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COMPUTATIONAL MODELING AND SIMULATION OF ALUMINIUM SMELTING PROCESS USING OPENFOAM
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Computational simulation of coupled poromechanical processes in deformable fractured and porous media.
Abstract not provided.
Numerical Simulation of Post Detonation Processes with Detailed Chemical Kinetics.
Abstract not provided.
A Coupled Approach for Thermal-Mechanical Simulation of the LENS Process.
Abstract not provided.
Computational Simulation of Coupled Poromechanical Processes in Deformable Porous Media.
Abstract not provided.
A Data Toolkit for Ultrahigh-resolution E3SM Simulation on Massively Parallel Processing Systems
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Computational simulation of a 100 kW dual circulating fluidized bed reactor processing coal by chemical looping with oxygen uncoupling
Chemical looping with oxygen uncoupling (CLOU) is a promising carbon capture technology that utilizes two interconnected fluidized-bed reactors to separate oxygen from air using a metal oxide, and then to use that oxygen to combust fuel in a nitrogen-free environment. CLOU is particularly well suited for solid fuels such as coal since released O 2 will readily combust with solid char. This study presents simulations of the University of Utah's dual fluidized bed chemical looping process development unit (PDU) operating as a CLOU system at 100 kW th , using CPFD Software's Barracuda-VR™ CFD modeling program. A full 3D model of the PDU was used including both reactors, as well as loop seals and cyclone separators. Hydrodynamic settings and the drag model are based on previous cold-flow validation experiments. Mechanisms describing CLOU reaction kinetics for cuprous oxide oxidation in the air reactor and cupric oxide reduction in the fuel reactor were adapted from previously completed experimental work. Coal char kinetics were based on the carbon-hydrogen-nitrogen-oxygen-sulfur, CHNOS, method. Submodels for devolatilization, gasification, and homogenous gas-phase reactions used relationships from the literature. Results predict volatile burnout almost immediately, though coal combustion continues into the upper portions of the fuel reactor and cyclone. Lastly, nitrogen gas leakage into the fuel reactor is shown to be mostly carryover from the air reactor
Hybrid framework for the simulation of stochastic chemical kinetics
Stochasticity plays a fundamental role in various biochemical processes, such as cell regulatory networks and enzyme cascades. Isothermal, well-mixed systems can be modelled as Markov processes, typically simulated using the Gillespie Stochastic Simulation Algorithm (SSA) [25]. While easy to implement and exact, the computational cost of using the Gillespie SSA to simulate such systems can become prohibitive as the frequency of reaction events increases. This has motivated numerous coarse-grained schemes, where the “fast” reactions are approximated either using Langevin dynamics or deterministically. While such approaches provide a good approximation when all reactants are abundant, the approximation breaks down when one or more species exist only in small concentrations and the fluctuations arising from the discrete nature of the reactions become significant. This is particularly problematic when using such methods to compute statistics of extinction times for chemical species, as well as simulating non-equilibrium systems such as cell-cycle models in which a single species can cycle between abundance and scarcity. In this paper, a hybrid jump-diffusion model for simulating well-mixed stochastic kinetics is derived. It acts as a bridge between the Gillespie SSA and the chemical Langevin equation. For low reactant reactions the underlying behaviour is purely discrete, while purely diffusive when the concentrations of all species are large, with the two different behaviours coexisting in the intermediate region. A bound on the weak error in the classical large volume scaling limit is obtained, and three different numerical discretisations of the jump-diffusion model are described. The benefits of such a formalism are illustrated using computational examples.
Classical molecular dynamics simulation of electronically non-adiabatic processes
Both classical and quantum mechanics (as well as hybrids thereof, i.e., semiclassical approaches) find widespread use in simulating dynamical processes in molecular systems. For large chemical systems, however, which involve potential energy surfaces (PES) of general/arbitrary form, it is usually the case that only classical molecular dynamics (MD) approaches are feasible, and their use is thus ubiquitous nowadays, at least for chemical processes involving dynamics on a single PES (i.e., within a single Born-Oppenheimer electronic state). Our paper reviews recent developments in an approach which extends standard classical MD methods to the treatment of electronically non-adiabatic processes, i.e., those that involve transitions between different electronic states. This approach treats nuclear and electronic degrees of freedom (DOF) equivalently (i.e., by classical mechanics, thereby retaining the simplicity of standard MD), and provides "quantization" of the electronic states through a symmetrical quasi-classical (SQC) windowing model. The approach is seen to be capable of treating extreme regimes of strong and weak coupling between the electronic states, as well as accurately describing coherence effects in the electronic DOF (including the de-coherence of such effects caused by coupling to the nuclear DOF). A survey of recent applications is presented to illustrate the performance of the approach. We also described is a newly developed variation on the original SQC model (found universally superior to the original) and a general extension of the SQC model to obtain the full electronic density matrix (at no additional cost/complexity).
