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At least 865 records · Page 48

Simplified Models of the Bicarbonate Buffer for Scaled Simulations of CO 2 Electrolyzers

Bicarbonate electrolytes are used in a range of chemical processes; however, resolved simulation of these electrolytes is difficult, as disparate reaction time scales lead to numerical stiffness and the formation of fine boundary layers. Based on several physically motivated approximations, we reduce the full set of chemical reactions within a bicarbonate electrolyte to a simpler subset, eliminating the numerical stiffness. We supported this simplification via a two-variable singular perturbation expansion and demonstrated that under neutral conditions (6 < pH < 10) typically found within a fluid-fed CO 2 electrolyzer, the simplifications lead to negligible error. Here, we also discuss two alternative simplifications, one valid at high pH and another valid at arbitrary pH. These simplifications reduce the condition number of the matrices resulting from spatiotemporal discretization by up to 10 orders of magnitude and enable three-dimensional (3D) simulation of CO 2 electrolyzers containing carbonate solutions.

10 SYNTHETIC FUELS↗

Experimentally validated high-fidelity simulations of a liquid jet in supersonic crossflow

Here, utilizing recent advancements in computational schemes for compressible, multiphase flows, this work features a parametric study of a pure liquid jet in supersonic crossflow that involves simulating the atomization process for four values of momentum-flux ratio. These simulations are validated against experimental results measured with high-speed X-ray imaging, which confirm the accuracy of the numerical approach. Also, the effect of numerical resolution on some flow behavior is investigated, revealing convergence of the jet shape and surface instability wavelength. Analysis of the resulting sprays includes statistical descriptions of the liquid distribution, liquid structures created through breakup, interfacial instabilities, and dominant flow features. As the flowrate increases, the spray penetrates further, it becomes more disperse, and less liquid impacts the wall, but the droplet size distribution changes little. The wavelength of instabilities on the windward side of the jet diverges from measured trends in subsonic crossflows. In a visualization of the time-averaged flow, counter-rotating vortices are observed along the jet core and in the wake, affecting the process of primary atomization and early droplet trajectories.

42 ENGINEERING↗

COUPLING SMOOTHED PARTICLE HYDRODYNAMICS WITH FINITE ELEMENT METHOD TO SIMULATE RESIDUAL STRESSES FROM FRICTION STIR PROCESSING

Friction stir processing (FSP) is a solid-state material processing technique that locally modifies the microstructure but also induces undesirable residual stresses. A robust numerical model for the FSP can help in mitigating these residual stresses. Heat source models within a finite element method (FEM) framework suffer from inaccuracies. In contrast, smoothed particle hydrodynamics (SPH) model that explicitly captures the material flow near the tool and the associated heat generation are accurate. However, the computational expense of SPH simulations can be prohibitive. In this work, we propose a coupled SPH-FEM framework. SPH is used to model the heat generation accurately near the tool and which is then inserted into to the FEM model as a heat source. To verify this proposed coupling approach, a test case is set up with typical FSP conditions and it is modeled in both SPH and SPH-FEM. The temperatures profiles were compared after the simulations have reached steady-state temperatures. The similarity of the temperature profiles from SPH-FEA and SPH validated the proposed coupling approach. This proposed approach achieves the accuracy of the SPH method while potentially retaining the low computational expense of FEM.

smoothed particle hydrodynamics, Finite Element Me↗

Effective direct steam regeneration of bis-iminoguanidine solid sorbent used for carbon dioxide capture

A cost-effective, energy-efficient sorbent regeneration process for phase-changing guanidines used for CO 2 capture was developed based on direct-steam stripping. This approach enhances the regeneration rate, simplifies the overall CO 2 capture process, and reduces the energy cost compared to conventional conductive thermal regeneration. A direct-steam sorbent regeneration reactor was developed, demonstrating that aqueous bis(iminoguanidines) (BIG) sorbents, e.g., methylglyoxal-bis(iminoguanidine) (MGBIG) and glyoxal-bis(iminoguanidine) (GBIG), could be efficiently regenerated with up to ~ 99 % CO 2 recovery through direct-steam stripping. Using low-temperature steam at 100 °C, a 4.5 times faster regeneration rate for GBIG carbonate sorbent (e.g., 30 min for 10 g) was demonstrated compared to conductive-heating (e.g., 135 min for 10 g) at 130 °C. Additionally, fully regenerated MGBIG converts into an aqueous MGBIG solution when the steam condenses onto the sorbent surface. Condensed steam with the guanidine can be easily recycled as an aqueous solution into the gas–liquid contactor to achieve a continuous-flow CO 2 -capture process. Molecular dynamics simulation was employed to provide a better understanding of the process. Higher heat transfer rates from steam to guanidine carbonate, compared to air heating, were attributed to the vibration resonance of water molecules within MGBIG with that of vapor molecules and the effective transfer of kinetic energy from vapor to solid. Technoeconomic analysis demonstrated that direct-steam stripping significantly decreases the CO 2 capture cost by 50 % compared to traditional conductive heating methods. Further, enhanced mass transfer facilitated by low-temperature steam and subsequent condensation effectively heats up the H 2 O-containing BIG-carbonate crystals, facilitating the desorption of CO 2 from the solid crystals, thereby leading to fast, effective, and energy-efficient sorbent regeneration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The LSST DESC data challenge 1: generation and analysis of synthetic images for next-generation surveys

