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At least 55 records · Page 3

Bridging molecular-scale interfacial science with continuum-scale models

Solid–water interfaces are crucial for clean water, conventional and renewable energy, and effective nuclear waste management. However, reflecting the complexity of reactive interfaces in continuum-scale models is a challenge, leading to oversimplified representations that often fail to predict real-world behavior. This is because these models use fixed parameters derived by averaging across a wide physicochemical range observed at the molecular scale. Recent studies have revealed the stochastic nature of molecular-level surface sites that define a variety of reaction mechanisms, rates, and products even across a single surface. To bridge the molecular knowledge and predictive continuum-scale models, we propose to represent surface properties with probability distributions rather than with discrete constant values derived by averaging across a heterogeneous surface. This conceptual shift in continuum-scale modeling requires exponentially rising computational power. By incorporating our molecular-scale understanding of solid–water interfaces into continuum-scale models we can pave the way for next generation critical technologies and novel environmental solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A three-dimensional pore-scale model for redox flow battery electrode design analysis

A three-dimensional (3-D) pore-scale model has been developed to construct multiscale fibrous electrodes for redox flow batteries (RFB). New designs, such as biporous electrodes modify electrode structures by creating secondary pores on single carbon fiber to reduce internal battery resistance. Existing pore-scale models only resolve electrodes to the single carbon fiber scale and cannot incorporate recent multiscale electrode designs into numerical models. Our new model aims to bridge this gap and provide a tool to rapidly screen new electrode configurations. Two multiscale electrodes, laser-perforated and biporous electrodes, were investigated at varying operation conditions with the proposed 3-D pore-scale models. The laser-perforated electrode exhibits a reduced pressure drop, but follows the same permeability correlation compared to the corresponding pristine electrode. For the biporous electrode, the added specific surface area and faster reaction kinetics from the secondary pores are the most influential factors leading to improved battery efficiency. However, operating the biporous electrode in limiting current density conditions should be avoided due to the decreased mass transfer efficiency and a more significant voltage loss. Finally, we believe that our 3-D pore-scale model can accelerate the flow battery electrode design process and provide new insights into electrode geometry optimizations.

25 ENERGY STORAGE↗

Blood Flow: Multi-scale Modeling and Visualization (July 2011)

Multi-scale modeling of arterial blood flow can shed light on the interaction between events happening at micro- and meso-scales (i.e., adhesion of red blood cells to the arterial wall, clot formation) and at macro-scales (i.e., change in flow patterns due to the clot). Coupled numerical simulations of such multi-scale flow require state-of-the-art computers and algorithms, along with techniques for multi-scale visualizations. This animation presents early results of two studies used in the development of a multi-scale visualization methodology. The first illustrates a flow of healthy (red) and diseased (blue) blood cells with a Dissipative Particle Dynamics (DPD) method. Each blood cell is represented by a mesh, small spheres show a sub-set of particles representing the blood plasma, while instantaneous streamlines and slices represent the ensemble average velocity. In the second we investigate the process of thrombus (blood clot) formation, which may be responsible for the rupture of aneurysms, by concentrating on the platelet blood cells, observing as they aggregate on the wall of an aneruysm. Simulation was performed on Kraken at the National Institute for Computational Sciences. Visualization was produced using resources of the Argonne Leadership Computing Facility at Argonne National Laboratory.

59 BASIC BIOLOGICAL SCIENCES↗

An alternative scaling model for neutron production in Z-pinch devices

The DD neutron yield (Y{sub n}) from z-pinches, either dense plasma foci or fast radial pinches, has been fitted for decades to the scaling model Y{sub n} {approx} {alpha}(I{sub max}){sup {delta}}, where {alpha} is a numerical scaling coefficient, I{sub max} the peak current, and 3 < {delta} < 5. The data from 12 000 pulses analyzed from eight different z-pinches presented in this paper show that Y{sub n} varies by as much as {+-}15 000% about the best fit value of the conventional scaling model with {delta} = 4. A revised scaling model derived from the reaction rate equation and a circuit model that includes the time derivative of the current dI/dt (normalized to its initial value) reduces the scatter in data from {+-}15 000% to {+-}100%. For the special case of very high normalized dI/dt, the standard deviation between the revised scaling prediction and the measured neutron yields is reduced to just {+-}30%. Implications of this revised scaling for higher current pinches are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

System-Scale Model of Aquifer, Vadose Zone, and River Interactions for the Hanford 300 Area - Application to Uranium Reactive Transport