Comparison of edge turbulence characteristics between DIII-D and C-Mod simulations with XGC1
The physical processes taking place at the separatrix and scrape-off layer regions are crucial for the operation of tokamaks as they govern the interaction of hot plasma with the vessel walls. Numerical modeling of the edge with state-of-the-art codes attempts to elucidate the complex interactions between neoclassical drifts, turbulence, poloidal and parallel flows that control the physical set-up of the SOL region. Here, we present post-processing analysis of simulation results from the gyrokinetic code XGC1, comparing and contrasting edge turbulence characteristics from a simulation of the DIII-D tokamak against a simulation of the Alcator C-Mod tokamak. We find that the equilibrium ExB flux across the separatrix has a similar poloidal pattern in both discharges which can be explained by rB-drifts and trapped ion excursions. Furthermore, collisionality is noted to play a major role in the way that it prevents local charge accumulations from having more global effects in the C-Mod case. In both cases, turbulent electron heat flux is observed to be higher than the ion one and is possibly related to the need of electrons to maintain quasineutrality through the only channel available to them for exiting the confinement. By Fourier analysis, we identify turbulent frequencies and growth rates of the dominant mode in both simulations. In the case of C-Mod, these numbers point to the presence of a drift wave. In the DIII-D case, further linear simulations with the Gene code reveal a trapped electron mode. Furthermore, using a blob detection and tracking tool, we present the amplitude and size distributions of the blobs from both simulations. The amplitude distributions are in qualitative agreement with experimental observations while the size distributions are consistent with the fact that most of the blobs are not connecting to the divertor plates and suggest that they are generated by the shearing of the turbulent modes.
Excited State Intramolecular Proton Transfer with Nuclear-Electronic Orbital Ehrenfest Dynamics
The recent development of the Ehrenfest dynamics approach in the nuclear-electronic orbital (NEO) framework provides a promising way to simulate coupled nuclear-electronic dynamics. Our previous study showed that the NEO-Ehrenfest approach with a semi- classical traveling proton basis method yields accurate predictions of molecular vibrational frequencies. In this work, we provide a more thorough analysis of the semiclassical traveling proton basis method to elucidate its validity and convergence behavior. We also conduct NEO-Ehrenfest dynamics simulations to study an excited state intramolecular proton transfer process. These simulations reveal that nuclear quantum effects influence the predictions of proton transfer reaction rates and kinetic isotope effects due to the intrinsic delocalized nature of the quantum nuclear wave function. This work illustrates the importance of nuclear quantum effects in coupled nuclear-electronic dynamical processes and shows that the NEO-Ehrenfest approach can be a powerful tool to provide insights and predictions for these processes.
Microphysical Piggybacking in the Weather Research and Forecasting Model
Abstract This paper presents incorporation of the microphysical piggybacking into the Weather Research and Forecasting (WRF) model. Microphysical piggybacking is to run a single simulation applying two microphysical schemes, the first scheme driving the simulation and the second piggybacking this simulated flow. “Driving the simulation” means that the simulated microphysical processes, affect the cloud buoyancy and thus force the simulated flow. In contrast, the piggybacking variables are advected by the simulated flow and undergo microphysical transformation, but they do not affect the simulated flow (like in prescribed flow—kinematic—simulations). The two sets of variables (driver and piggybacker) include temperature, water vapor mixing ratio, and all microphysical variables. We provide details of implementing piggybacking into the WRF model, illustrate its applications, and demonstrate the benefits of this methodology in two idealized three‐dimensional cases: (a) a squall line case applying two microphysics schemes, the Thompson bulk microphysics scheme and the University of Pécs/NCAR bin (UPNB) scheme. The piggybacking simulations revealed that the microphysics‐dynamics interaction plays a more important role than the pure microphysical size sorting effect in the transition zone formation. (b) A case of daytime shallow‐to‐deep convective development over land. This case uses the UPNB scheme and contrasts convection developing in environments with either pristine or polluted cloud condensation nuclei (CCN). The piggybacking results indicated that the increase of cloud cover and decrease of supersaturation are mainly associated with the microphysical effect of increasing CCN while the change of precipitation on the ground is also influenced by microphysics‐dynamics interactions.
