOCKS

Computational and observational evidence is accruing that heliospheric shocks, as emitters of vorticity, can produce downstream magnetic flux ropes and filaments. This led Zank et al. to investigate a new paradigm whereby energetic particle acceleration near shocks is a combination of diffusive shock acceleration (DSA) with downstream acceleration by many small-scale contracting and reconnecting (merging) flux ropes. Using a model where flux-rope acceleration involves a first-order Fermi mechanism due to the mean compression of numerous contracting flux ropes, Zank et al. provide theoretical support for observations that power-law spectra of energetic particles downstream of heliospheric shocks can be harder than predicted by DSA theory and that energetic particle intensities should peak behind shocks instead of at shocks as predicted by DSA theory. In this paper, a more extended formalism of kinetic transport theory developed by le Roux et al. is used to further explore this paradigm. We describe how second-order Fermi acceleration, related to the variance in the electromagnetic fields produced by downstream small-scale flux-rope dynamics, modifies the standard DSA model. The results show that (i) this approach can qualitatively reproduce observations of particle intensities peaking behind the shock, thus providing further support for the new paradigm, and (ii) stochastic acceleration by compressible flux ropes tends to be more efficient than incompressible flux ropes behind shocks in modifying the DSA spectrum of energetic particles.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

Random effects of fissile lumps in molten salt reactors

The problem of the effect of fissile lumps spatially appearing in a random fashion inside a fluid fuel reactor is addressed. The effect on reactivity is evaluated by means of first-order perturbation theory. The analysis is carried out in diffusion theory with the presence of delayed neutron emissions in one dimensional plane geometry. The estimation of the mean value and standard deviation of the reactivity inserted is performed by Monte Carlo simulations and a deterministic quadrature approach, to compare the methods in terms of computational effort and the accuracy of the results. The results presented show that the effects constitute an important issue in the assessment of these innovative systems. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

Runaway electron deconfinement in SPARC and DIII-D by a passive 3D coil

The operation of a 3D coil—passively driven by the current quench (CQ) loop voltage—for the deconfinement of runaway electrons (REs) is modeled for disruption scenarios in the SPARC and DIII-D tokamaks. Nonlinear magnetohydrodynamic (MHD) modeling is carried out with the NIMROD code including time-dependent magnetic field boundary conditions to simulate the effect of the coil. Further modeling in some cases uses the ASCOT5 code to calculate advection and diffusion coefficients for REs based on the NIMROD-calculated fields, and the DREAM code to compute the runaway evolution in the presence of these transport coefficients. Compared with similar modeling in Tinguely et al (2021 Nucl. Fusion 61 124003), considerably more conservative assumptions are made with the ASCOT5 results, zeroing low levels of transport, particularly in regions in which closed flux surfaces have reformed. Of three coil geometries considered in SPARC, only the n = 1 coil is found to have sufficient resonant components to suppress the runaway current growth. Without the new conservative transport assumptions, full suppression of the RE current is maintained when the thermal quench MHD is included in the simulation or when the RE current is limited to 250kA, but when transport in closed flux regions is fully suppressed, these scenarios allow RE beams on the order of 1–2 MA to appear. Additional modeling is performed to consider the effects of the close ideal wall. In DIII-D, the CQ is modeled for both limited and diverted equilibrium shapes. In the limited shape, the onset of stochasticity is found to be insensitive to the coil current amplitude and governed largely by the evolution of the safety-factor profile. In both devices, prediction of the q-profile evolution is seen to be critical to predicting the later time effects of the coil.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2013

Realistic multisite lattice-gas modeling and KMC simulation of catalytic surface reactions: Kinetics and multiscale spatial behavior for CO-oxidation on metal (100) surfaces

