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Assessing the Ability of Zonal δ 18 O Contrast in Benthic Foraminifera to Reconstruct Deglacial Evolution of Atlantic Meridional Overturning Circulation
δ 18 O in foraminifera δ 18 O c ) is a useful proxy for density, and the strength of the Atlantic Meridional Overturning Circulation (AMOC) can be reconstructed by the zonal density contrast in the Atlantic. However, whether the deglacial zonal δ 18 O c contrast can represent the AMOC change is still unclear. δ 18 O c contrast across the Florida Straits has been hypothesized as a proxy for the AMOC evolution during the last deglaciation, but the strength of Florida Current could also be influenced by wind forcing. In this work, we examine the ability of the zonal δ 18 O c contrast to reconstruct AMOC in a deglacial model simulation. The model simulation suggests that the deglacial variation of the Florida Current strength is dominated by AMOC, with the wind effect on the variation of the Florida Current being negligible. Furthermore, the δ 18 O c contrast across the western boundary along the entire Atlantic and the basin-wide δ 18 O c contrast in the North Atlantic in the upper ocean can also be used to reconstruct AMOC. However, using basin-wide δ 18 O c contrast to reconstruct AMOC in the South Atlantic is not possible at all water depths. In the subtropical South Atlantic, the basin-wide δ 18 O c contrast is decoupled from the density contrast between 400 to 600 m through the deglaciation because of the deglacial change of the Antarctic Intermediate Water. Thus, δ 18 O c is a useful proxy to reconstruct past density and in turn past AMOC, but caution has to be used when using the basin-wide δ 18 O c contrast to reconstruct the basin-wide density contrast in the South Atlantic.
Numerical Simulation and Modeling of Hydrogen Gas Evolution on Planar and Microwire Array Electrodes
The impact of gas evolution on the electrochemical characteristics of planar electrodes and microwire array electrodes has been analyzed using modeling and simulation. The impacts can mainly be broken into three phenomena: a) a shift in the local reversible hydrogen electrode potential; b) hyperpolarization; and c) an increase in the solution resistance of the electrolyte. The local reversible hydrogen electrode potential shift was found to play the most important role, constituting >40% of the total potential drop between the cathode and reference electrode, following correction for cell resistance. Compared to planar electrodes, a microwire array structure reduces the impact of bubbles on the solution conductance, but the shift in the local reversible hydrogen electrode potential varies with distance from the actual electrode surface.
Report on casting modeling and simulation
Abstract Not Provided
Understanding Creep Mechanisms in Graphite with Experiments, Multiscale Simulations, and Modeling
Disordering mechanisms in graphite have a long history with conflicting viewpoints. Using Raman and x-ray photon spectroscopy, electron microscopy, x-ray diffraction experiments and atomistic modeling and simulations, the current project has developed a fundamental understanding of early-to-late state radiation damage mechanisms in nuclear reactor grade graphite (NBG-18 and PCEA). We show that the topological defects in graphite play an important role under neutron and ion irradiation.
Evaluation of Spray and Combustion Models for Simulating Dilute Combustion in a Direct-Injection Spark-Ignition Engine
Dilute combustion in spark-ignition engines has the potential to improve thermal efficiency by mitigating knock and by reducing throttling and wall heat losses. However, ignition and combustion processes can become unstable for dilute operation due to a lowered laminar flame speed, resulting in excessive cycle-to-cycle variability (CCV) of the combustion process. To compensate for the slower combustion in less reactive mixtures, a modified intake port geometry can be employed to generate a strong tumble flow in the cylinder and elevate turbulence levels around the spark plug, thereby promoting a faster transition to turbulent deflagration. Consequently, optimizing combustion chamber geometry and operating strategy is crucial to maximizing the benefits of using dilute combustion with enhanced in-cylinder turbulence across a wide range of operating conditions. Computational fluid dynamics (CFD) simulations can be utilized for virtual engine optimization tasks, but this would require the models to be truly predictive regarding the impact of changes to the engine design and operational parameters.In this study, multicycle large-eddy simulations (LES) are performed for a direct-injection spark-ignition engine to investigate the model performance in predicting engine combustion characteristics with respect to changes in the intake configuration. A tumble plate that blocks the lower part of the intake port inlet is used to vary the tumble. A set of CFD models that have been recently developed are employed, which takes into account the drag of nonspherical droplets, flash-boiling behavior of liquid sprays, spray-wall interaction, surrogate formulation of a research-grade E10 gasoline, and fast chemical kinetic solvers. Simulation results are compared to experimental engine data in terms of cylinder pressure, apparent heat release rate, mass fraction burned timing, and flame images. It is found that LES employing the state-of-the-art CFD models are capable of properly predicting the spray processes and reproducing the measured mean cylinder pressure for the case with the tumble plate. On the other hand, the LES over-predicts the combustion rate during the early combustion stage and under-estimates the CCV, and these discrepancies become larger when the tumble plate is removed.