Observation of Downward Facing Pool Boiling on a Hemispherical Vessel under External Reactor Vessel Cooling
It is a great challenge to ensure the safety of nuclear power plant during a severe accident. One of the major concerns is to overheat the reactor core which potentially may create a nuclear crisis if the core cooling fails. The concept of In-vessel retention (IVR) by passive external reactor vessel cooling (ERVC) in a flooded cavity of pressurized water reactor (PWR) is a viable and effective approach to retain radioactive core melt within the reactor pressure vessel (RPV). As long as the heat flux at the lower head of the RPV is lower than the critical heat flux (CHF) limit at the corresponding point, nucleate boiling will be the prevailing regime. In that case, the temperature of outer surface can be maintained near the saturated temperature of water such that the reactor vessel is able to be sufficiently cooled to sustain its thermal and structural integrity. Owing to the practical significance of this IVR-ERVC concept, there were many experimental and theoretical studies to investigate the two-phase flow natural circulation phenomena including the effect of inclination angle on the CHF, based on which many different empirical or semiempirical correlations were developed for CHF by fitting the experimental results. For the engineering applications, reactor-scale facilities such as ULPU series, KAIST facility, CYBL and FIRM were built to experimentally verify and validate the feasibility of ERVC for different design of reactors. Besides, for the research on physical mechanism of downward facing pool boiling, laboratory-scale experiments such as DELTA, CASA and SBLB were performed to visually and theoretically simulate the process of IVR-ERVC. All of the aforementioned test facilities and experiments provided a simulation of the downward facing boiling process and experimental study on the CHF limits during the ERVC conditions of different types of reactors. There were also some visualized investigations on the two-phase flow behavior in both quenching and steady state experiments. In this study, a scale-down three-dimensional downward facing pool boiling facility (iSBLB) was built to investigate the two phase natural circulation flow characteristics during the ERVC process. The general morphologies of vapor mass at different locations were visually recorded using the high-speed camera. The observation results showed that vapor behavior along the hemispherical curved surface was periodical. The boiling phenomenon was quite different from those on all other surface orientations.
Managing complexity in simulations of land surface and near-surface processes
Increasing computing power and the growing role of simulation in Earth systems science have led to an increase in the number and complexity of processes in modern simulators. We present a multiphysics framework that specifies interfaces for coupled processes and automates weak and strong coupling strategies to manage this complexity. Process management is enabled by viewing the system of equations as a tree, where individual equations are associated with leaf nodes and coupling strategies with internal nodes. A dynamically generated dependency graph connects a variable to its dependencies, streamlining and automating model evaluation, easing model development, and ensuring models are modular and flexible. Additionally, the dependency graph is used to ensure that data requirements are consistent between all processes in a given simulation. Here we discuss the design and implementation of these concepts within the Arcos framework, and demonstrate their use for verification testing and hypothesis evaluation in numerical experiments.
Laboratory-Scale Melter Systems for Simulated and Real AP-105 Tank Waste - 19301
The Hanford Tank Waste Treatment and Immobilization Plant is being constructed to vitrify the nuclear waste stored in underground tanks on the Hanford Site. Through this conversion process, waste components become partitioned into one of two product streams: glass and off-gas, including condensate. A small-scale melter system is appropriate for analyzing the waste-to-glass process because it does not require the high volumes of input waste or resource commitment of a large-scale melter system while providing dynamic information that can be difficult to determine from batch reactions in a crucible system. A continuous laboratory-scale melter (CLSM) was sized to collect the relevant process and chemical information from obtainable volumes of Hanford tank waste and designed to operate with a continuous feeding process while periodically pouring glass product and collecting off-gas. Two CLSMs were constructed: one in a non-radioactive environment for processing waste simulants and another in a fume hood capable of handling radioactive material for processing actual Hanford tank waste. Multiple waste simulants were first tested in the non-radioactive CLSM to determine the processability and desired operating window for actual tank waste. About 12 liters of real waste from Hanford tank 241-AP-105 were received, filtered, and ion exchanged for removal of Cs-137. This quantity of waste was vitrified into 9.5 kg of glass product over the course of ∼15 hours of feeding to the CLSM. (authors)
Evaluation of the atmosphere–land–ocean–sea ice interface processes in the Regional Arctic System Model version 1 (RASM1) using local and globally gridded observations
The Regional Arctic System Model version 1 (RASM1) has been developed to provide high-resolution simulations of the Arctic atmosphere–ocean–sea ice–land system. Here, we provide a baseline for the capability of RASM to simulate interface processes by comparing retrospective simulations from RASM1 for 1990–2014 with the Community Earth System Model version 1 (CESM1) and the spread across three recent reanalyses. Evaluations of surface and 2 m air temperature, surface radiative and turbulent fluxes, precipitation, and snow depth in the various models and reanalyses are performed using global and regional datasets and a variety of in situ datasets, including flux towers over land, ship cruises over oceans, and a field experiment over sea ice. These evaluations reveal that RASM1 simulates precipitation that is similar to CESM1, reanalyses, and satellite gauge combined precipitation datasets over all river basins within the RASM domain. Snow depth in RASM is closer to upscaled surface observations over a flatter region than in more mountainous terrain in Alaska. The sea ice–atmosphere interface is well simulated in regards to radiation fluxes, which generally fall within observational uncertainty. RASM1 monthly mean surface temperature and radiation biases are shown to be due to biases in the simulated mean diurnal cycle. At some locations, a minimal monthly mean bias is shown to be due to the compensation of roughly equal but opposite biases between daytime and nighttime, whereas this is not the case at locations where the monthly mean bias is higher in magnitude. These biases are derived from errors in the diurnal cycle of the energy balance (radiative and turbulent flux) components. Therefore, the key to advancing the simulation of SAT and the surface energy budget would be to improve the representation of the diurnal cycle of radiative and turbulent fluxes. The development of RASM2 aims to address these biases. Still, an advantage of RASM1 is that it captures the interannual and interdecadal variability in the climate of the Arctic region, which global models like CESM cannot do.