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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 OSTI2015

Molecular hydrogen solvated in water – A computational study

The aqueous hydrogen molecule is studied with molecular dynamics simulations at ambient temperature and pressure conditions, using a newly developed flexible and polarizable H{sub 2} molecule model. The design and implementation of this model, compatible with an existing flexible and polarizable force field for water, is presented in detail. The structure of the hydration layer suggests that first-shell water molecules accommodate the H{sub 2} molecule without major structural distortions and two-dimensional, radial-angular distribution functions indicate that as opposed to strictly tangential, the orientation of these water molecules is such that the solute is solvated with one of the free electron pairs of H{sub 2}O. The calculated self-diffusion coefficient of H{sub 2}(aq) agrees very well with experimental results and the time dependence of mean square displacement suggests the presence of caging on a time scale corresponding to hydrogen bond network vibrations in liquid water. Orientational correlation function of H{sub 2} experiences an extremely short-scale decay, making the H{sub 2}–H{sub 2}O interaction potential essentially isotropic by virtue of rotational averaging. The inclusion of explicit polarizability in the model allows for the calculation of Raman spectra that agree very well with available experimental data on H{sub 2}(aq) under differing pressure conditions, including accurate reproduction of the experimentally noted trends with solute pressure or concentration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Turbulent shear-layer mixing: initial conditions, and direct-numerical and large-eddy simulations

Aspects of turbulent shear-layer mixing are investigated over a range of shear-layer Reynolds numbers, $Re_{\unicode[STIX]{x1D6FF}}=\unicode[STIX]{x0394}U\unicode[STIX]{x1D6FF}/\unicode[STIX]{x1D708}$ , based on the shear-layer free-stream velocity difference, $\unicode[STIX]{x0394}U$ , and mixing-zone thickness, $\unicode[STIX]{x1D6FF}$ , to probe the role of initial conditions in mixing stages and the evolution of the scalar-field probability density function (p.d.f.) and variance. Scalar transport is calculated for unity Schmidt numbers, approximating gas-phase diffusion. The study is based on direct-numerical simulation (DNS) and large-eddy simulation (LES), comparing different subgrid-scale (SGS) models for incompressible, uniform-density, temporally evolving forced shear-layer flows. Moderate-Reynolds-number DNS results help assess and validate LES SGS models in terms of scalar-spectrum and mixing estimates, as well as other metrics, to $Re_{\unicode[STIX]{x1D6FF}}\lesssim 3.3\times 10^{4}$ . High-Reynolds-number LES investigations to $Re_{\unicode[STIX]{x1D6FF}}\lesssim 5\times 10^{5}$ help identify flow parameters and conditions that influence the evolution of scalar variance and p.d.f., e.g. marching versus non-marching. Initial conditions that generate shear flows with different mixing behaviour elucidate flow characteristics in each flow regime and identify elements that induce p.d.f. transition and scalar-variance behaviour. P.d.f. transition is found to be largely insensitive to local flow parameters, such as $Re_{\unicode[STIX]{x1D6FF}}$ , or a previously proposed vortex-pairing parameter based on downstream distance, or other equivalent criteria. The present study also allows a quantitative comparison of LES SGS models in moderate- and high- $Re_{\unicode[STIX]{x1D6FF}}$ forced shear-layer flows.

Mechanics↗
DOE OSTI2020

Tracking Radioactive Isotopes in HVAC and Application for Hot Cell Analyses - 20155