Biochemical Process Modeling and Simulation (BPMS)
The Biochemical Process Modeling and Simulation project aims to reduce the cost and time of research by applying theory, modeling, and simulation to the most relevant bottlenecks in the biochemical process. We use molecular modeling, quantum mechanics, metabolic modeling, fluid dynamics, and reaction-diffusion methods in close collaboration with pretreatment, hydrolysis, upgrading, and TEA. The project's outcomes are increased yields and efficiency of the biochemical process, added value to products, and reduced price of fuels by specifically targeting catalytic efficiency, reactor design, enzyme efficiency, and microbial design. We work closely with experimental projects to identify problems and iterate with experiments to find and refine solutions. By working with experimentalists, we decide on problems that can be solved with simulation that could otherwise not be solved or would take too long with experiment alone to reach BETO's targets. Over the years, we have produced solutions that have resulted in determining the most likely fatty-acid derivative for passive transport out of bacteria that upgrade biomass, and we have also designed enzyme mutations for enhanced lignin upgrading. Metabolic models have been developed to tune the activity of 2,3 butanediol production for the 2030 target. A computational method to deliver understanding of how complex omics data can be interpreted in the metabolic pathways of organisms used in the Agile Biofoundry. We have found methods to overcome specific barriers and continue to develop those methods. Our reactor studies have guided the design of both the microbes and reactors for aerobic and micro-aerobic production at all scales and have been instrumental in improving the accuracy of techno-economic analysis models. This project is essential in the process of selecting the final processes for 2030 SAF production targets. More specifically, recently, we have: 1) Predicted the strength of the basic structural interactions in commodity plastics to provide guidance for plastics upcycling strategies. 2) Developed computational tool to improve the characterization of lignin-derived compounds 3) Developed new methodologies to enable Machine Learning-based Directed Evolution for protein engineering. 4) Developed Machine Learning methods to predict protein promiscuity and mutations to further improve microbial and enzymatic driven processes and demonstrated the utility of ML approaches to engineering proteins from sparse experimental datasets. 5) Developed new methods to enable high-fidelity simulation of aerobic fermentation at industrial scale and resolving mismatch of time scales through subcycling/operator splitting 7) Identified the difficulty in preventing local high-oxygen conditions in industrial bubble columns, which leads to less-desirable acetoin production, suggesting future research directions in alternative reactor configurations (e.g loop reactors, shallow-channel reactors).
BETO 2021 Peer Review - Biochemical Process Modeling and Simulation (BPMS)
The Biochemical Process Modeling and Simulation project aims to reduce the cost and time of research by applying theory, modeling, and simulation to the most relevant bottlenecks in the biochemical process. We use molecular modeling, quantum mechanics, metabolic modeling, fluid dynamics, and reaction-diffusion methods in close collaboration with pretreatment, hydrolysis, upgrading, and TEA. The project's outcomes are increased yields and efficiency of the biochemical process, added value to products, and reduced price of fuels by specifically targeting catalytic efficiency, reactor design, enzyme efficiency, and microbial design.