A realistic molecular-level description of catalytic reactions on single-crystal metal surfaces can be provided by stochastic multisite lattice-gas (msLG) models. This approach has general applicability, although in this report, we will focus on the example of CO-oxidation on the unreconstructed fcc metal (100) or M(100) surfaces of common catalyst metals M = Pd, Rh, Pt and Ir (i.e., avoiding regimes where Pt and Ir reconstruct). These models can capture the thermodynamics and kinetics of adsorbed layers for the individual reactants species, such as CO/M(100) and O/M(100), as well as the interaction and reaction between different reactant species in mixed adlayers, such as (CO + O)/M(100). The msLG models allow population of any of hollow, bridge, and top sites. This enables a more flexible and realistic description of adsorption and adlayer ordering, as well as of reaction configurations and configuration-dependent barriers. Adspecies adsorption and interaction energies, as well as barriers for various processes, constitute key model input. The choice of these energies is guided by experimental observations, as well as by extensive Density Functional Theory analysis. Model behavior is assessed via Kinetic Monte Carlo (KMC) simulation. We also address the simulation challenges and theoretical ramifications associated with very rapid diffusion and local equilibration of reactant adspecies such as CO. These msLG models are applied to describe adsorption, ordering, and temperature programmed desorption (TPD) for individual CO/M(100) and O/M(100) reactant adlayers. In addition, they are also applied to predict mixed (CO + O)/M(100) adlayer structure on the nanoscale, the complete bifurcation diagram for reactive steady-states under continuous flow conditions, temperature programmed reaction (TPR) spectra, and titration reactions for the CO-oxidation reaction. Extensive and reasonably successful comparison of model predictions is made with experimental data. Furthermore, we discuss the possible transition from traditional mean-field-type bistability and reaction kinetics for lower-pressure to multistability and enhanced fluctuation effects for moderate- or higher-pressure. Behavior in the latter regime reflects a stronger influence of adspecies interactions and also lower diffusivity in the higher-coverage mixed adlayer. We also analyze mesoscale spatiotemporal behavior including the propagation of reaction diffusion fronts between bistable reactive and inactive states, and associated nucleation-mediated transitions between these states. This behavior is controlled by complex surface mass transport processes, specifically chemical diffusion in mixed reactant adlayers for which we provide a precise theoretical formulation. The msLG models together with an appropriate treatment of chemical diffusivity enable equation-free heterogeneous coupled lattice-gas (HCLG) simulations of spatiotemporal behavior. In addition, msLG + HCLG modeling can describe coverage variations across polycrystalline catalysts surfaces, pressure variations across catalyst surfaces in microreactors, and could be incorporated into a multiphysics framework to describe mass and heat transfer limitations for high-pressure catalysis. (C) 2013 Elsevier Ltd. All rights reserved.