In recent years, the surge in the number of isotope production facilities under design has increased the need to analyze isotope migration in facility Heating, Ventilation, and Air Conditioning (HVAC) during normal operations and accident scenarios. These facilities are used to produce isotopes for medical, security, and industrial applications and as such are subject to license and regulatory requirements 10CFR20, 10CFR30, 10CFR50, and 10CFR70. GOTHIC, a general-purpose thermal-hydraulics software package, includes the ability to model isotopic tracers, radioactive decay and isotope migration as well as HEPA and charcoal filters for isotope retention. A GOTHIC model was developed by Zachry Nuclear Engineering (ZNE) to examine the effect of negative room pressure, HEPA filtration, and HVAC fluctuations on radiation areas, hot cells and gloveboxes. Radioactive tracers were used to simulate the concentration of spills within contaminated areas, track the migration of isotopes of interest, and determine the isotopic retention and buildup on facility HEPA filters. A variety of isotopes with concern to dose (e.g., Kr-85, Sr-90, I-131, etc.), including their decay and progeny, are included in the analysis. Negative pressures are maintained in the regions of interest by a representative central HVAC system equipped with a volumetric fan that exhausts to the environment after a series of isolation valves and HEPA filters. GOTHIC is an industry trusted tool for providing engineering solutions for a variety of applications, including fission product tracking, aerosol and particulate transport and ventilation assessments. The software provides an integrated analysis environment that includes a graphical user interface (GUI) for constructing analysis models, a numerical solver that includes parallel processing capabilities and a post-processor for evaluating simulation results. It solves the conservation equations for mass, momentum and energy for multicomponent, multi-phase flow in lumped parameter and multi-dimensional geometries (1, 2, or full 3D), including the effects of turbulence, diffusion and buoyancy. It has been developed and maintained under a Quality Assurance program in compliance with the requirements of 10CFR50 Appendix B and applicable portions of ASME NQA-1 since 1995. GOTHIC has been used for assessing both forced and natural convection conditions for a wide range of applications, including: - Tracking concentration of hazardous gases and chemicals for habitability and safety assessments - Determining ventilation and filtration requirements and optimizing location and arrangement of these systems - Room heat-up, including diverse and Flexible coping strategies for Extended Loss of AC Power (FLEX/ELAP) - Equipment Qualification (EQ) A distinctive feature of GOTHIC is the ability to track many different fields/substances in a simulation, including user defined tracer elements, in the liquid, vapor and droplet fields as well as surfaces and filters. This capability allows GOTHIC to model fission product transport and release or the removal of particulates or harmful toxins from exhaust gases using a spray scrubber or other types of filtration systems. GOTHIC also includes models for engineered equipment, such as fans, filters, charcoal filters, dryers/demisters, dampers, etc. The aerosols and other filtered material are removed or accumulated in these components. The range of aerosol and radiological applications that GOTHIC has been used for includes: - Source Term: Primary Coolant (Equilibrium) Activity; Non-Water Coolant Source/Leakage. - Conditions for Iodine Re-evolution: Sump/Suppression Pool Conditions and pH; - RWST Conditions and pH. - Isotope Removal Mechanisms: Containment Sprayed and Unsprayed Region Mixing; Charcoal Filter Heating due to Iodine decay. - Radionuclide Transport and Decay: Post-LOCA Release in containment; Transport between connected Compartments and vent systems; Groundwater transport of radionuclides. - Non-Newtonian Fluid modeling for sludge, waste tanks, etc. ADAMS ML071581053 (titled 'Best Practice Guidelines for the use of CFD in Nuclear Reactor Safety Applications') poses guidelines for applying single phase CFD codes in nuclear reactor safety problems and GOTHIC is listed as a 'tool for 3D flows' and 'dispersal and deposition of radionuclides.' The Nuclear Quality Assurance (NQA) pedigree of GOTHIC is an important aspect for applications in the nuclear industry. The fundamental tracer models (convective transport, molecular and turbulent diffusion, removal mechanisms, etc.) have been verified using analytical solutions and validated against applicable separate effects tests. Also, GOTHIC has been benchmarked to many integrated effects tests, including Phebus FP (Fission Product). GOTHIC gives good agreement for the buildup and decay of fission products in Phebus Test 3. The model developed by ZNE demonstrates GOTHIC's applicability and acceptability for use in analyzing the migration and retention of radioactive isotopes and their progeny in normal operation and accident scenario analyses for isotope production facilities, hot cells, and gloveboxes. The tracer activities calculated by GOTHIC can then be used in downstream radiation transport and shielding codes like RADTRAD-NAI{sup C}, MCNP{sup R}, and MicroShield{sup R} to determine on-site and of-site doses. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Imaging and Modeling of Passive Water Management in a Miniature Fuel Cell

A small microwatt fuel cell stack with 8 cells was designed, fabricated, and tested for passive operation with pure H 2 and O 2 to provide continuous power for multiple decades with uncontrolled fluctuating ambient conditions. The stack was designed to operate with dead ended gas flows with water removal via passive membrane diffusion to notches in the bipolar plates. Two stacks with active areas of 0.2 cm 2 , one with 200 nm of membrane and the other with 400 urn, were assembled and tested at varying temperatures and current conditions. Temperatures ranged -55 °C to 70 °C, with focus on the lower temperatures. Factors affecting water production and removal included temperature, gas crossover, and membrane thickness. Currents were applied from 16 uA to 10 mA after the cells were stabilized at temperature, followed by a period of drying to observe water transport to the external peripheries of the cell. Finally, a two-dimensional multiphysics model was developed to further explore the water management system in varying conditions.

