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Results for “Coupled Simulation”
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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Mathematical modeling of novel porous transport layer architectures for proton exchange membrane electrolysis cells
Thin foil based porous transport layers (PTLs) that contain highly structured pore arrays have shown promise as anode PTLs in proton exchange membrane electrolysis cells. These novel PTLs, fabricated with advanced manufacturing techniques, produce thin, tunable, multifunctional layers with reduced flow and interfacial resistances and high thermal and electric conductivities. To further optimize their design, it is important to understand their fundamental impact on the transport of protons, electrons, and liquid/vapor mixtures in the electrode. In this work, we develop a two-dimensional multiphysics model to simulate the coupled electrochemistry and multiphase transport in an electrolysis cell operated with the novel PTL architecture. The results show that larger pores improve access of water to the anode catalyst layer, which is beneficial for both the oxygen evolution reaction and membrane hydration. Larger pore sizes also improve oxygen gas transport from the catalyst layer, because generated oxygen gas is forced to travel in-plane through the anode catalyst layer until it reaches a pore opening that is connected to a channel. The discussed results confirm that the proposed thin foil based PTLs are fundamentally different from conventional PTLs, such as felts or layered meshes. The model developed in this work also provides generalizable insight into fundamental PEMEC phenomena, such as the competition between liquid and gas phase transport, membrane hydration and water management, and nonuniform electrochemical reactions, which are processes relevant to all PEMEC designs.
Analysis of soot formation from aviation fuels in laminar counterflow flames
Combustion emissions from aviation contribute to the formation of condensation trail (contrail) that can lead to the formation of anthropogenic cirrus clouds. Ice particles that form contrails are observed to have a linear correlation with soot particle number density. Synthetic aviation fuels (SAFs) offer a promising route to mitigate the production of soot particles while also increasing energy security. Although studies have focused on combustion and spray behavior, the detailed investigation of soot formation processes for different jet fuels and their impact on models for computational fluid dynamics (CFD) applications is not well understood. Moreover, experimental measurements of soot for canonical flames using Synthetic aviation fuels (SAF) for model validation remain scarce. To address this, we use employed the Lawrence Livermore National Laboratory (LLNL) detailed soot model based on the discrete sectional method. Additionally, we develop two reduced chemical mechanisms for Jet-A and Alcohol-to-Jet (C1) that are suitable for turbulent flame simulations and couple them with the Hybrid Method of Moments (HMOM). The detailed and reduced model frameworks are validated against experimental measurements of soot volume fraction (ƒ ν ) from a counterflow burner experiment previously reported in the literature. Given the good agreement between modeling results and experimental measurements for the (1) spatial distribution of ƒ ν and (2) the non-linear variation of peak ƒ ν with strain rate, we further investigate the modeled sub-processes (nucleation, condensation, surface growth, and oxidation) using the LLNL model to analyze the assumptions in the reduced model framework. Furthermore, the results indicate a significant contribution from resonant radicals to the surface growth of soot particles, which are not accounted for in the current implementation of HMOM and could help reconcile soot predictions by the reduced model with observations.
Concentration-Dependent Solvation Structure and Dynamics of Aqueous Sulfuric Acid Using Multinuclear NMR and DFT
Sulfuric acid is a ubiquitous compound for industrial processes and aqueous sulfate solutions also play a critical role in electrolytes for many prominent battery chemistries. While the thermodynamic literature for it is quite well-developed, comprehensive studies of the solvation structure, and particularly molecular-scale dynamical and transport properties, are less available. This study applies a multinuclear NMR approach to the elucidation of the solvation structure and dynamics over a wide temperature (-10 – 50?C) and concentration (0 – 18 M) range, combining 17O shift, linewidth, and T1 relaxation measurements, 33S shift and linewidth measurements, and 1H PFG-NMR measurements of the proton self-diffusivity. In conjunction, these results indicate a crossover between two regimes of solvation structure and dynamics, occurring above the concentration associated with the deep eutectic point (~ 4.5 M), with the high-concentration regime dominated by strong water-sulfate correlation. This description was borne out in detail by the activation energy trends with increasing concentration derived from the relaxation of both the H2O/H3O+ and H2SO4/HSO4-/SO42- 17O resonances and the 1H self-diffusivity. However, the 17O chemical shift difference between the H2O/H3O+ and H2SO4/HSO4-/SO42- resonances across the entire temperature range is nevertheless strikingly linear. A computational approach coupling MD simulations and DFT NMR shift calculations to reproduce this trend is presented, which will be the subject of further development. This combination of multinuclear, dynamical NMR and computational methods, and the results furnished by this study, will provide a platform for future studies on battery electrolytes where aqueous sulfate chemistry plays a central role in the solution structure.
