Multiscale modeling of CO2-induced carbonate dissolution: From core to meter scale
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58 GEOSCIENCES↗
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Results for “Multiscale simulations”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Hydrological Controls on Riverbed Methane Emissions: A Numerical Investigation of Hydrodynamic and Ebullitive Mechanisms from Site to Basin Scales
Methane production and emission from riverbed sediments constitute a significant yet underexplored component of the river methane budget. Despite their importance, a mechanistic and quantitative understanding of these processes under dynamic flow conditions remains elusive, particularly at the basin scale. In this study, we investigate the multiscale (site-to-basin) mechanisms governing methane emissions from riverbeds, focusing on the interplay between biogeochemical processes and hydrological dynamics. We developed a reactive transport model that integrates methane production with hydrodynamic and ebullitive pathways and coupled it with a basin-scale groundwater flow model to simulate methane emissions across scales. By incorporating key factors such as vertical hydrological exchange flow (VHEF), particulate organic carbon availability, sediment properties, and temperature sensitivity, our model captures the spatiotemporal variability of methane ebullition at both the site and basin scales. Our results reveal that methane ebullition is strongly modulated by VHEF, with lower flow rates promoting methane accumulation and subsequent ebullition. Sensitivity analyses underscore nonlinear responses of methane fluxes to environmental drivers. Furthermore, these findings emphasize the critical roles of sediment composition, hydrological exchange, and environmental conditions in shaping methane dynamics. Overall, this work advances our understanding of riverine methane emissions and offers insights for guiding climate models and mitigation strategies.
Fluxes↗
Continuum- and particle-based modeling of shapes and dynamics of red blood cells in health and disease
Here, we review recent advances in multiscale modeling of the mechanics of healthy and diseased red blood cells (RBCs), and blood flow in the microcirculation. We cover the traditional continuum-based methods but also particle-based methods used to model both the RBCs and the blood plasma. We highlight examples of successful simulations of blood flow including malaria and sickle cell anemia.
59 BASIC BIOLOGICAL SCIENCES↗
The Method of Finite Averages
The Method of Finite Averages (MoFA) is a rigorous multiscale modeling methodology for efficiently modeling multi-physical phenomena in heterogeneous porous media. The code developed in this project aims to perform the numerical calculations required to formulate, implement, and verify MoFA models for Earth and Energy systems (i.e., model verification refers to performing fully-resolved simulations of the systems and comparing their results to those of the models). In general, MoFA transforms partial differential equations (PDEs) describing the fine-scale physics of a system into coupled ordinary differential equations (ODEs)---in time---that describe the coarse-scale---or "average"---physical behaviors of the system. This transformation significantly expedites system simulation, as the coarse-scale ODEs involve vastly fewer degrees of freedom than the fine-scale PDEs. The code developed under this project will allow users to 1.) generate system geometries and numerical meshes, 2.) solve the PDE and ODE systems required for MoFA model formulation and implementation, 3.) solve the PDE systems required to obtain fully-resolved simulation results for model verification, and 4.) compare and plot results (e.g., the model and fully-resolved simulation solutions, the error between the solutions, etc.).
Pietrzyk, KyleM [Lawrence Livermore National Labor↗
Nanosecond Laser Drying in Wafer Foundries for Significant Energy Efficiency Improvement
Surface drying is a critical process in microelectronics wafer fabrication. In order to reduce and eliminate watermarks, many surface drying processes have been studied and used. Most of the wafer foundries currently use drying processes based on Isopropyl Alcohol (IPA), which causes serious safety (fire), health, environmental, and energy efficiency issues. The long-term goal of this project is to develop a fast, effective, chemical-free, and extremely energy efficient wafer drying technology that employs nanosecond laser-induced sub-surface evaporation and explosion. The objectives of this project are to 1) experimentally develop and verify the laser surface drying method, explore and identify how and to what extent various physical parameters influence the drying efficiency and effectiveness; and 2) understand and optimize the underlying thermodynamics in the proposed laser surface drying, including micro/nanoscale sub-surface superheating, evaporation, explosion, and photo/thermochemical bond breaking via atomistic modeling and experimental characterization. Toward these objectives, five tasks have been accomplished successfully, including 1) develop in-lab laser surface drying setup and study the effect of varied laser parameters, 2) use multiscale hybrid-modeling to study and understand the physics of water behavior during drying toward process optimization, 3) investigate the effect of drying conditions on the drying effectiveness, 4) develop a large-scale laser drying scanning system with automatic scanning, and 5) conduct large-scale simulation to study the effect of dopant level and develop strategies for system development toward industry deployment.