Data Challenge 1 (DC1) is the first synthetic data set produced by the Rubin Observatory Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC). DC1 is designed to develop and validate data reduction and analysis and to study the impact of systematic effects that will affect the LSST data set. DC1 is comprised of r -band observations of 40 deg 2 to 10 yr LSST depth. In this paper, we present each stage of the simulation and analysis process: (a) generation, by synthesizing sources from cosmological N -body simulations in individual sensor-visit images with different observing conditions; (b) reduction using a development version of the LSST Science Pipelines; and (c) matching to the input cosmological catalogue for validation and testing. We verify that testable LSST requirements pass within the fidelity of DC1. We establish a selection procedure that produces a sufficiently clean extragalactic sample for clustering analyses and we discuss residual sample contamination, including contributions from inefficiency in star–galaxy separation and imperfect deblending. We compute the galaxy power spectrum on the simulated field and conclude that: (i) survey properties have an impact of 50 per cent of the statistical uncertainty for the scales and models used in DC1; (ii) a selection to eliminate artefacts in the catalogues is necessary to avoid biases in the measured clustering; and (iii) the presence of bright objects has a significant impact (2σ–6σ) in the estimated power spectra at small scales (ℓ > 1200), highlighting the impact of blending in studies at small angular scales in LSST.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A review of transport models in charged porous electrodes

There is increased interest in many different processes based upon interactions between a charged solid surface and a liquid electrolyte. Energy storage in capacitive porous materials, ionic membranes, capacitive deionization (CDI) for water desalination, capacitive energy generation, removal of heavy ions from wastewater streams, and geophysical applications are some examples of these processes. Process development is driven by the production of porous materials with increasing surface area. Understanding of the physical phenomena occurring at the charged solid-electrolyte interface will significantly improve the design and development of more effective applied processes. The goal of this work is to critically review the current knowledge in the field. The focus is on concepts behind different models. We start by briefly presenting the classical electrical double layer (EDL) models in flat surfaces. Then, we discuss models for porous materials containing macro-, meso-, and micro-pores. Some of the current models for systems comprising two different pore sizes are also included. Finally, we discuss the concepts behind the most common models used for ionic transport and Faradaic processes in porous media. The latter models are used for simulation of electrosorption processes in porous media.

42 ENGINEERING↗

An Interactive Visualization Tool for Large-Scale Building Stock Modeling

Recent advancements in data science and high-performance computing are making it easier to run millions of building simulations, but meaningful visualization of such large datasets remains a challenge. This paper presents a new tool developed to view the results of large-scale OpenStudio simulations of national, regional, or local building stocks. The tool processes millions of simulations to calculate measure savings, utility bills, carbon emissions, primary energy, and cost-effectiveness metrics at a high geographic resolution. Interactive visualizations of the building characteristics, consumption, and measure savings data include proportional symbol maps and histogram plots and can be filtered by any building characteristic.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

An Interactive Visualization Tool for Large-Scale Building Stock Modeling: Preprint

Recent advancements in data science and high-performance computing are making it easier to run millions of building simulations, but meaningful visualization of such large datasets remains a challenge. This paper presents a new tool developed to view the results of large-scale OpenStudio simulations of national, regional, or local building stocks. The tool processes millions of simulations to calculate measure savings, utility bills, carbon emissions, primary energy, and cost-effectiveness metrics at a high geographic resolution. Interactive visualizations of the building characteristics, consumption, and measure savings data include proportional symbol maps and histogram plots and can be filtered by any building characteristic.

big data↗

Unraveling Hydrogen Induced Geochemical Reaction Mechanisms through Coupled Geochemical Modeling and Machine Learning