CHARMM-GUI Nanomaterial Modeler for Modeling and Simulation of Nanomaterial Systems
Molecular modeling and simulation are invaluable tools for nanoscience that predict mechanical, physicochemical, and thermodynamic properties of nanomaterials and provide molecular-level insight into underlying mechanisms. However, building nanomaterial-containing systems remains challenging due to the lack of reliable and integrated cyberinfrastructures. Here we present Nanomaterial Modeler in CHARMM-GUI, a web-based cyberinfrastructure that provides an automated process to generate various nanomaterial models, associated topologies, and configuration files to perform state-of- the-art molecular dynamics simulations using most simulation packages. The nanomaterial models are based on the interface force field, one of the most reliable force fields (FFs). The transferability of nanomaterial models among the simulation programs was assessed by single-point energy calculations, which yielded 0.01% relative absolute energy differences for various surface models and equilibrium nanoparticle shapes. Three widely used Lennard-Jones (LJ) cutoff methods are employed to evaluate the compatibility of nanomaterial models with respect to conventional biomolecular FFs: simple truncation at r = 12 Å (12 cutoff), force-based switching over 10 to 12 Å (10-12 fsw), and LJ particle mesh Ewald with no cutoff (LJPME). The FF parameters with these LJ cutoff methods are extensively validated by reproducing structural, interfacial, and mechanical properties. As a result, we find that the computed density and surface energies are in good agreement with reported experimental results, although the simulation results increase in the following order: 10-12 fsw <12 cutoff < LJPME. Nanomaterials in which LJ interactions are a major component show relatively higher deviations (up to 4% in density and 8% in surface energy differences) compared with the experiment. Nanomaterial Modeler's capability is also demonstrated by generating complex systems of nanomaterial-biomolecule and nanomaterial-polymer interfaces with a combination of existing CHARMM-GUI modules. We hope that Nanomaterial Modeler can be used to carry out innovative nanomaterial modeling and simulations to acquire insight into the structure, dynamics, and underlying mechanisms of complex nanomaterial-containing systems.
Single reader between-cases AUC estimator with nested data
The area under the receiver operating characteristic curve (AUC) is widely used in evaluating diagnostic performance for many clinical tasks. It is still challenging to evaluate the reading performance of distinguishing between positive and negative regions of interest (ROIs) in the nested-data problem, where multiple ROIs are nested within the cases. To address this issue, we identify two kinds of AUC estimators, within-cases AUC and between-cases AUC. We focus on the between-cases AUC estimator, since our main research interest is in patient-level diagnostic performance rather than location-level performance (the ability to separate ROIs with and without disease within each patient). Another reason is that as the case number increases, the number of between-cases paired ROIs is much larger than the number of within-cases ROIs. We provide estimators for the variance of the between-cases AUC and for the covariance when there are two readers. We derive and prove the above estimators’ theoretical values based on a simulation model and characterize their behavior using Monte Carlo simulation results. We also provide a real-data example. Moreover, we connect the distribution-based simulation model with the simulation model based on the linear mixed-effect model, which helps better understand the sources of variation in the simulated dataset.
Molten Salt Reactor Campaign Modeling and Simulation Program Plan
The modeling and simulation activities within the Molten Salt Reactor Research and Development Campaign of the US Department of Energy Office of Nuclear Energy Advanced Reactor Technologies Program facilitate the development and application of analysis tools for the licensing and design of molten salt reactors.
Plateau to River Model Predictive Simulations for All Ensemble Realizations to Support Modeling Work in Fiscal Year 2025
The purpose of this environmental calculation file (ECF) is to document predictions of flow and hydraulic head on the Central Plateau of the Hanford Site using the Plateau-to-River (P2R) Model (CP-57037, Model Package Report for the Plateau-to-River Model: Version 9.1). This calculation documents the simulation of the groundwater for the parent model domain of the P2R Model as a basis for use in other applications of the P2R Model. This application is unique from the standpoint that it will simulate all ensemble member models of the P2R Model whereas other applications may only utilize specific ensemble members. These simulations provide results that can be used in the process of selecting an appropriate subset of ensemble members for other applications.
Nuclear Energy Advanced Modeling and Simulation (NEAMS) Accident Tolerant Fuels High Impact Problem: FeCrAl Modeling Capabilities
Iron-chromium-aluminum alloys are a potential candidate replacement for zirconium-based claddings in light water reactor fuel rods due to their increased strength (lower creep rates and higher yield stress) and slower oxidation kinetics with steam. Their larger neutron absorption cross-section necessitates thinner claddings and larger fuel pellets to maintain the same as-fabricated fuel-to-clad gap. The aggressive development schedule of the United States Department of Energy's (DOE) Advanced Fuels Campaign (AFC) to have potential accident tolerant fuels (ATF) concepts in lead test rods or assemblies by 2022 has necessitated the need for advanced modeling and simulation techniques to investigate the behavior of these materials under normal operating and accident conditions. This report presents the modeling capabilities for FeCrAl claddings at the engineering (continuum) scale developed as part of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) high impact problem (HIP). Sensitivity studies of select material parameters have been completed to determine their significance in predictions of important fuel performance parameters such as fuel centerline and surface temperatures, cladding stresses and strains, fission gas released, and rod internal pressure. Comparative analyses of FeCrAl and Zircaloy-4 claddings for separate effects conditions are presented.