This report represents a synthesis and integration of basic and applied research into a system-scale model of the Hanford 300 Area groundwater uranium plume, supported by the U.S. Department of Energy’s Richland Operations (DOE-RL) office. The report integrates research findings and data from DOE Office of Science (DOE-SC), Office of Environmental Management (DOE-EM), and DOE-RL projects, and from the site remediation and closure contractor, Washington Closure Hanford, LLC (WCH). The three-dimensional, system-scale model addresses water flow and reactive transport of uranium for the coupled vadose zone, unconfined aquifer, and Columbia River shoreline of the Hanford 300 Area. The system-scale model of the 300 Area was developed to be a decision-support tool to evaluate processes of the total system affecting the groundwater uranium plume. The model can also be used to address “what if” questions regarding different remediation endpoints, and to assist in design and evaluation of field remediation efforts. For example, the proposed cleanup plan for the Hanford 300 Area includes removal, treatment, and disposal of contaminated sediments from known waste sites, enhanced attenuation of uranium hot spots in the vadose and periodically rewetted zone, and continued monitoring of groundwater with institutional controls. Illustrative simulations of polyphosphate infiltration were performed to demonstrate the ability of the system-scale model to address these types of questions. The use of this model in conjunction with continued field monitoring is expected to provide a rigorous basis for developing operational strategies for field remediation and for defining defensible remediation endpoints.

uranium reactive transport, parallel computing↗

Viscoelastic Model for Lung Parenchyma for Multi-Scale Modeling of Respiratory System - Phase II: Dodecahedral Micro-Model

In the first year of this contractual effort a hypo-elastic constitutive model was developed and shown to have great potential in modeling the elastic response of parenchyma. This model resides at the macroscopic level of the continuum. In this, the second year of our support, an isotropic dodecahedron is employed as an alveolar model. This is a microscopic model for parenchyma. A hopeful outcome is that the linkage between these two scales of modeling will be a source of insight and inspiration that will aid us in the final year's activity: creating a viscoelastic model for parenchyma.

59 BASIC BIOLOGICAL SCIENCES↗

The Earth Model Column Collaboratory (EMC 2 ) v1.1: an open-source ground-based lidar and radar instrument simulator and subcolumn generator for large-scale models

Abstract. Climate models are essential for our comprehensive understanding of Earth's atmosphere and can provide critical insights on future changes decades ahead. Because of these critical roles, today's climate models are continuously being developed and evaluated using constraining observations and measurements obtained by satellites, airborne, and ground-based instruments. Instrument simulators can provide a bridge between the measured or retrieved quantities and their sampling in models and field observations while considering instrument sensitivity limitations. Here we present the Earth Model Column Collaboratory (EMC2), an open-source ground-based lidar and radar instrument simulator and subcolumn generator, specifically designed for large-scale models, in particular climate models, but also applicable to high-resolution model output. EMC2 provides a flexible framework enabling direct comparison of model output with ground-based observations, including generation of subcolumns that may statistically represent finer model spatial resolutions. In addition, EMC2 emulates ground-based (and air- or space-borne) measurements while remaining faithful to large-scale models' physical assumptions implemented in their cloud or radiation schemes. The simulator uses either single particle or bulk particle size distribution lookup tables, depending on the selected scheme approach, to perform the forward calculations. To facilitate model evaluation, EMC2 also includes three hydrometeor classification methods, namely, radar- and sounding-based cloud and precipitation detection and classification, lidar-based phase classification, and a Cloud Feedback Model Intercomparison Project Observational Simulator Package (COSP) lidar simulator emulator. The software is written in Python, is easy to use, and can be straightforwardly customized for different models, radars, and lidars. Following the description of the logic, functionality, features, and software structure of EMC2, we present a case study of highly supercooled mixed-phase cloud based on measurements from the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment (AWARE). We compare observations with the application of EMC2 to outputs from four configurations of the NASA Goddard Institute for Space Studies (GISS) climate model (ModelE3) in single-column model (SCM) mode and from a large-eddy simulation (LES) model. We show that two of the four ModelE3 configurations can form and maintain highly supercooled precipitating cloud for several hours, consistent with observations and LES. While our focus is on one of these ModelE3 configurations, which performed slightly better in this case study, both of these configurations and the LES results post-processed with EMC2 generally provide reasonable agreement with observed lidar and radar variables. As briefly demonstrated here, EMC2 can provide a lightweight and flexible framework for comparing the results of both large-scale and high-resolution models directly with observations, with relatively little overhead and multiple options for achieving consistency with model microphysical or radiation scheme physics.