Underground hydrogen storage (UHS) provides a promising large-scale, long-term energy storage solution. A reasonable recovery of stored hydrogen is critical for a successful storage scheme. However, in subsurface reservoirs hydrogen is subject to active geochemical reactions that might result in hydrogen loss. In this study, we implemented a geochemical modeling approach coupled with an unsupervised machine learning technique called non-negative matrix factorization (NMF) to unravel the complex brine-rock-H 2 geochemical processes responsible for hydrogen losses, with particular focus on sulfate reduction reactions. NMF is applied to modeled mineral evolution and fluid component profiles to retrieve profiles that can be interpreted to more easily assess competing processes. NMF decouples simulated competing equilibrium reactions. This facilitates separation of overlapping reaction profiles from redox processes, dissolution fronts, and secondary precipitation while considering the effects of simulation parameters such as salinity, temperature, and total H 2 pressure. NMF successfully discriminates these competing effects in nonlinear ways, allowing robust interpretation. In addition, NMF reveals subtle coupled mineral associations and reaction fronts that are invisible to conventional model analysis. This integrated approach strengthens the conceptual understanding of complex nonlinear hydrogen-brine-rock interactions and advances geochemical research on UHS systems to resolve complexities in modeled geochemical systems without the need for direct experiments or prior knowledge. Furthermore, this study highlights the efficacy of combining geochemical modeling with machine learning techniques to enhance the interpretability of the intricate geochemical simulation output through deciphering the overlapping reaction path that cannot be achieved only using conventional analysis of geochemical models alone.

08 HYDROGEN↗

An assessment of coupling algorithms for nuclear reactor core physics simulations

This paper evaluates the performance of multiphysics coupling algorithms applied to a light water nuclear reactor core simulation. The simulation couples the k-eigenvalue form of the neutron transport equation with heat conduction and subchannel flow equations. We compare Picard iteration (block Gauss–Seidel) to Anderson acceleration and multiple variants of preconditioned Jacobian-free Newton–Krylov (JFNK). The performance of the methods are evaluated over a range of energy group structures and core power levels. A novel physics-based approximation to a Jacobian-vector product has been developed to mitigate the impact of expensive on-line cross section processing steps. Numerical simulations demonstrating the efficiency of JFNK and Anderson acceleration relative to standard Picard iteration are performed on a 3D model of a nuclear fuel assembly. Both criticality (k-eigenvalue) and critical boron search problems are considered.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Vitrification of Hanford Tank 241-AP-101 Waste and Simulant

Hanford tank 241-AP-101 (referred to herein as AP-101) is the second Hanford radioactive tank waste planned to be processed and vitrified. A simulant version of AP 101 waste was formulated from the best-basis inventory (BBI) for the Hanford Tank 241-AP-101 liquid with an assumed target dilution of the waste from the BBI sodium molarity of 8.61 M to the desired 5.5 M Na. After the addition of glass-forming chemicals (GFCs), the simulant melter feed was processed in a non-radioactive, continuous laboratory-scale melter (CLSM) system. The AP-101 simulant melter feed was charged into the CLSM for 6.11 h of processing, which produced 6.55 kg of glass, for an average glass production rate of 2275 kg m 2 d -1 . Since there were no processing issues with the AP-101 simulant melter feed, AP-101 melter feed made with actual waste was then processed in a CLSM system built into a contamination area in a radioactive environment. The melting behavior characteristics appeared similar for both the simulant and waste melter feeds. The AP-101 waste melter feed was charged into the CLSM for 12.14 h of processing, which produced 8.75 kg of glass, for an average glass production rate of 1530 kg m 2 d -1 . During the AP-101 waste melter feed charging, the pump used to move the feed reached a maximum and it is believed that if the pump had a greater capacity, a greater average glass production rate could have been achieved. A constituent of interest present in low quantities in the AP-101 waste is 99 Tc or its non-radioactive surrogate, Re, added to the AP-101 simulant. Analysis for the quantities of 99 Tc and Re in the AP-101 glass product resulted in an average single-pass retention from the melter feed during relative chemical steady state of 55 ± 2 % for 99 Tc and 45 ± 2 % for Re. Compared to the processing of other melter feeds, the retention of 99 Tc in the AP-101 glass was greater than in both AP-107 and AP-105 glass, while the retention of Re in the AP-101 was less than in the AP-107 glass, but greater than in the AP-105 glass. A spike of I was added into the AP-101 melter feed that could be detected above the analysis detection limits. However, the iodine was only detectable above the ~6 ppm limit in one glass pour: the pour immediately following the burn off of the cold cap, where the I level reached ~30 ppm. This event was significant because the glass was poured immediately after burn off and thus it is presumed that the iodine had yet to volatilize from the glass melt while idling. It is recommended to perform future tests with I spikes at greater levels so that it can be detected in additional glass pours to determine if the expected 50 % retention of I used in the Kim et al. glass models can be confirmed. Offgas liquid samples were analyzed for acetonitrile, which was present at greater concentrations in CLSM liquids than in other scaled melter systems. This result was expected based on unique conditions with the CLSM system including a small plenum space leading to low residence time for offgas and the rapidity of offgas cooling upon exiting the CLSM vessel due to the location and environment. About 90 % of the total acetonitrile captured during both the AP-101 simulant and waste CLSM runs was found in the offgas condensate and demister liquids, thus it is recommended that only those liquids be sent for analysis if future testing to study the presence of acetonitrile in offgas products is desired.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Tutorial: The equations of electron emission and their evaluation