Selecting Adsorbents to Separate Diverse Near-Azeotropic Chemicals
Industrial separations of near-azeotropic chemicals, species with very similar boiling points, are energy- and capital-intensive. Adsorption-based processes can energy-efficiently separate near-azeotropic mixtures provided suitable adsorbent materials can be found. Among the full diversity of industry-relevant molecules, millions of these mixtures exist, meaning that discovery of mixture-specific adsorbents by direct experiment is infeasible. We show that vast numbers of adsorbents and adsorbing molecules can be explored in a powerful way by coupling atomistic simulations with machine learning. This concept is demonstrated by describing the adsorption of ~54000 industry-relevant chemicals in an experimentally derived set of thousands of metal–organic framework materials. Here, our results identify thousands of near-azeotropic mixtures that can be efficiently separated using adsorption and open possibilities for creating adsorption processes for complex mixtures with many components.
The Sensitivity of Hyporheic Exchange to Fractal Properties of Riverbeds
Hyporheic exchange in riverbeds is driven by current-bed topography interactions. Because riverbeds exhibit topographic roughness across scales, from individual grains to bedforms and bars, they can exhibit fractal patterns. This study analyzed the influence of fractal properties of riverbed topography on hyporheic exchange. A set of synthetic fractal riverbeds with different scaling statistics was used as inputs to sequentially coupled numerical simulations of turbulent channel flow and hyporheic flow. In the analysis, the maximum power spectrum (dune size) and the fractal dimension (topographic complexity) were considered as independent variables and we then investigated how interfacial fluxes and hyporheic travel times are functionally related to these variables. As the maximum power spectrum increases (i.e., dune height to flow depth ratio), the average interfacial flux increases logarithmically whereas it increases exponentially with an increase in fractal dimension. Hyporheic exchange is more sensitive to additional roughness (larger fractal dimensions) than to bedform size (larger maximum power). Our results imply that fractal properties of riverbeds are crucial to predicting hyporheic exchange. The predictive relationships we propose could be integrated with reduced complexity, large-scale models. Further, they can also be used to design artificial topographies that target hyporheic ecosystem services.
Hyporheic Exchange in Sand Dunes Under a Freely Deforming River Water Surface
Bedform-driven hyporheic exchange is conditioned by the head gradients at the sediment-water interface. Local exchange phenomena between the surface and the subsurface are often driven by the dynamic forces related to the velocity distributions around sediment waves. In open channels, the static forces are represented by the water depth, yet most computational fluid dynamics models use a rigid-lid approximation. Here, we investigated whether and when the deformation of the river’s free-surface influences bedform-driven hyporheic exchange. This was done through simulations of coupled open channel and hyporheic flows with the air-water interface modeled either as a free-surface or a rigid-lid across increasing subcritical Froude numbers from ~0.05 to ~0.95. The normalized hyporheic flux was higher when considering free-surface deformation across most of the range of Froude numbers considered. When the Froude number was larger than 0.6 and smaller than 0.85, both hydrostatic and nonhydrostatic-driven fluxes increased significantly compared to the rigid-lid approach and the total flux was about five times that predicted with the rigid-lid. These results indicate that bedform-driven hyporheic fluxes are underestimated in most studies that use a rigid-lid assumption in subcritical flows.