25 ENERGY STORAGE↗
DOE OSTI2024

Temperature effect on turbulent burning velocity of lean premixed hydrogen/air flames

Hydrogen has drawn great attention in recent years as a carbon-free fuel. The turbulent burning velocity (S T ) is an important parameter for the design and modeling of hydrogen-fueled engines given the high propagation speed of hydrogen flames. It has been well documented that S T of hydrogen flames can be dramatically increased by thermo-diffusive effects which are sensitive to thermodynamic conditions. Previous studies have mainly focused on the pressure effect on S T of lean hydrogen flames, while the temperature effect has been largely ignored. Here, in the present study, the turbulent burning velocity for a lean hydrogen/air mixture over a wide range of temperatures (300–641 K) and pressures (1–15 atm) is investigated through direct numerical simulations of statistically planar turbulent premixed flames. Results show that the variation of normalized turbulent burning velocity (S T /S L , where S L is the laminar flame speed) with temperature and pressure is mainly controlled by the variation of the stretching factor I 0 . While S T /S L is only marginally dependent on temperature at the atmospheric pressure, it exhibits a decreasing trend with temperature at an elevated pressure (10 atm). This is associated with different temperature dependencies of flame surface area enlargement at the two different pressures, despite the monotonically decreasing trends of I 0 with temperature at both pressures. In addition, under engine-relevant conditions where the temperature and pressure increase simultaneously, the promotion effect of pressure is found to be largely canceled out by the suppression effect of temperature, leading to only a slight increase in I 0 and S T /S L . The observed trends are further explained through detailed flame dynamic analysis. Furthermore, I 0 at different temperatures and pressures is found to correlate very well with the enhancement of fuel consumption rate in the critically strained laminar flames. The present study elucidates the strong impact of temperature on S T of lean premixed hydrogen/air flames at elevated pressures and provides new insights into the modeling of S T , especially for engine-relevant conditions.

Wang, Yiqing [Argonne National Laboratory (ANL), A↗
DOE OSTI2018

Final technical report

This final report covers the final year of the project. Reports from previous years were included in the group report for that year. The objective of this part of the project was to compare results from two large-scale, nonlinear plasma simulation codes based on magnetohydrodynamics, M3D and M3D-C1, for plasma edge instabilities. This is a difficult undertaking and the comparison was only partially successful because, while the MHD equations are standard, there are a number of valid MHD models of the plasma dissipation that make different approximations to their physics and the numerical implementation of a given model can be quite different depending on the way that the rest of the equations are solved. Large differences arise, and have major effects on the predicted plasma behavior, in the case of the greatest interest to this project, the plasma edge region under conditions where the plasma edge instabilities are strongest and the background plasma changes abruptly from interior hot, dense conditions to an unconfined, cool, diffuse plasma outside the magnetic boundary surface. Experimental observations only partially measure the background plasma and there are many non-MHD processes that can have important effects (studied in the rest of the project). Comparisons for edge instabilities at very small amplitude, the so-called linear modes, had showed good agreement for a few interior plasma instabilities, but strong differences between the default models for the plasma edge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Nitrogen mass transfer models for plasma-based low-energy ion implantation

The nitrogen mass transfer process in plasma-based low-energy ion implantation (PBLEII) is theoretically and experimentally studied in order to explore the process mechanism of PBLEII and therefore to optimize the apparatus design and the process conditions. An electron cyclotron resonance (ECR) microwave discharge generates the nitrogen plasma with a high density of 10{sup 11}–10{sup 12} ions/cm{sup 3}, which diffuses downstream to the process chamber along the divergent magnetic field. The nitrogen ions in the plasma implant into the surface and transport to the matrix of an austenitic stainless steel under the low negative pulsed bias of −2 kV at a process temperature of 400 °C. A global plasma model is used to simulate the ECR microwave plasma discharge for a range of working pressures and microwave powers. The fluid models are adopted to calculate the plasma downstream diffusion, the sheath expansion and the low-energy ion implantation on the surface. A nonlinear kinetic discrete model is established to describe the nitrogen transport in the austenitic stainless steel and the results are compared with the experimental measurements. Under an average implantation current density of 0.3–0.6 mA/cm{sup 2}, the surface nitrogen concentration in the range from 18.5 to 29 at. % is a critical factor for the nitrogen transport in the AISI 304 austenitic stainless steel by PBLEII, which accelerates the implanted nitrogen diffusion inward up to 6–12 μm during a nitriding time of 4 h.