Electron emission and transport through and over potential barriers is an essential process requiring modeling and simulation to meet the design needs and characterization of an exceedingly broad range of technologically important devices and processes. The simulation and description of thermal, field, and photoemission, and the related concerns of space–charge affected electron flow, often make use of specialized formulations developed in the early days of quantum mechanics. Advancements in the utilization of electron sources and particularly the simulation of devices and applications using advanced particle-in-cell and trajectory methods for beam optics codes create a strong need for a pedagogical account of the emission models to ensure correct numerical evaluation of their equations. This Tutorial starts from simple phenomenological accounts and progressively builds to comprehensive models emphasizing straightforward and often rapid calculation. It recommends formulations to supplant the canonical Richardson–Laue–Dushman (thermal), Fowler–Nordheim (field), Fowler–DuBridge (photo), and Baroody (secondary) equations and provides a useful formulation of space–charge affected flow commonly described by the Child–Langmuir relation that takes into account cathode dependence on surface field.

Physics↗

ATDM/ECP Milestone Memo WBS 2.3.4.04 / SNL ATDM Data and Visualization Projects STDV04-21 - [MS1/YR2] Q3: Prototype Catalyst/ParaView in-situ viz for unsteady RV flow on ATS-1

ParaView Catalyst is an API for accessing the scalable visualization infrastructure of ParaView in an in-situ context. In-situ visualization allows simulation codes to access data post-processing operations while the simulation is running. In-situ techniques can reduce data post-processing time, allow computational steering, and increase the resolution and frequency of data output. For a simulation code to use ParaView Catalyst, adapter code needs to be created that interfaces the simulations data structures to ParaView/VTK data structures. Under ATDM, Catalyst is to be integrated with SPARC, a code used for simulation of unsteady reentry vehicle flow.

97 MATHEMATICS AND COMPUTING↗

Comparing emulation methods for a high‐resolution storm surge model

Abstract Realistic simulations of complex systems are fundamental for climate and environmental studies. Large computer systems are often not sufficient to run sophisticated computational models for large numbers of different input settings. Statistical surrogate models, or emulators, are key tools enabling fast exploration of the simulator input space. Gaussian processes have become standard for computer simulator emulation. However, they require careful implementation to scale appropriately, motivating alternative methods more recently introduced. We present a comparison study of surrogates of the Sea, Lake, and Overland Surges from Hurricanes (SLOSH) simulator—the simulator of choice for government agencies—using four emulation approaches: BASS; BART; SEPIA; and RobustGaSP. SEPIA and RobustGaSP use Gaussian processes, BASS implements adaptive splines, and BART is based on ensembles of regression trees. We describe the four models and compare them in terms of computation time and predictive metrics. These surrogates use proven and distinct methodologies, are available through accessible software, and quantify prediction uncertainty. Our data cover millions of response values. We find that SEPIA and RobustGaSP provide exceptional predictive power, but cannot scale to emulate experiments as large as the one considered in this paper as effectively as BASS and BART.

Hutchings, Grant↗

Reinforcement Learning-Guided Long-Timescale Simulation of Hydrogen Transport in Metals

Diffusion in alloys is an important class of atomic processes. However, atomistic simulations of diffusion in chemically complex solids are confronted with the timescale problem: the accessible simulation time is usually far shorter than that of experimental interest. In this work, long-timescale simulation methods are developed using reinforcement learning (RL) that extends simulation capability to match the duration of experimental interest. Two special limits, RL transition kinetics simulator (TKS) and RL low-energy states sampler (LSS), are implemented and explained in detail, while the meaning of general RL are also discussed. As a testbed, hydrogen diffusivity is computed using RL TKS in pure metals and a medium entropy alloy, CrCoNi, and compared with experiments. The algorithm can produce counter-intuitive hydrogen-vacancy cooperative motion. We also demonstrate that RL LSS can accelerate the sampling of low-energy configurations compared to the Metropolis–Hastings algorithm, using hydrogen migration to copper (111) surface as an example.