Local and Global Sensitivity Analysis of a Reactive Transport Model Simulating Floodplain Redox Cycling
Reactive transport models (RTMs) are essential tools that simulate the coupling of advective, diffusive, and reactive processes in the subsurface, but their complexity makes them difficult to understand, develop and improve without accompanying statistical analyses. Although global sensitivity analysis (SA) can address these issues, the computational cost associated with most global SA techniques limits their use with RTMs. In this study, we apply distance-based generalized sensitivity analysis (DGSA), a novel and computationally efficient method of global SA, to a floodplain-scale RTM and compare DGSA results to those from local SA. Our test case focuses on the impact of 17 uncertain environmental parameters on spatially and temporally variable redox conditions within a floodplain aquifer. The input parameters considered include flow and diffusion rates, geochemical reaction rates, and the spatial distribution of sediment facies. Sensitivity was evaluated for three distinct components of the model response, encompassing both multidimensional and categorical output. Parameter rankings differ between local SA and DGSA, due to nonlinear effects of individual parameters and interaction effects between parameters. DGSA results show that fluid residence time, which is controlled by aquifer permeability, generally exerts a stronger control on redox conditions than do geochemical reaction rates. Sensitivity indices also demonstrate that sulfate reduction is key for establishing and maintaining reducing conditions throughout the aquifer. Furthermore, these results provide insights into the key drivers of heterogeneous redox processes within floodplain aquifers, as well as the main sources of uncertainty when modeling complex subsurface systems.
Use of Shallow Ice Core Measurements to Evaluate and Constrain 1980–1990 Global Reanalyses of Ice Sheet Precipitation Rates
Abstract Sea‐level rise (SLR) projections by Earth System Models (ESMs) depend on ice sheet surface mass balances. Accurate, global atmosphere reanalyses would be ideal for providing equilibrated ice sheet model initial conditions in fully coupled ESM simulations. Here we present the first evaluation of 1980–1990 global reanalysis precipitation over Greenland and Antarctica that uses independent observations of net accumulation rates derived from shallow ice cores. Precipitation distributions from both the European Centre for Medium‐Range Weather Forecast's Reanalysis (ERA5) and the Modern‐Era Retrospective Analysis for Research and Applications (MERRA‐2) are highly correlated with contemporaneous co‐located net accumulation rates from Greenland ( r 2 > 0.95) and West Antarctica ( r 2 > 0.7). Three other commonly used reanalyses (WFDE5, CRUNCEP, and GSWP3) exhibit significantly weaker correlations on one or both ice sheets. Our findings imply that ESMs should use ERA5 or MERRA‐2 in data‐forced simulations to validate ice sheet model dynamics and precondition firn for SLR projections.
Sensitivity of Arctic Surface Temperature to Including a Comprehensive Ocean Interior Reflectance to the Ocean Surface Albedo Within the Fully Coupled CESM2
Abstract Almost all current climate models simplify the ocean surface albedo (OSA) by assuming the reflected solar energy without the ocean interior contribution. In this study, an improved ocean surface albedo scheme is incorporated into the Community Earth System Model version 2 (CESM2) to assess the sensitivity of Arctic surface temperature to including ocean interior reflectance to the OSA. Fully coupled CESM2 simulations with and without ocean interior reflectance are subsequently performed, we focus on the analysis of Arctic surface temperature responses. Incorporating ocean interior reflectance increases absorbed solar radiation and warms the ocean, enhancing seasonal heat storage and release across the Arctic Ocean, and increasing sea ice reduction and positive climate feedbacks that elevates Arctic surface temperature. Seasonal variations in air‐surface temperature differences induce changes in turbulent heat flux patterns, concurrently modifying dynamic advection and moisture processes that affect boundary layer humidity and low clouds, especially in winter. Based on partitioning physical processes in the thermodynamic energy equation, surface air warming is induced primarily through positive heating anomalies of vertical advection, latent heat release, and longwave radiative forcing. Through an examination of the surface energy budget, skin temperature warming is driven predominantly by increased downward longwave radiation, positive surface albedo feedback in summer, and increased conductive heat transport from the ocean particularly in winter. Significant effects of ocean interior reflectance on the Arctic Ocean, including sea surface warming and sea ice reduction, justify the importance of ocean interior reflectance in climate models for better understanding of ongoing Arctic climate changes.