42 ENGINEERING↗
Stochastic behavior of nanoscale dielectric wall buckling
The random buckling patterns of nanoscale dielectric walls are analyzed using a nonlinear multi-scale stochastic method that combines experimental measurements with simulations. The dielectric walls, approximately 200 nm tall and 20 nm wide, consist of compliant, low dielectric constant (low-k) fins capped with stiff, compressively stressed TiN lines that provide the driving force for buckling. The deflections of the buckled lines exhibit sinusoidal pseudoperiodicity with amplitude fluctuation and phase decorrelation arising from stochastic variations in wall geometry, properties, and stress state at length scales shorter than the characteristic deflection wavelength of about 1000 nm. The buckling patterns are analyzed and modeled at two length scales: a longer scale (up to 5000 nm) that treats randomness as a longer-scale measurable quantity, and a shorter-scale (down to 20 nm) that treats buckling as a deterministic phenomenon. Statistical simulation is used to join the two length scales. Through this approach, the buckling model is validated and material properties and stress states are inferred. In particular, the stress state of TiN lines in three different systems is determined, along with the elastic moduli of low-k fins and the amplitudes of the small-scale random fluctuations in wall properties—all in the as-processed state. The important case of stochastic effects giving rise to buckling in a deterministically sub-critical buckling state is demonstrated. The nonlinear multiscale stochastic analysis provides guidance for design of low-k structures with acceptable buckling behavior and serves as a template for how randomness that is common to nanoscale phenomena might be measured and analyzed in other contexts.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Multiscale topology optimization using neural network surrogate models
In this study, we are concerned with optimization of macroscale elastic structures that are designed utilizing spatially varying microscale metamaterials. The macroscale optimization is accomplished using gradient-based nonlinear topological optimization. But instead of using density as the optimization decision variable, the decision variables are the multiple parameters that define the local microscale metamaterial. This is accomplished using single layer feedforward Gaussian basis function networks as a surrogate models of the elastic response of the microscale metamaterial. The surrogate models are trained using highly resolved continuum finite element simulations of the microscale metamaterials and hence are significantly more accurate than analytical models e.g. classical beam theory. Because the derivative of the surrogate model is important for sensitivity analysis of the macroscale topology optimization, a neural network training procedure based on the Sobolev norm is described. Since the SIMP method is not appropriate for spatially varying lattices, an alternative method is developed to enable creation of void regions. Lastly, the efficacy of this approach is demonstrated via several examples in which the optimal graded metamaterial outperforms a traditional solid structure.
42 ENGINEERING↗
Multiscale modeling of fission gas behavior in U 3 Si 2 under LWR conditions
In this work, we present a model of fission gas behavior in U 3 Si 2 under light water reactor (LWR) conditions for application in engineering fuel performance codes. The model includes components for intra-granular and inter-granular behavior of fission gases. The intra-granular component is based on cluster dynamics and computes the evolution of intra-granular fission gas bubbles and swelling coupled to gas diffusion to grain boundaries. The inter-granular component describes the evolution of grain-boundary fission gas bubbles coupled to fission gas release. Given the lack of experimental data for U 3 Si 2 under LWR conditions, the model is informed with parameters calculated via atomistic simulations. In particular, we derive fission gas diffusivities through density functional theory calculations, and the re-solution rate of fission gas atoms from intra-granular bubbles through binary collision approximation calculations. Further, the developed model is applied to the simulation of an experiment for U 3 Si 2 irradiated under LWR conditions available from the literature. Results point out a credible representation of fission gas swelling and release in U 3 Si 2 . Finally, we perform a sensitivity analysis for the various model parameters. Based on the sensitivity analysis, indications are derived that can help in addressing future research on the characterization of the physical parameters relative to fission gas behavior in U 3 Si 2 . The developed model is intended to provide a suitable infrastructure for the engineering scale calculation of fission gas behavior in U 3 Si 2 that exploits a multiscale approach to fill the experimental data gap and can be progressively improved as new lower-length scale calculations and validation data become available.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Tailoring ductile-phase toughened tungsten hierarchical microstructures for plasma-facing materials