36 MATERIALS SCIENCE↗
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 OSTI2014

The Coal-Seq III Consortium. Advancing the Science of CO 2 Sequestration in Coal Seam and Gas Shale Reservoirs

The Coal-Seq consortium is a government-industry collaborative that was initially launched in 2000 as a U.S. Department of Energy sponsored investigation into CO2 sequestration in deep, unmineable coal seams. The consortium’s objective aimed to advancing industry’s understanding of complex coalbed methane and gas shale reservoir behavior in the presence of multi-component gases via laboratory experiments, theoretical model development and field validation studies. Research from this collaborative effort was utilized to produce modules to enhance reservoir simulation and modeling capabilities to assess the technical and economic potential for CO2 storage and enhanced coalbed methane recovery in coal basins. Coal-Seq Phase 3 expands upon the learnings garnered from Phase 1 & 2, which has led to further investigation into refined model development related to multicomponent equations-of-state, sorption and diffusion behavior, geomechanical and permeability studies, technical and economic feasibility studies for major international coal basins the extension of the work to gas shale reservoirs, and continued global technology exchange. The first research objective assesses changes in coal and shale properties with exposure to CO2 under field replicated conditions. Results indicate that no significant weakening occurs when coal and shale were exposed to CO2, therefore, there was no need to account for mechanical weakening of coal due to the injection of CO2 for modeling. The second major research objective evaluates cleat, Cp, and matrix, Cm, swelling/shrinkage compressibility under field replicated conditions. The experimental studies found that both Cp and Cm vary due to changes in reservoir pressure during injection and depletion under field replicated conditions. Using laboratory data from this study, a compressibility model was developed to predict the pore-volume compressibility, Cp, and the matrix compressibility, Cm, of coal and shale, which was applied to modeling software to enhance model robustness. Research was also conducted to improve algorithms and generalized adsorption models to facilitate realistic simulation of CO2 sequestration in coal seams and shale gas reservoirs. The interaction among water and the adsorbed gases, carbon dioxide (CO2), methane (CH4), and nitrogen (N2) in coalbeds is examined using experimental in situ laboratory techniques to comprehensively model CBM production and CO2 sequestration in coals. An equation of state (EOS) module was developed which is capable of predicting the density of pure components and mixtures involving the wet CBM gases CH4, CO2, and N2 at typical reservoir condition, and is used to inform CO2 injection models. The final research objective examined the effects adsorbed CO2 has on coal strength and permeability. This research studied the weakening or failure of coal by the adsorption of CO2 from empirically derived gas production data to develop models for advanced modeling of permeability changes during CO2 sequestration. The results of this research effort have been used to construct a new and improved model for assessing changes in permeability of coal reservoirs due CO2 injection. The modules developed from these studies and knowledge learned are applied to field validation and basin assessment studies. These data were used to assess the flow and storage of CO2 in a shale reservoir, test newly developed code against large-scale projects, and conduct a basin-oriented review of coal storage potential in the San Juan Basin. The storage potential and flow of CO2 was modeled for shale sequestration of a proprietary Marcellus Shale horizontal gas production well using COMET3 simulation software. Simulation results from five model runs indicate that stored CO2 quantities are linked to the duration of primary production preceding injection. Matrix CO2 saturation is observed to increase in each shale zone after injection with an increase in primary production, and the size of the CO2 plume is also observed to increase in size the longer initial production is sustained. The simulation modules developed around the Coal-Seq experimental work are also incorporated into a pre-existing large-scale numerical simulation model of the Pump Canyon CO2-ECBM pilot in the San Juan Basin. The new model was applied to re-history match the data set to explore the improvements made in permeability prediction against previously published data sets and to validate this module. The assessment of the new data, however, indicates that the impact of the variable Cp is negligible on the overall behavior of the coal for CO2 storage purposes. Applying these new modules, the San Juan Basin and the Marcellus Shale are assessed for their technical ECBM/AGR and CO2 storage potential and the economic potential of these operations. The San Juan Basin was divided into 4 unique geographic zones based on production history, and the Marcellus was divided into nine. Each was assessed based upon each zone’s properties, and simulations were run to assess the potential of full Basin development. Models of a fully developed San Juan Basin suggest the potential for up to 104 Tcf of CO2 storage, and 12.3 Tcf of methane recovery. The Marcellus models suggest 1,248 Tcf of CO2 storage and 924 Tcf of AGR. The economics are deemed favorable where credits cover the cost of CO2 in the San Juan Basin, and in many cases in the Marcellus, but to maximize storage potential, credits need to extend to pay the operator to store CO2.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2017