Proton radiation resilience of CdSeTe photovoltaics: High predicted end-of-life performance for space applications
Two types of cadmium selenide telluride (CdSeTe) photovoltaic devices have been exposed to high-energy (150–1500 keV) protons with fluences ranging from 1 × 10 11 to 9 × 10 13 cm −2 . Pre- and post-irradiation current density vs voltage characteristic data were collected and analyzed. Arsenic-doped CdSeTe devices retained 80% of the power conversion efficiency (PCE) relative to control devices after exposure to 10 12 cm −2 650 keV protons, while copper-doped CdSeTe devices retained about 95% of the control PCE under the same irradiation condition. Displacement damage dose analysis coupled with simulations for duration-dependent performance in a medium Earth orbit space mission revealed superior PCE remaining factors, indicating greater resilience to proton bombardment than state-of-the-art multijunction III-V based space photovoltaic technologies.
Model Development for Thermal-Hydrology Simulations of a Full-Scale Heater Experiment in Opalinus Clay
Disposal of commercial spent nuclear fuel in a geologic repository is studied. In situ heater experiments in underground research laboratories provide a realistic representation of subsurface behavior under disposal conditions. Here, this study describes process model development and modeling analysis for a full-scale heater experiment in opalinus clay host rock. The results of thermal-hydrology simulation, solving coupled nonisothermal multiphase flow, and comparison with experimental data are presented. The modeling results closely match the experimental data.
Tungsten–carbon surface evolution and erosion modeling for a small angle slot divertor in DIII-D
Abstract We modeled tungsten–carbon mixed surface evolution, sputtering erosion, and transport for the tungsten coated region of a small angle slot (SAS) divertor design for the DIII-D tokamak. This divertor concept aims to achieve a closed slot dissipative plasma to minimize heat load and surface erosion, and to study high- Z material performance. Our advanced simulations use coupled ITMC-DYN material mixing/response and 3D full kinetic REDEP/WBC erosion/redeposition code packages, with divertor plasma solution from the SOLPS-ITER package with 4 MW power input. The SAS design geometry and resulting in-slot plasma parameters cause significant differences in predicted sputter/transport from a conventional divertor. For 2% C/D incident plasma ratio, an equilibrium mixed C/W surface is attained at ∼30 s of discharge, from wall sputtered carbon transported to the 10 cm long tungsten divertor region. Tungsten remains exposed to the plasma, but the evolved surface composition varies with different C/D ratios. Tungsten is primarily sputtered from the mixed surface by impinging carbon ions in the +1 to +4 charge states, with some self-sputtering. Redeposition of sputtered tungsten to the divertor is significant, ∼80% along the higher plasma temperature attached plasma SAS entrance region, but this is less than the typically near-unity values for a conventional divertor. Plasma-incident carbon is highly backscattered (∼50%) from the mixed surface, with little redeposition (<10%); this helps maintain tungsten in the surface sputter zone. Carbon is mainly sputtered from the mixed surface by D + ions, also with low redeposition (∼10%–30%). Finally, the modeling shows non-zero but low sputtered tungsten current from the divertor to the core plasma direction. These results appear favorable for effective testing of a tungsten-containing SAS divertor in DIII-D, and extrapolation of mixed-material evolution/response findings to the analogous low- Z /high- Z , Be/W, ITER plasma facing system.
Capturing electronic decoherence in quantum-classical dynamics using the ring-polymer-surface-hopping–density-matrix approach
Simulations of coupled electronic and nuclear dynamics in molecules can be quite challenging due to the involved interplay of the many degrees of freedom. Because a full quantum treatment of both electrons and nuclei is computationally very demanding, it is generally restricted to model systems or rather small molecules and short timescales. Mixed quantum-classical dynamics methods such as Tully's fewest switches surface hopping (FSSH) can be used to overcome this limitation. However, FSSH is known to poorly describe electronic coherences and decoherence phenomena. Here, we present an approach that combines FSSH with ring-polymer molecular dynamics (RPMD) in a specific way that aims to alleviate the coherence problem. Termed the ring-polymer-surface-hopping–density-matrix approach, this method uses an electronic density-matrix formulation to calculate surface hopping rates. Additionally, this incorporates decoherence effects into FSSH in a natural way by taking into account the spatial spreading of the ring polymer that mimics the width of a nuclear wave packet in each RPMD trajectory. By applying our method to Tully's one-dimensional model system, we demonstrate that this method captures a crucial decoherence mechanism that is missing in FSSH. Furthermore, our method turns out to be superior at describing electronic coherences compared with earlier attempts at combining RPMD and FSSH.