36 MATERIALS SCIENCE↗

DOE OSTI2024

DECOVALEX-2023: Task F1 Final Report

DECOVALEX-2023 Task F is a comparison of models and methods for post-closure performance assessment (PA) of a deep geologic repository for radioactive waste. The general aims of Task F are to build confidence in the models, methods, and software used for PA and to stimulate additional research and development in PA methodologies. The task objectives are to motivate development of PA modelling skills and capabilities, to examine the influence of model choices on calculated repository performance, and to compare the uncertainties introduced by model choices to other sources of uncertainty. Task F involves no actual experiment or site. It is a PA modelling exercise that requires the conceptual development of hypothetical repository designs and geologic settings. Because three of the teams were interested in salt and the rest of the teams were interested in crystalline rock, Task F was split into two branches: Task F1 for crystalline rock and Task F2 for salt. This report is for Task F1, crystalline rock. Teams from seven countries (Canada, Czech Republic, Germany, Korea, Sweden, Taiwan, and United States) participated in Task F1. The teams worked together to define the features, events, and processes of the reference case repository and established a set of performance measures. In addition, they defined a set of benchmark problems designed to test and compare modelling capabilities for fracture flow and transport at different scales. The repository design and benchmark problems are documented in a Task Specification that evolved over time as the group honed the specifications. The benchmark problems verified that each team can aptly model flow and transport in fractured media in 1-, 2-, and 3-dimensions. Two general approaches were used for the 3-dimensional benchmarks: discrete fracture network (DFN) and equivalent continuous porous medium (ECPM). DFN modelling involves explicit meshing of each fracture while ECPM modelling aims to capture the effective porosity and directional permeability of each cell in a space-filling mesh as affected by intersecting fractures. In some models, a combination of the two is used, i.e., DFN for large known fractures and ECPM for the rest of the domain. Transport is solved by using either the advection-dispersion equation or particle tracking. Although some variation is observed among model breakthrough curves in the benchmark problems, there is strong agreement in breakthrough behaviour up to at least the 75 th percentile for all benchmarks. At the 90 th percentile, breakthrough results show larger differences, suggesting several models retain substantially higher fractions of tracer in regions of slower moving water. In addition to the flow and transport benchmarks, several teams completed the source term benchmark, verifying capabilities for modelling radionuclide decay and ingrowth, waste package breach, instant release fractions, fuel matrix degradation rates, and radionuclide solubility limitations. The reference case is conceptualized as a generic spent fuel repository at a depth of 450 m in fractured crystalline rock. The repository has 50 parallel backfilled drifts, each with 50 deposition holes 6 m apart. Each deposition hole contains a 4-PWR waste package and bentonite buffer. The rock domain is 5 km in length, 2 km in width, and 1 km in depth. It has 6 deterministic fractured deformation zones and a multitude of stochastic fractures. Teams generally used the ECPM approach for the entire rock or a hybrid approach in which the deterministic fracture zones are modelled with a DFN and the rest of the rock is modelled by ECPM. Of the reference case problems specified, only the results of the initial reference case problem are compared in this report. The initial problem focuses on transport from the deposition holes to the surface, i.e., it neglects waste package performance. Tracers are released at all waste package locations at time zero and tracked for their releases to the near field and ground surface. The water fluxes calculated at the ground surface entry and exit regions of the domain are similar for all models except for two that have considerably lower fluxes. For tracer transport, large differences are observed among models in the magnitude of tracer transported. Much of the difference appears to be due to how the repository is implemented and hence the different degrees of repository simplification. Models that exclude the drifts, buffer, and backfill from the domain tend to show greater release of tracers and radionuclides from the repository. The initial study presented here indicates that major differences in modelling important processes within the repository (e.g., diffusion through buffer and backfill) can produce broadly different release and transport results, especially when those processes are excluded. Even for the models that included all specified features, events, and processes, the results show significant differences and demonstrate the importance of examining multiple modelling approaches in performance assessment. The differences in results observed in this study are expected to motivate teams to either increase complexity in future versions of the reference case models or to improve methods to account for the effects of simplified features and processes. Either way, future improvements in these models are expected to produce results that more closely agree.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2015

Diversity waves in collapse-driven population dynamics

Populations of species in ecosystems are often constrained by availability of resources within their environment. In effect this means that a growth of one population, needs to be balanced by comparable reduction in populations of others. In neutral models of biodiversity all populations are assumed to change incrementally due to stochastic births and deaths of individuals. Here we propose and model another redistribution mechanism driven by abrupt and severe collapses of the entire population of a single species freeing up resources for the remaining ones. This mechanism may be relevant e.g. for communities of bacteria, with strain-specific collapses caused e.g. by invading bacteriophages, or for other ecosystems where infectious diseases play an important role. The emergent dynamics of our system is cyclic ‘‘diversity waves’’ triggered by collapses of globally dominating populations. The population diversity peaks at the beginning of each wave and exponentially decreases afterwards. Species abundances are characterized by a bimodal time-aggregated distribution with the lower peak formed by populations of recently collapsed or newly introduced species while the upper peak - species that has not yet collapsed in the current wave. In most waves both upper and lower peaks are composed of several smaller peaks. This self-organized hierarchical peak structure has a long-term memory transmitted across several waves. It gives rise to a scale-free tail of the time-aggregated population distribution with a universal exponent of 1.7. We show that diversity wave dynamics is robust with respect to variations in the rules of our model such as diffusion between multiple environments, species-specific growth and extinction rates, and bet-hedging strategies.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2013