Biological materials, such as bones, nacre, etc., have been found to show attractive and unique combinations of stiffness, strength and fracture toughness. Research has been conducted in various engineering areas to mimic the naturally hierarchical microstructures or nanostructures of these materials to produce materials with optimum stiffness, high strength and fracture toughness for their intended structural applications. In the same objective, this work applies a multiscale microstructural approach recently developed to investigate the deformation and fracture behavior of ductile phase toughened tungsten (W) materials such as tungsten-nickel/iron (W-Ni/Fe) composites that possess lamellar-like and hierarchical “brick-and-mortar” (BAM) microstructures. First, the approach is used to simulate tensile loading of W-Ni/Fe specimens cut out from hot-rolled W-Ni/Fe plates which possess lamellar-like microstructures. The finite element model of the gage section of the specimen consists of a W-Ni/Fe dual-phase microstructural domain in which the constitutive behaviors of W and Ni/Fe phases are described by an elastic-plastic damage model. The predicted material stress-strain response and crack pattern development as a function of loading are then compared to the corresponding experimental results to determine the constitutive model parameters for W and Ni/Fe. Subsequently, the model parameters are used to analyze W-Ni/Fe BAM microstructures that are artificially created to investigate the effects of microstructural features and morphologies on the composite stress-strain response, damage, and fracture patterns. The modeling shows that regular BAM microstructures that experience bridging mechanism combined with crack penetration across W-phase regions exhibit significantly higher strengths than the rather random lamellar-like microstructures. More significantly, however adjusting the brick’s length-to-height ratio, the BAM microstructure can be designed to allow a more distributed damage zone which leads to increased strength, ductility and fracture energy.
36 MATERIALS SCIENCE↗
Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems
Abstract Predicting complex dynamics in physical applications governed by partial differential equations in real-time is nearly impossible with traditional numerical simulations due to high computational cost. Neural operators offer a solution by approximating mappings between infinite-dimensional Banach spaces, yet their performance degrades with system size and complexity. We propose an approach for learning neural operators in latent spaces, facilitating real-time predictions for highly nonlinear and multiscale systems on high-dimensional domains. Our method utilizes the deep operator network architecture on a low-dimensional latent space to efficiently approximate underlying operators. Demonstrations on material fracture, fluid flow prediction, and climate modeling highlight superior prediction accuracy and computational efficiency compared to existing methods. Notably, our approach enables approximating large-scale atmospheric flows with millions of degrees, enhancing weather and climate forecasts. Here we show that the proposed approach enables real-time predictions that can facilitate decision-making for a wide range of applications in science and engineering.
97 MATHEMATICS AND COMPUTING↗
QM/MM investigation of the concentration effects on the second-order nonlinear optical responses of solutions
A multiscale approach combining quantum mechanics (QM) and molecular mechanics methods has been employed to investigate the effects of solute-solute interactions and therefore of concentration on the first hyperpolarizability of solutions of nitrobenzene in benzene. First, spatial distributions of solute and solvent molecules are generated using Monte Carlo simulations where the intermolecular interactions are described using the Lennard-Jones potentials and Coulomb terms. Then, a reduced number of statistically-uncorrelated configurations are sampled and submitted to time-dependent Hartree-Fock calculations of the first hyperpolarizability. When only one molecule is described quantum-mechanically and is embedded in the electrostatic polarization field of the solution described by point charges, β{sub HRS} and β{sub //} as well as the depolarization ratio increase in parallel with the concentration in nitrobenzene. This effect is attributed to the increase of the polarization field associated with the presence of polar nitrobenzene molecules in the surrounding. Then, the first solvation shell is considered explicitly in the QM calculation to address solute-solute interactions effects. When the number of nitrobenzenes in the first solvation shell increases, β{sub HRS} and β{sub //} normalized to the number of nitrobenzene molecules decrease and this decrease attains roughly 50% when there are 3 nitrobenzene molecules in the first solvation shell. These drastic reductions of the first hyperpolarizability result from (partial) centro-symmetric arrangements between the nitrobenzene molecules, as supported by the relationship between β and the angle between the nitrobenzene charge transfer axes. Moreover, these β decreases originate mostly from the reduction of the dipolar β component, whereas the octupolar one is rather constant as a function of the nitrobenzene concentration.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Multiscale dynamics of reactive fronts in the subsurface