Energy Gap Closure of Crystalline Molecular Hydrogen with Pressure
Here, we study the gap closure with pressure of crystalline molecular hydrogen. The gaps are obtained from grand-canonical quantum Monte Carlo methods properly extended to quantum and thermal crystals, simulated by coupled electron ion Monte Carlo methods. Nuclear zero point effects cause a large reduction in the gap (~2 eV). Depending on the structure, the fundamental indirect gap closes between 380 and 530 GPa for ideal crystals and 330–380 GPa for quantum crystals. Beyond this pressure the system enters into a bad metal phase where the density of states at the Fermi level increases with pressure up to ~450–500 GPa when the direct gap closes. Our work partially supports the interpretation of recent experiments in high pressure hydrogen.
A Novel Grid-forming Voltage Control Strategy for Supplying Unbalanced Microgrid Loads Using Inverter-based Resources
This paper presents a novel grid-forming voltage control strategy for a battery energy storage system to maintain balanced three-phase output voltages when serving unbalanced loads. A stationary reference frame (αβ) based control scheme is proposed to regulate positive-sequence and negative-sequence voltages. Compared with the conventional rotating reference frame (dq) based control scheme, the proposed scheme shows better dynamic performance. Then, we analyze the system zero-sequence network and propose adding a grounding transformer to the Y/Yg connected output transformer to further reduce the voltage unbalance at the point of common coupling. The simulation results demonstrate the effective performance of the proposed voltage control scheme. Based on the results, the power-voltage unbalance curve is derived for different output transformer configurations to establish the relationship between the power unbalance limit and the voltage unbalance limit for microgrid power scheduling.
Switching Dynamics in Vanadium Dioxide-Based Stochastic Thermal Neurons
We report on switching dynamics of individual and coupled vanadium dioxide (VO 2 ) devices subject to voltage pulses as the temperature is systematically varied from room temperature spanning the insulator–metal transition (IMT) temperature. The switching voltage of single devices has a strong relationship with both temperature and voltage pulsewidth. Two-step switching in connected VO 2 devices has been noted in current transient plots and was found to depend on temperature, pulsewidth, and pulse amplitude. Experimental switching behavior measured from VO 2 artificial neurons was implemented into a spiking neural network (SNN). During training, modulating the switching voltage via temperature affords a novel method to implement homeostasis with the coupled devices. Simulation results show the efficacy of the stochastic neuronal characteristics and the proposed homeostasis mechanism on a standard digit recognition task. As a result, these studies contribute to ongoing efforts in neuromorphic computing exploiting collective phase transitions.
Bridging Scales to Model Reactive Diffusive Transport in Porous Media
Published by ECS. Two novel scale-bridging algorithms to model reaction-diffusion transport in porous media are presented. The algorithms are based on direct numerical simulations and couple the information of a micro-scale model, which accounts for the large field of view provided by micro X-ray computed tomography (X-ray CT), and a nano-scale model, which locally resolves transport in the fine structure extracted from nano X-ray CT. The micro-scale model is discretized in the through-plane direction into a 1D grid, where effective properties and internal boundaries are determined based on the results from the nano-scale model. The validated algorithms are used to examine transport of oxygen in precious group metal-free electrodes considering both zero- and first-order kinetics. Unlike conventional methods, the results show that the effective diffusivity is not a passive property but increases in regions where the reaction-rate coefficient is large. The proposed algorithms account for the multiscale coupling of reaction-diffusion transport and material microstructure, thus improving the predictions compared to conventional methods.