Year-end report on FY13 activities for J8A6

The Russian-3 (R3) HANE, a 60 km high-latitude burst with yield estimated at 300 kt, was chosen for the demonstration. This test was selected because it allowed LLNL to leverage existing funding, which was directed at extending LLNL’s capability to simulate HANEs at atmospheric altitudes (<100 km). David Larsen (LLNL) developed a new particle-tracing code that tracks monoenergetic electrons of various energies from a point source as they interact with the atmosphere, losing energy and ‘pitch-angle scattering’ as they are transported. A relatively large fraction of the initial electrons are able to escape the atmosphere and were handed off to LANL for further processing to calculate the effect on space based assets. LANL binned the electrons into a phase-space density as a function of energy and equatorial pitch-angle and showed that all of the electrons would travel along field lines to the conjugate point in the Southern hemisphere, where they would likely be absorbed, because their equatorial pitch-angles were too field-aligned to permit them to ‘mirror’ above the atmosphere and be ‘trapped’. Thus, the initial LLNL output did not produce any trapped electrons to input into LANL’s diffusion code and so no study of the long-term evolution of the trapped population and its effect on space-based assets could be performed. It was recognized that LLNL’s calculation did not properly model the low-probability, large-angle scattering associated with a single Coulomb interaction between a beta-decay electron and the nucleus of the neutral particles in the high atmosphere, which would be the dominant interaction above some altitude (>100 km) and might allow the electrons to be pitch-angle scattered sufficiently to become trapped. A second LLNL calculation that properly included this single interaction probability was conducted and the output processed by LANL. It was shown that a small fraction of the initial population (~0.01%) would be ‘locally trapped’; however, even this small population would likely be absorbed within a few minutes as the electrons drifted around earth and eventually ended up on field lines where they would be absorbed in the atmosphere. The output of the second LLNL calculation was found to produce about 4x fewer backscattered electrons than previous work (Selesnick et al 2012), and so the remainder of the FY13 LANL effort on the project was aimed at trying to resolve this discrepancy. LANL implemented a stochastic differential equation to simulate the backscatter process so that the results could be compared to Larsen and Selesnick. Initial results from this capability have been obtained, but no quantitative comparison to Larsen or Selesnick has been done yet.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

High-resolution radiation detection using Ni/SiO 2 /n-4H-SiC vertical metal-oxide-semiconductor capacitor

In this article, we demonstrate the radiation detection performance of vertical metal-oxide-semiconductor (MOS) capacitors fabricated on 20 μm thick n-4H-SiC epitaxial layers with the highest energy resolution ever reported. The 100 nm SiO2 layer was achieved on the Si face of n-4H-SiC epilayers using dry oxidation in air. The Ni/SiO2/n-4H-SiC MOS detectors not only demonstrated an excellent energy resolution of 0.42% (ΔE/E 100) for 5.48 MeV alpha particles but also caused a lower enhancement in the electronic noise components of the spectrometer compared with that observed for the best high-resolution Schottky barrier detectors. The MOS detectors also exhibited a high charge collection efficiency (CCE) of 96% at the optimized operating bias despite the presence of the oxide layer. A drift-diffusion model applied to the CCE vs gate bias voltage data revealed a minority (hole) carrier diffusion length of 24 μm. Capacitance mode deep level transient spectroscopy (C-DLTS) scans in the temperature range 84–800 K were carried out to identify the resolution limiting electrically active defects. Interestingly, the C-DLTS spectra revealed both positive and negative peaks, indicating the simultaneous presence of electron (majority) and hole (minority) trap centers. It has been inferred that at the steady-state bias for the C-DLTS measurement, the MOS detector operates in the inversion mode at certain device temperatures, causing holes to populate the minority trap centers and, hence, manifests minority carrier peaks as well.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

Asymmetric collapse by dissolution or melting in a uniform flow

An advection-diffusion-limited dissolution model of an object being eroded by a two-dimensional potential flow is presented. By taking advantage of the conformal invariance of the model, a numerical method is introduced that tracks the evolution of the object boundary in terms of a time-dependent Laurent series. Simulations of a variety of dissolving objects are shown, which shrink and collapse to a single point in finite time. The simulations reveal a surprising exact relationship, whereby the collapse point is the root of a non-Analytic function given in terms of the flow velocity and the Laurent series coefficients describing the initial shape. This result is subsequently derived using residue calculus. The structure of the non-Analytic function is examined for three different test cases, and a practical approach to determine the collapse point using a generalized Newton-Raphson root-finding algorithm is outlined. These examples also illustrate the possibility that the model breaks down in finite time prior to complete collapse, due to a topological singularity, as the dissolving boundary overlaps itself rather than breaking up into multiple domains (analogous to droplet pinch-off in fluid mechanics). In conclusion, the model raises fundamental mathematical questions about broken symmetries in finite-Time singularities of both continuous and stochastic dynamical systems.

42 ENGINEERING↗