Nanoscopic dynamics of bicontinous microemulsions: effect of membrane associated protein

Bicontinous microemulsions (BμE) generally consist of nanodomains formed by surfactant in a mixture of water and oil at nearly equal proportions and are potential candidates for the solubilization and purification of membrane proteins. In this paper, we present the first time report of nanoscopic dynamics of surfactant monolayers within BμEs formed by the anionic surfactant sodium dodecyl sulfate (SDS) measured on the nanosecond to picosecond time scale using quasielastic neutron scattering (QENS). BμEs investigated herein consisted of middle phases isolated from Winsor-III microemulsion systems that were formed by mixing aqueous and oil solutions under optimal conditions. QENS data indicates that surfactants undergo two distinct motions, namely (i) lateral motion along the surface of the oil nanodomains and (ii) localized internal motion. Lateral motion can be described using a continuous diffusion model, from which the lateral diffusion coefficient is obtained. Internal motion of surfactant is described using a model which assumes that a fraction of the surfactants’ hydrogens undergoes localized translational diffusion that could be considered confined within a spherical volume. The effect of cytochrome c, an archetypal membrane-associated protein known to strongly partition near the surfactant head groups in BμEs (a trend supported by small-angle X-ray scattering [SAXS] analysis), on the dynamics of BμE has also been investigated. QENS results demonstrated that cytochrome c significantly hindered both the lateral and the internal motions of surfactant. The lateral motion was more strongly affected: a reduction of the lateral diffusion coefficient by 33% was measured. This change is mainly attributable to the strong association of cytochrome c with oppositely charged SDS. In contrast, analysis of SAXS data suggested that thermal fluctuations (for a longer length and slower time scale compared to QENS) were increased upon incorporation of cytochrome c. Finally, this study demonstrates the utility of QENS for evaluating dynamics of BμEs in nanoscopic region, and that proteins directly affect the microscopic dynamics, which is of relevance for evaluating release kinetics of encapsulated drugs from BμE delivery systems and the use of BμEs as biomembrane mimetic systems for investigating membrane protein–biomembrane interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Impact of oxidation and carbonation on the release rates of iodine, selenium, technetium, and nitrogen from a cementitious waste form

Evaluation of the long-term retention mechanisms and potential release rates for the primary constituents of potential concern (COPCs) (i.e., Tc, I, Se, and nitrate) is necessary to determine if Cast Stone, a radioactive waste form, can meet performance objectives under near-surface disposal scenarios. In this work, a mineral and parameter set accounting for the solubility of I and Se in Cast Stone was developed based on pH-dependent and monolithic diffusion leaching test results, to extend a geochemical speciation model previously developed. The impact of oxidation and carbonation as environmental aging processes on the retention properties of Cast Stone for primary COPCs was systematically estimated. Physically, the effective diffusion coefficients of 4 COPCs in Cast Stone were increased after carbonation and/or oxidation, reflecting an increase in permeability to diffusion. Chemically, i) pH & pe conditions in the original Cast Stone were favorable for the stabilization of Tc, but not for I, Se, and N; ii) oxidation (with/without carbonation) of Cast Stone changed the pe & pH conditions to be detrimental for Tc stabilization; and iii) carbonation (with/without oxidation) of Cast Stone modified the pH & pe conditions to be beneficial for the stabilization of I (in system with Ag added) and Se.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Current transport mechanisms in mercury cadmium telluride diode