36 MATERIALS SCIENCE↗

Recommended direct simulation Monte Carlo collision model parameters for modeling ionized air transport processes

A systematic approach for calibrating the direct simulation Monte Carlo (DSMC) collision model parameters to achieve consistency in the transport processes is presented. The DSMC collision cross section model parameters are calibrated for high temperature atmospheric conditions by matching the collision integrals from DSMC against ab initio based collision integrals that are currently employed in the Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA) and Data Parallel Line Relaxation (DPLR) high temperature computational fluid dynamics solvers. The DSMC parameter values are computed for the widely used Variable Hard Sphere (VHS) and the Variable Soft Sphere (VSS) models using the collision-specific pairing approach. The recommended best-fit VHS/VSS parameter values are provided over a temperature range of 1000-20 000 K for a thirteen-species ionized air mixture. Use of the VSS model is necessary to achieve consistency in transport processes of ionized gases. The agreement of the VSS model transport properties with the transport properties as determined by the ab initio collision integral fits was found to be within 6% in the entire temperature range, regardless of the composition of the mixture. The recommended model parameter values can be readily applied to any gas mixture involving binary collisional interactions between the chemical species presented for the specified temperature range.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Kinetic Simulations of Microstructural Evolution (KSOME)

"Kinetic simulations of microstructural evolution" (KSOME) is an object Kinetic Monte Carlo (OMKC) simulation code. It is developed to simulate microstructural evolution in materials during irradiation. KSOME is developed from ground up with priority given to the flexibility, ease of upgradability, and computation efficiency, in that order. With previously developed simulation codes, various processes (more precisely, the diffusion-reaction processes) that can occur in a system were hardwired into the code. Hence, to perform higher fidelity simulations, a significant coding effort was required every time to incorporate either a more accurate description of existing processes or new processes. With KSOME, the necessity for frequent code upgrades whenever there is a need to perform higher fidelity simulations is either eliminated or reduced significantly. In KSOME, the categories of various diffusion-reaction processes and the data-management system are hardwired, while the execution of the diffusion-reaction processes specific to a system is specified via input files. In the present version of KSOME, the analytical expression required to calculate defect interaction radii are inputted via a text file. However, the ability to parse mathematical expressions from a text file can be extended to input the analytical expression to calculate other defect properties; including the expressions to calculate the change in the migration barriers of mobile defects due to long-range interaction with extended defects

Nandipati, Giridhar [Pacific Northwest National La↗

Implications of z ~ 6 Quasar Proximity Zones for the Epoch of Reionization and Quasar Lifetimes

In this paper, we study quasar proximity zones in the redshift range $5.77\leqslant z\leqslant 6.54$ by homogeneously analyzing 34 medium-resolution spectra, encompassing both archival and newly obtained data, and exploiting recently updated systemic redshift and magnitude measurements. Whereas previous studies found strong evolution of proximity zone sizes with redshift and argued that this provides evidence for a rapidly evolving intergalactic medium (IGM) neutral fraction during reionization, we measure a much shallower trend $\propto {(1+z)}^{-1.44}$. We compare our measured proximity zone sizes to predictions from hydrodynamical simulations post-processed with one-dimensional radiative transfer and find good agreement between observations and theory, irrespective of the ionization state of the ambient IGM. This insensitivity to IGM ionization state has been previously noted, and results from the fact that the definition of proximity zone size as the first drop of the smoothed quasar spectrum below the 10% flux transmission level probes locations where the ionizing radiation from the quasar is an order of magnitude larger than the expected ultraviolet ionizing background that sets the neutral fraction of the IGM. Our analysis also uncovered three objects with exceptionally small proximity zones (two have ${R}_{p}\lt 1$ proper Mpc), which constitute outliers from the observed distribution and are challenging to explain with our radiative transfer simulations. Finally, we consider various explanations for their origin, such as strong absorption line systems associated with the quasar or patchy reionization, but find that the most compelling scenario is that these quasars have been shining for ≲10 5 years.

79 ASTRONOMY AND ASTROPHYSICS↗