Development of a wind turbine model and simulation platform using an acausal approach: Multiphysics modeling, validation, and control
This article presents the development of the Control-oriented, Reconfigurable, and Acausal Floating Turbine Simulator (CRAFTS). CRAFTS has a modular, hierarchical model architecture that enables rapid and accurate simulation of wind turbines. The architecture facilitates the incorporation of model variants, and its system reconfiguration features help simulate multiple design variants. CRAFTS also supports the integration of models developed on a causality-free platform (e.g., Modelica®) with existing causal models. This article focuses on the validation of a land-based wind turbine models against OpenFAST, an industry-standard platform, for several test cases. Closed-loop scenarios are also tested using the standard ROSCO controller and compared against OpenFAST. In addition, a nonlinear controller developed in our prior work is also evaluated. The test cases demonstrate the user-friendly and computationally efficient capabilities of CRAFTS to facilitate control co-design, assist in incorporating multiphysics models, be adaptable to design variants, and allow for rapid simulations to validate models and evaluate controllers.
Can-Crush Model and Simulations for Verifying Uncertainty Quantification Method for Sparse Stress-Strain Curve Data.
Abstract not provided.
Opportunities and challenges in process modeling and simulation of electrochemical systems
Electrochemical technologies have garnered intense interest in both academic research and industrial applications due to their potential to increase energy efficiency and reduce carbon footprint. However, electrochemical process fundamentals have been absent from the chemical process simulators available to millions of chemical engineers worldwide. To expedite process research and development of electrochemical technologies in the chemical industry, it is imperative that essential electrochemical process fundamentals be incorporated into process simulators to support modeling and simulation of electrochemical processes. Here, this study examines three process fundamentals key to the research and development of electrochemical processes: electrochemical reaction kinetics, electrolyte thermodynamics, and heat and mass transfer. It further illustrates application of these process fundamentals with a case study modeling an electrochemical process for the conversion of acrylonitrile to adiponitrile. The modeling example highlights the roles of applied voltage on reaction rates, and electron flow rates on the performance of electrochemical processes. It suggests that the applied voltage and electron flow rates are two unique concepts that should be included in simulators for electrochemical processes.
A hybrid embedded discrete fracture model for simulating tight porous media with complex fracture systems
Numerical simulation considering complex fracture networks in tight oil reservoir becomes a hot issue during these years. Recently, embedded discrete fracture model (EDFM) shows great advantages over the DFM approaches in both calculation efficiency and simplicity of simulation workflow. EDFM has been widely used in tight oil/gas natural energy or enhanced oil recovery (EOR) development. If a large number of small-scale natural fractures exist in reservoir, the calculation efficiency of EDFM method may decrease. A new hybrid simulation model combining the EDFM and dual porosity (DP) model is proposed. The large-scale fractures are dealt with EDFM method while small scale fractures are dealt with DP model. Considering the low permeability of matrix, transient transfer between matrix and natural fracture is considered. The proposed hybrid model is validated compared with the local grid refinement (LGR) model and EDFM-MINC model, and the difference between transient transfer and pseudo-steady-state transfer effect on production is presented. Finally, two test cases are presented, and the sensitivity of some key parameters are investigated. Result shows that the new simulation model has higher calculation efficiency than LGR and EDFM-MINC models. Meanwhile, it honors a good accuracy. The pseudo-steady-state transfer between matrix and natural fracture leads to big error in tight oil production performance analysis both in single phase and two phases flow. Low matrix permeability and big matrix size increase the production difference between pseudo-steady-state transfer and transient transfer models. The proposed model can simulate reservoirs considering stochastic permeability distribution.