This paper reports the results of modelling of the current-voltage characteristics (I-V) of a planar mid-wave Mercury Cadmium Telluride photodiode in a gate controlled diode experiment. It is reported that the diode exhibits nearly ideal I-V characteristics under the optimum surface potential leading to the minimal surface leakage current. Deviations from the optimum surface potential lead to non ideal I–V characteristics, indicating a strong relationship between the ideality factor of the diode with its surface leakage current. Diode's I–V characteristics have been modelled over a range of gate voltages from −9 V to −2 V. This range of gate voltages includes accumulation, flat band, and depletion and inversion conditions below the gate structure of the diode. It is shown that the I–V characteristics of the diode can be very well described by (i) thermal diffusion current, (ii) ohmic shunt current, (iii) photo-current due to background illumination, and (iv) excess current that grows by the process of avalanche multiplication in the gate voltage range from −3 V to −5 V that corresponds to the optimum surface potential. Outside the optimum gate voltage range, the origin of the excess current of the diode is associated with its high surface leakage currents. It is reported that the ohmic shunt current model applies to small surface leakage currents. The higher surface leakage currents exhibit a nonlinear shunt behaviour. It is also shown that the observed zero-bias dynamic resistance of the diode over the entire gate voltage range is the sum of ohmic shunt resistance and estimated zero-bias dynamic resistance of the diode from its thermal saturation current.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Strengthening model development and effects of low diffusing solutes to coarsening resistance in aluminum alloys

A modified Orowan strengthening model is proposed to account for finite rod-shaped precipitates with hemispherical caps in aluminum alloy systems. A combined computational and experimental approach is used to study the influences of anisotropic Orowan looping and solute-dislocation interaction on temperature-dependent yield strength. Here, the strengthening model is validated with a dataset containing 297 experimental precipitate geometries, chemistries, temperatures, and strength measurements, and achieves a strong predictive correlation of 0.8713 with experimentally measured yield strengths. Under conditions that are applicable to coarsening, constant particle volume fraction and aspect ratio, the model predicts that short rod precipitates provide far superior strengthening effects compared to plate precipitates. A cast Al-Si-Mg-Cu alloy with rod-shaped Q-phase (Al 3 Cu 2 Mg 9 Si 7 ) precipitates was developed with a novel chemistry exploring the use of low-diffusivity elements (Mn, Ni, V, Zr) to limit precipitate coarsening. The thermodynamic behavior of Mn, Ni, V, and Zr across the Q-phase interface is examined using transmission electron microscopy (TEM), first-principles density-functional theory (DFT) calculations. and atom-probe tomography (APT). DFT calculations utilizing TEM identified Q-phase/Al-matrix interfaces show that Mn, Ni, V, and Zr preferentially segregate to the Q-phase precipitate boundaries which suggests inhibition of precipitate coarsening and higher strengths after temperature exposure. Atom-probe tomography confirms solute atom partitioning/segregation at the Q-phase/Al-matrix interface, found in the modified commercial AS7GU alloy (A356 +0.5%Cu), which supports these observations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Analytical modeling for redox flow battery design

Deeper market penetration of redox flow batteries requires optimization of the cell performance. Though important for optimization, detailed analytical solutions have not been developed for electrolyte flow, mass and charge transport, and reaction kinetics within redox flow batteries. To this end, here we present analytical solutions to active species concentration and over-potential based on advection-diffusion transport for ions and Bulter-Volmer model for interface reaction kinetics. The solutions were validated with results from a finite element model. These solutions were then applied to investigate the relationship between over-potential and state of charge, current density, reaction rate constant, flow velocity, diffusivity, total active species concentration, and electrode structure. Explicit formulas were identified for minimum activation over-potential and limiting current density as well as their dependence on electrolyte properties, operation conditions, and electrode structure. With our new mathematical formulas, this work provides a theoretical framework for flow battery design.

25 ENERGY STORAGE↗
DOE OSTI2017

The Weakly Nonlinear Magnetorotational Instability in a Local Geometry

The magnetorotational instability (MRI) is a fundamental process of accretion disk physics, but its saturation mechanism remains poorly understood despite considerable theoretical and computational effort. We present a multiple-scales analysis of the non-ideal MRI in the weakly nonlinear regime—that is, when the most unstable MRI mode has a growth rate asymptotically approaching zero from above. Here, we develop our theory in a local, Cartesian channel. Our results confirm the finding by Umurhan et al. that the perturbation amplitude follows a Ginzburg–Landau equation. We further find that the Ginzburg–Landau equation will arise for the local MRI system with shear-periodic boundary conditions, when the effects of ambipolar diffusion are considered. A detailed force balance for the saturated azimuthal velocity and vertical magnetic field demonstrates that, even when diffusive effects are important, the bulk flow saturates via the combined processes of reducing the background shear and rearranging and strengthening the background vertical magnetic field. We directly simulate the Ginzburg–Landau amplitude evolution for our system, and demonstrate the pattern formation our model predicts on long scales of length- and timescales. We compare the weakly nonlinear theory results to a direct numerical simulation of the MRI in a thin-gap Taylor Couette flow.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