1. Brief summary of progress to date. Major Goals of the Project. Overreaching goals of the proposed activity are to develop an or- ganizing framework to describe nonlinear reactive transport in geologic systems over many length and time scales, and corresponding physics-based adaptive multi-scale hybrid models. We will also provide computational tools for robust uncertainty quantification in hybrid simulations. Major Activities of the Project. The major activities in this reporting period have focused on developing a time-averaging framework for ADR transport (Task 1) and global diagnosis criteria for spatio-temporal algorithm refinement (Task 2), as well as numerical validation and verification of the analytical approaches developed. The main activities are as follows: (a) We use homogenization theory to perform a spatio-temporal upscaling of pore-scale advection- diffusion equation in a periodic porous medium in the presence of fluctuating boundary conditions on some parts of the boundary and nonlinear chemical reaction on the solid-liquid interface and we investigate the constraints under which the macroscopic equation gives an accurate explanation of the underlying physics at the pore scale. We demonstrate that the dynamics at the continuum scale is strongly influenced by the interplay between signal frequency at the boundary and transport processes at the pore level. Furthermore, we show that by choosing appropriate scaling factors, a homogenized equation along with expressions for the effective coefficients reliably describe the concentration of solute at the length and time scales vastly different from physically robust micro-scale provided that some specific scale separation constraints are met. Our analysis proves that if the reaction rate or advection at the micro-scale are large, the effectiveness of the homogenized model is impeded. (b) We test numerically the conditions derived theoretically for advective-diffusive and reactive trans- port in a fracture with planar walls subject to temporally oscillating Dirichlet boundary conditions. The numerical analysis confirms the theoretical predictions. Significant Results. Two paper are in preparation. 2. Description of work yet to be accomplished The Tasks yet to be accomplished are listed below: (a) Quantify the impact of uncertainty in wall geometry of planar fractures on predictions hybrids of ARD transport (b) Develop coupling conditions for time hybridzation (c) Quantify the impact of uncertainty in pore geometry on predictions of hybrids of ARD transport in porous media, i.e. develop stochastic hybrid models (d) Use the hybrids combined with X-Ray tomographic images of pore scale structure (from Dr. Gouze, see letter of collaboration) to model dynamic changes in porosity/permeability
42 ENGINEERING↗
Large Scale DD Simulation Results for Crystal Plasticity Parameters in Fe-Cr And Fe-Ni Systems
The development of viable nuclear energy source depends on ensuring structural materials integrity. Structural materials in nuclear reactors will operate in harsh radiation conditions coupled with high level hydrogen and helium production, as well as formation of high density of point defects and defect clusters, and thus will experience severe degradation of mechanical properties. Therefore, the main objective of this work is to develop a capability that predicts aging behavior and in-service lifetime of nuclear reactor components and, thus provide an instrumental tool for tailoring materials design and development for application in future nuclear reactor technologies. Towards this end goal, the long term effort is to develop a physically based multiscale modeling hierarchy, validated and verified, to address outstanding questions regarding the effects of irradiation on materials microstructure and mechanical properties during extended service in the fission and fusion environments. The focus of the current investigation is on modern steels for use in nuclear reactors including high strength ferritic-martensitic steels (Fe-Cr-Ni alloys). The effort is to develop a predicative capability for the influence of irradiation on mechanical behavior. Irradiation hardening is related to structural information crossing different length scales, such as composition, dislocation, and crystal orientation distribution. To predict effective hardening, the influence factors along different length scales should be considered. Therefore, a hierarchical upscaling methodology is implemented in this work in which relevant information is passed between models at three scales, namely, from molecular dynamics to dislocation dynamics to dislocation-based crystal plasticity. The molecular dynamics (MD) was used to predict the dislocation mobility in body centered cubic (bcc) Fe and its Ni and Cr alloys. The results are then passed on to dislocation dynamics to predict the critical resolved shear stress (CRSS) from the evolution of local dislocation and defects. In this report the focus is on the results obtained from large scale dislocation dynamics simulations. The effect of defect density, materials structure was investigated, and evolution laws are obtained. These results will form the bases for the development of evolution and hardening laws for a dislocation-based crystal plasticity framework. The hierarchical upscaling method being developed in this project can provide a guidance tool to evaluate performance of structural materials for next-generation nuclear reactors. Combined with other tools developed in the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the models developed will have more impact in improving the reliability of current reactors and affordability of new reactors.