58 GEOSCIENCES↗

Meso-scale modeling of UO2 nuclear fuel to high burnup

To improve the economics of light water reactors for commercial nuclear energy generation, utility operators are seeking to obtain regulatory approval to run UO2 fuel to higher levels of burnup. One potential impediment to obtaining this approval is the phenomenon of fuel fragmentation, relocation, and dispersal (FFRD). FFRD can result when fuel experiences a rapid temperature transient, such as that occurring during a Loss Of Coolant Accident (LOCA). FFRD has historically been most associated with the rim region in UO2 fuel pellets, where the phenomenon of fragmentation is also referred to as pulverization due to the small size of the fragments. More recent evidence suggests that the so-called “dark zone” (due to its appearance in micrographs) that can be observed in the mid-radial regions of high burnup fuel is also susceptible to FFRD. Although empirical fuel performance models have been developed that can adequately predict pulverization in the rim region under typical LWR conditions, a scientific understanding of what underlies fuel restructuring and subsequent FFRD is lacking even in the rim region, and no models are currently available for the behavior the dark zone. To address these challenges, the U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has employed a multi-scale modeling approach to improve scientific understanding and develop new fuel performance models. In this talk, I will focus on meso-scale efforts, which form a crucial link between atomic-scale and engineering-scale models. Phase-field modeling combined with cluster dynamics is used to predict the restructuring process in the rim region. Phase-field fracture modeling, informed by atomistic simulations, is used to predict the onset of pulverization in the rim region. Combining these techniques together allows the extent of rim pulverization to be predicted. The formation and evolution of the dark zone has also been simulated with the phase-field method, using an improved approach to vacancy source term parameterization. The work shows the important impact of microstructure on fuel performance.

fracture↗

Coupling particle scale model and SuperDEM–CFD for multiscale simulation of biomass pyrolysis in a packed bed pyrolyzer

An efficient biomass pyrolysis process requires a comprehensive understanding of the chemical and physical phenomena that occur at multi-length and time scales. In this study, a multiscale computational approach was developed and validated for biomass pyrolysis in a packed-bed reactor by integrating pyrolysis kinetics, a particle scale model, and SuperDEM-CFD in open-source code MFiX. A one-dimensional particle-scale model that discretizes the characteristic length of biomass particle into layers was developed to predict the intraparticle phenomena inside a single particle. The 1D model was validated by comparing it with a single biomass particle pyrolysis experiment. Here, a recently developed SuperDEM-CFD model was employed to simulate the non-spherical particle-particle contact and fluid-particle interaction. The coupled model was applied to simulate the pyrolysis of cubic biomass particles in a packed bed and validated by comparing with experimental data. Simulation with and without particle-scale model was compared, and the effect of the gas-solid heat transfer models was also investigated.

09 BIOMASS FUELS↗

Towards the Reconstruction of Integrated Genome-Scale Models of Metabolism and Gene Expression

The reconstruction of integrated genome-scale models of metabolism and gene expression has been a challenge for a while now. In fact, various methods that allow integrating reconstructions of Transcriptional Regulatory Networks, gene expression data or both into Genome-Scale Metabolic Models have been proposed. Several of these methods are surveyed in this article, which allowed identifying their strengths and weaknesses concerning the reconstruction of integrated models for multiple prokaryotic organisms. Additionally, the main resources of regulatory information were also surveyed, as the existence of novel sources of regulatory information and gene expression data may contribute for the improvement of methodologies referred herein.

Databases of regulatory information↗

Particle scale modeling of CuFeAlO 4 during reduction with CO in chemical looping applications

Particle scale models that couple reaction phenomena to changes in the solid-state chemistry of an oxygen carrier system are critical to the advancement of the chemical looping concept by allowing for a means to assess process scale up. This work presents an analysis of the reduction for a CuFeAlO 4 oxygen carrier with Carbon Monoxide (CO). The analysis was utilized to aid in the application of particle scale model representation of the carrier system. An experimentally driven study was conducted to provide an array of operational/parametric data sets for the analysis and their impact accessed. Quantification of the cubic spinel oxide phase and changes due to lattice oxygen depletion from reduction were explored to link the solid-state chemistry changes to the reaction progression. Reduction occurred in a multistep process as oxygen was depleted from the structure. Oxygen bound to Cu cations were the first to react with CO. As oxygen was depleted further phase re-orientation occurred resulting in an iron based aluminate (FeAl 2 O 4 ) with discrete metallic copper present. FeAl 2 O 4 was further depleted of oxygen to metallic Fe and alumina. The multistep process was emulated through the use of a multi-interface Grainy pellet model. To add to the utility of the model, the effects of product gas, CO 2 , on the reaction progression were incorporated into the description. In addition, the catalytic effects of the Boudouard reaction were examined and incorporated into the representation adding to the novelty of the work.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Utilizing genome-scale models to optimize nutrient supply for sustained algal growth and lipid productivity