A double-layer based model of ion confinement in electron cyclotron resonance ion source

The paper proposes a new model of ion confinement in ECRIS, which can be easily generalized to any magnetic configuration characterized by closed magnetic surfaces. Traditionally, ion confinement in B-min configurations is ascribed to a negative potential dip due to superhot electrons, adiabatically confined by the magneto-static field. However, kinetic simulations including RF heating affected by cavity modes structures indicate that high energy electrons populate just a thin slab overlapping the ECR layer, while their density drops down of more than one order of magnitude outside. Ions, instead, diffuse across the electron layer due to their high collisionality. This is the proper physical condition to establish a double-layer (DL) configuration which self-consistently originates a potential barrier; this “barrier” confines the ions inside the plasma core surrounded by the ECR surface. The paper will describe a simplified ion confinement model based on plasma density non-homogeneity and DL formation.

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

A Public-Private-Acadmic Partnership to Advance Solar Power Forecasting

The National Center for Atmospheric Research (NCAR) is pleased to have led a partnership to advance the state-of-the-science of solar power forecasting by designing, developing, building, deploying, testing, and assessing the SunCast™ Solar Power Forecasting System. The project has included cutting edge research, testing in several geographically- and climatologically-diverse high penetration solar utilities and Independent System Operators (ISOs), and wide dissemination of the research results to raise the bar on solar power forecasting technology. The partners include three other national laboratories, six universities, and industry partners. This public-private-academic team has worked in concert to perform use-inspired research to advance solar power forecasting through cutting-edge research to advance both the necessary forecasting technologies and the metrics for evaluating them. The project has culminated in a year-long, full-scale demonstration of provide irradiance and power forecasts to utilities and ISOs to use in their operations. The project focused on providing elements of a value chain, beginning with the weather that causes a deviation from clear sky irradiance and progresses through monitoring and observations, modeling, forecasting, dissemination and communication of the forecasts, interpretation of the forecast, and through decision-making, which produces outcomes that have an economic value. The system has been evaluated using metrics developed specifically for this project, which has provided rich information on model and system performance. Research was accomplished on the very short range (0-6 hours) Nowcasting system as well as on the longer term (6-72 hour) forecasting system. The shortest range forecasts are based on observations in the field. The shortest range system, built by Brookhaven National Laboratory (BNL) and based on Total Sky Imagers (TSIs) is TSICast, which operates on the shortest time scale with a latency of only a few minutes and forecasts that currently go out to about 15 min. This project has facilitated research in improving the hardware and software so that the new high definition cameras deployed at multiple nearby locations allow discernment of the clouds at varying levels and advection according to the winds observed at those levels. Improvements over “smart persistence” are about 29% for even these very short forecasts. StatCast is based on pyranometer data measured at the site as well as concurrent meteorological observations and forecasts. StatCast is based on regime-dependent artificial intelligence forecasting techniques and has been shown to improve on “smart persistence” forecasts by 15-50%. A second category of short-range forecasting systems employ satellite imagery and use that information to discern clouds and their motion, allowing them to project the clouds, and the resulting blockage of irradiance, in time. CIRACast (the system produced by the Cooperative Institute for Atmospheric Research [CIRA] at Colorado State University) was already one of the more advanced cloud motion systems, which is the reason that team was brought to this project. During the project timeframe, the CIRA team was able to advance cloud shadowing, parallax removal, and implementation of better advecting winds at different altitudes. CIRACast shows generally a 25-40% improvement over Smart Persistence between sunrise and approximately 1600 UTC (Coordinated Universal Time) . A second satellite-based system, MADCast (Multi-sensor Advective Diffusive foreCast system), assimilates data from multiple satellite imagers and profilers to assimilate a fully three-dimensional picture of the cloud into the dynamic core of WRF. During 2015, MADCast (provided at least 70% improvement over Smart Persistence, with most of that skill being derived during partly cloudy conditions. That allows advection of the clouds via the Weather Research and Forecasting (WRF) model dynamics directly. After WRF-Solar™ showed initial success, it was also