36 MATERIALS SCIENCE↗
The self-assembly of particles with isotropic interactions: Using DNA coated colloids to create designer nanomaterials
Self-consistent field theory equations are presented that are suitable for use as a coarse-grained model for DNA coated colloids, polymer-grafted nanoparticles and other systems with approximately isotropic interactions. The equations are generalized for arbitrary numbers of chemically distinct colloids. The advantages and limitations of such a coarse-grained approach for DNA coated colloids are discussed, as are similarities with block copolymer self-assembly. In particular, preliminary results for three species self-assembly are presented that parallel results from a two dimensional ABC triblock copolymer phase. The possibility of incorporating crystallization, dynamics, inverse statistical mechanics and multiscale modelling techniques are discussed.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Multiscale Studies of the Formation and Stability of Surface-based Nanostructures, DOE Computational Materials Science Network - Final Report
Summary of work performed under DOE-CMSN/FG0205ER46227, Multiscale Studies of the Formation and Stability of Surface-based Nanostructures, listing publications, collaborations, and presentations.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Development of Composite Photocatalyst Materials that are Highly Selective for Solar Hydrogen Production and their Evaluation in Z-Scheme Reactor Designs
The key technology gap preventing a vertically stacked dual-bed particle suspension reactor from achieving the DOE MYRD&D ultimate cost target for H 2 production remains the lack of materials in particle form factor that exhibit ≥10% solar-to-H 2 energy conversion (STH) efficiency as a suspension. Therefore, our project goals centered around strategies to increase the STH efficiency by enhancing photophysical properties of perovskite oxide particles including increased visible-light absorption, increased selectivity for electrocatalysis of the H 2 evolution reaction (HER) and the O 2 evolution reaction (OER) through development of ultrathin oxide coatings, correlating composition and structure to function, and improving understanding of multiscale transport and kinetic processes.
08 HYDROGEN↗
Exascale Co-design for Modeling Materials in Extreme Environments
Computational materials science has provided great insight into the response of materials under extreme conditions that are difficult to probe experimentally. For example, shock-induced plasticity and phase transformation processes in single-crystal and nanocrystalline metals have been widely studied via large-scale molecular dynamics simulations, and many of these predictions are beginning to be tested at advanced 4th generation light sources such as the Advanced Photon Source (APS) and Linac Coherent Light Source (LCLS). I will describe our simulation predictions and their recent verification at LCLS, outstanding challenges in modeling the response of materials to extreme mechanical and radiation environments, and our efforts to tackle these as part of the multi-institutional, multi-disciplinary Exascale Co-design Center for Materials in Extreme Environments (ExMatEx). ExMatEx has initiated an early and deep collaboration between domain (computational materials) scientists, applied mathematicians, computer scientists, and hardware architects, in order to establish the relationships between algorithms, software stacks, and architectures needed to enable exascale-ready materials science application codes within the next decade. We anticipate that we will be able to exploit hierarchical, heterogeneous architectures to achieve more realistic large-scale simulations with adaptive physics refinement, and are using tractable application scale-bridging proxy application testbeds to assess new approaches and requirements. Such current scale-bridging strategies accumulate (or recompute) a distributed response database from fine-scale calculations, in a top-down rather than bottom-up multiscale approach.
36 MATERIALS SCIENCE↗
Multiscale Investigation of Thermal Fluctuations on Solar-Energy Conversion
Photoinduced charge transfer (CT) plays a central role in biologically significant systems and in applications that harvest solar energy. We investigate the relationship of CT kinetics and conformation in a molecular triad. The triad, consisting of carotenoid, porphyrin, and fullerene is structurally flexible and able to acquire significantly varied conformations under ambient conditions. With an integrated approach of quantum calculations and molecular dynamics simulations, we compute the rate of CT at two distinctive conformations. The linearly extended conformation, in which the donor (carotenoid) and the acceptor (fullerene) are separated by nearly 50 Å, enables charge separation through a sequential CT process. A representative bent conformation that is entropically dominant, however, attenuates the CT, although the donor and the acceptor are spatially closer. Our computed rate of CT at the linear conformation is in good agreement with measured values. Our work provides unique fundamental understanding of the photoinduced CT process in the molecular triad.
30 DIRECT ENERGY CONVERSION↗