Nutrient availability is critical for growth of algae and other microbes used for generating valuable biochemical products. Determining the optimal levels of nutrient supplies to cultures can eliminate feeding of excess nutrients, lowering production costs and reducing nutrient pollution into the environment. With the advent of omics and bioinformatics methods, it is now possible to construct genome-scale models that accurately describe the metabolism of microorganisms. In this study, a genome-scale model of the green alga Chlorella vulgaris (iCZ946) was applied to predict feeding of multiple nutrients, including nitrate and glucose, under both autotrophic and heterotrophic conditions. The objective function was changed from optimizing growth to instead minimizing nitrate and glucose uptake rates, enabling predictions of feed rates for these nutrients. The metabolic model control (MMC) algorithm was validated for autotrophic growth, saving 18% nitrate while sustaining algal growth. Additionally, we obtained similar growth profiles by simultaneously controlling glucose and nitrate supplies under heterotrophic conditions for both high and low levels of glucose and nitrate. Finally, the nitrate supply was controlled in order to retain protein and chlorophyll synthesis, albeit at a lower rate, under nitrogen-limiting conditions. This model-driven cultivation strategy doubled the total volumetric yield of biomass, increased fatty acid methyl ester (FAME) yield by 61%, and enhanced lutein yield nearly 3 fold compared to nitrogen starvation. This study introduces a control methodology that integrates omics data and genome-scale models in order to optimize nutrient supplies based on the metabolic state of algal cells in different nutrient environments. This approach could transform bioprocessing control into a systems biology-based paradigm suitable for a wide range of species in order to limit nutrient inputs, reduce processing costs, and optimize biomanufacturing for the next generation of desirable biotechnology products.

59 BASIC BIOLOGICAL SCIENCES↗

Do genome-scale models need exact solvers or clearer standards?

Constraint-based analysis of genome-scale models (GEMs) arose shortly after the first genome sequences became available. As numerous reviews of the field show, this approach and methodology has proven to be successful in studying a wide range of biological phenomena (McCloskey et al, 2013; Bordbar et al, 2014). However, efforts to expand the user base are impeded by hurdles in correctly formulating these problems to obtain numerical solutions. In particular, in a study entitled “An exact arithmetic toolbox for a consistent and reproducible structural analysis of metabolic network models” (Chindelevitch et al, 2014), the authors apply an exact solver to 88 genome-scale constraint-based models of metabolism. The authors claim that COBRA calculations (Orth et al, 2010) are inconsistent with their results and that many published and actively used (Lee et al, 2007; McCloskey et al, 2013) genome-scale models do support cellular growth in existing studies only because of numerical errors. They base these broad claims on two observations: (i) three reconstructions ( i AF1260, i IT341, and i NJ661) compute feasibly in COBRA, but are infeasible when exact numerical algorithms are used by their software (entitled MONGOOSE); (ii) linear programs generated by MONGOOSE for i IT341 were submitted to the NEOS Server (a Web site that runs linear programs through various solvers) and gave inconsistent results. They further claim that a large percentage of these COBRA models are actually unable to produce biomass flux. Here, we demonstrate that the claims made by Chindelevitch et al (2014) stem from an incorrect parsing of models from files rather than actual problems with numerical error or COBRA computations.

59 BASIC BIOLOGICAL SCIENCES↗

Two-scale model for the effect of physical aging in elastomers filled with hard nanoparticles

A two-scale model is developed, and solved numerically, to describe the mechanical behavior of elastomers filled with hard nanoparticles. Of particular interest is the slow recovery of the elastic modulus after large-amplitude oscillatory deformation. To account for this effect, the physical aging of the glassy bridges between the filler particles is captured with two thermal degrees of freedom for the matrix material, namely a kinetic and a configurational one. Formulating the two-scale model enriched with aging in a nonequilibrium thermodynamics context, first results in a constitutive relation for the Cauchy stress tensor. Second, the dynamics of physical aging is described, which eventually results in the slow recovery of the elastic modulus with waiting time. The proposed model is investigated numerically under large amplitude oscillatory shear deformation. Of particular interest in this respect is the coupling of the micro-scale dynamics with the physical aging on the macroscopic scale. This coupling is examined in detail, both in an approximate way using a Gaussian approximation, as well as numerically, under specific conditions. It turns out that the CONNFFESSIT approach (Laso and Öttinger 1993 ) can not be employed for the numerical solution of the model under arbitrary loading conditions because of the novel structure of the two-level coupling term. While a procedure for solving the model numerically for the case of strong applied deformation is presented in this paper, other solution methodologies need to be sought for the cases of weak and no applied deformation.