deployed in nowcasting mode with coarser runs out to 6 hours made hourly. It provided improvements on the order of 50-60% over Smart Persistence for forecasts up to 1600 UTC. The advantages of WRF-Solar-Nowcasting and MADCast were then blended to develop the new MAD-WRF model that incorporates the most important features of each of those models, both assimilating satellite cloud fields and using WRF-So far physics to develop and dissipate clouds. MAE improvements for MAD-WRF for forecasts from 3-6 hours are improved over WRF-Solar-Now by 20%. While all the Nowcasting system components by themselves provide improvement over Smart Persistence, the largest benefit is derived when they are smartly blended together by the Nowcasting Integrator to produce an integrated forecast. The development of WRF-Solar™ under this project has provided the first numerical weather prediction (NWP) model specifically designed to meet the needs of irradiance forecasting. The first augmentation improved the solar tracking algorithm to account for deviations associated with the eccentricity of the Earth’s orbit and the obliquity of the Earth. Second, WRF-Solar™ added the direct normal irradiance (DNI) and diffuse (DIF) components from the radiation parameterization to the model output. Third, efficient parameterizations were implemented to either interpolate the irradiance in between calls to the expensive radiative transfer parameterization, or to use a fast radiative transfer code that avoids computing three-dimensional heating rates but provides the surface irradiance. Fourth, a new parameterization was developed to improve the representation of absorption and scattering of radiation by aerosols (aerosol direct effect). A fifth advance is that the aerosols now interact with the cloud microphysics, altering the cloud evolution and radiative properties, an effect that has been traditionally only implemented in atmospheric computationally costly chemistry models. A sixth development accounts for the feedbacks that sub-grid scale clouds produce in shortwave irradiance as implemented in a shallow cumulus parameterization Finally, WRF-Solar™ also allows assimilation of infrared irradiances from satellites to determine the three dimensional cloud field, allowing for an improved initialization of the cloud field that increases the performance of short-range forecasts. We find that WRF-Solar™ can improve clear sky irradiance prediction by 15-80% over a standard version of WRF, depending on location and cloud conditions. In a formal comparison to the NAM baseline, WRF-Solar™ showed improvements in the Day-Ahead forecast of 22-42%. The SunCast™ system requires substantial software engineering to blend all of the new model components as well as existing publically available NWP model runs. To do this we use an expert system for the Nowcasting blender and the Dynamic Integrated foreCast (DICast®) system for the NWP models. These two systems are then blended, we use an empirical power conversion method to convert the irradiance predictions to power, then apply an analog ensemble (AnEn) approach to further tune the forecast as well as to estimate its uncertainty. The AnEn module decreased RMSE (root mean squared error) by 17% over the blended SunCast™ power forecasts and provided skill in the probabilistic forecast with a Brier Skill Score of 0.55. In addition, we have also developed a Gridded Atmospheric Forecast System (GRAFS) in parallel, leveraging cost share funds. An economic evaluation based on Production Cost Modeling in the Public Service Company of Colorado showed that the observed 50% improvement in forecast accuracy will save their customers $819,200 with the projected MW deployment for 2024. Using econometrics, NCAR has scaled this savings to a national level and shown that an annual expected savings for this 50% forecast error reduction ranges from $11M in 2015 to $43M expected in 2040 with increased solar deployment. This amounts to a $455M discounted savings over the 26 year period of analysis.

14 SOLAR ENERGY↗
DOE OSTI2021

Connection Between Mass Flux Transport and Eddy Diffusivity in Convective Atmospheric Boundary Layers

Turbulence parameterizations for convective boundary layer in coarse-scale atmospheric models usually consider a combination of the eddy-diffusive transport and a non-local transport, typically in the form of a mass flux term, such as the widely adopted eddy-diffusivity mass-flux (EDMF) approach. These two types of turbulent transport are generally considered to be independent of each other. Using results from large-eddy simulations, here, we show that a Taylor series expansion of the updraft and downdraft mass-flux transport can be used to approximate the eddy-diffusivity transport in the atmospheric surface layer and the lower part of the mixed layer, connecting both eddy-diffusivity and mass-flux transport theories in convective conditions, which also quantifies departure from the Monin-Obukhov similarity (MOS) in the surface layer. This study provides a theoretical support for a unified EDMF parameterization applied to both the surface layer and mixed layer and highlights important correction required for surface models relying on MOS

54 ENVIRONMENTAL SCIENCES↗