36 MATERIALS SCIENCE↗

Non-Boussinesq subgrid-scale model with dynamic tensorial coefficients

A major drawback of Boussinesq-type subgrid-scale stress models used in large-eddy simulations is the inherent assumption of alignment between large-scale strain rates and filtered subgrid-stresses. A priori analyses using direct numerical simulation (DNS) data have shown that this assumption is invalid locally as subgrid-scale stresses are poorly correlated with the large-scale strain rates [J. Bardina, J. Ferziger, and W. Reynolds, Improved subgrid-scale models for large-eddy simulation, in Proceedings of the 13th Fluid and Plasmadynamics Conference, AIAA (1980); C. Meneveau and K. Katz, Scale-invariance and turbulence models for large-eddy simulation, Ann. Rev. Fluid Mech. 32, 1 (2000)]. In the present work, a new, non-Boussinesq subgrid-scale model is presented where the model coefficients are computed dynamically. Some previous non-Boussinesq models have observed issues in providing adequate dissipation of turbulent kinetic energy [e.g., Bardina et al., Proceedings of the 13th Fluid and Plasmadynamics Conference (1980); R. A. Clark, J. Ferziger, and W.C. Reynolds. Evaluation of subgrid-scale models using an accurately simulated turbulent flow, J. Fluid Mech. 91, 1 (1979); S. Stolz and N. A. Adams, An approximate deconvolution procedure for large-eddy simulation, Phys. Fluids 11, 1699 (1999)]; however, the present model is shown to provide sufficient dissipation using dynamic coefficients. Modeled subgrid-scale Reynolds stresses satisfy the consistency requirements of the governing equations for large-eddy simulation (LES), vanish in laminar flow and at solid boundaries, and have the correct asymptotic behavior in the near-wall region of a turbulent boundary layer. The new model, referred to as the dynamic tensor-coefficient Smagorinsky model (DTCSM), has been tested in simulations of canonical flows: decaying and forced homogeneous isotropic turbulence, and wall-modeled turbulent channel flow at high Reynolds numbers. The results show favorable agreement with DNS data. It has been shown that DTCSM offers similar predictive capabilities as the dynamic Smagorinsky model for canonical flows. In order to assess the performance of DTCSM in more complex flows, wall-modeled simulations of high Reynolds number flow over a Gaussian bump (Boeing speed bump) exhibiting smooth-body flow separation are performed. Predictions of surface pressure and skin friction, compared against DNS and experimental data, show improved accuracy from DTCSM in comparison to existing static coefficient (Vreman) and dynamic Smagorinsky model. The computational cost of performing LES with this model is up to 15% higher than the dynamic Smagorinsky model.

42 ENGINEERING↗

Development of a Scale Model for High Flux Isotope Reactor Cycle 400

The development of a comprehensive SCALE computational model for the High Flux Isotope Reactor (HFIR) is documented and discussed in this report. The SCALE model has equivalent features and functionality as the reference MCNP model for Cycle 400 that has been used extensively for HFIR safety analyses and for HFIR experiment design and analyses. Numerical comparisons of the SCALE and MCNP models for the multiplication constant, power density distribution in the fuel, and neutron fluxes at several locations in HFIR indicate excellent agreement between the results predicted with the two models. The SCALE HFIR model is presented in sufficient detail to provide the users of the model with a tool that can be easily customized for various safety analysis or experiment design requirements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Evaluating and Improving Cloud Processes in the Multi-Scale Modeling Framework

The research performed under this grant was intended to improve the embedded cloud model in the Multi-scale Modeling Framework (MMF) for convective clouds by using a 2-moment microphysics scheme rather than the single moment scheme used in all the MMF runs to date. The technical report and associated documents describe the results of testing the cloud resolving model with fixed boundary conditions and evaluation of model results with data. The overarching conclusion is that such model evaluations are problematic because errors in the forcing fields control the results so strongly that variations in parameterization values cannot be usefully constrained

54 ENVIRONMENTAL SCIENCES↗