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Results for “multiscale processes”

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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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Comparison of Magnetospheric Multiscale Ion Jet Signatures with Predicted Reconnection Site Locations at the Magnetopause

Magnetic reconnection at the Earths magnetopause is the primary process by which solar wind plasma and energy gains access to the magnetosphere. One indication that magnetic reconnection is occurring is the observation of accelerated plasma as a jet tangential to the magnetopause. The direction of ion jets along the magnetopause surface as observed by the Fast Plasma Instrument (FPI) and the Hot Plasma Composition Analyzer (HPCA) instrument on board the recently launched Magnetospheric Multiscale (MMS) set of spacecraft is examined. For those cases where ion jets are clearly discerned, the direction of origin compares well statistically with the predicted location of magnetic reconnection using convected solar wind observations in conjunction with the Maximum Magnetic Shear model.

Petrinec, S. M.↗
DOE OSTI2024

Adaptive tau-leaping methods for microscopic-lattice kinetic Monte Carlo simulations

Traditional Kinetic Monte Carlo (KMC) approaches, rooted in Gillespie’s stochastic simulation algorithm, become computationally demanding in systems with a large range of timescales. The goal of this work is to propose and study new adaptive lattice-KMC time integration strategies for spatially non-uniform systems. To that end, two novel adaptive tau-leaping methods and their corresponding time integration strategies are developed based on the idea of the “n-fold” direct KMC method. These strategies allow for the simultaneous execution of multiple reactions, advancing time by adaptively selected coarse increments. We present numerical experiments comparing the proposed methods with existing approaches in a catalytic surface kinetics application involving ammonia decomposition.

Bimolecular reactions↗
DOE OSTI2025

Time-resolved tracking of cellulose biosynthesis and assembly during cell wall regeneration in live Arabidopsis protoplasts

Cellulose, the most abundant polysaccharide on earth composing plant cell walls, is synthesized by coordinated action of multiple enzymes in cellulose synthase complexes embedded within the plasma membrane. Multiple chains of cellulose fibrils form intertwined extracellular matrix networks. It remains largely unknown how newly synthesized cellulose is assembled into an intricate fibril network on cell surfaces. Here, we have established an in vivo time-resolved imaging platform to continuously visualize cellulose biosynthesis and fibril network assembly onArabidopsis thalianaprotoplast surfaces as the primary cell wall regenerates. Our observations provide the basis for a model of cellulose fibril network development in protoplasts driven by an interplay of multiscale dynamics that includes rapid diffusion and coalescence of nascent cellulose fibrils, processive elongation of single fibrils, and cellulose fibrillar network rearrangement during maturation. This study provides fresh insights into the dynamic and mechanistic aspects of cell wall synthesis at the single-cell level.

Science & Technology - Other Topics↗
NASA NTRS1997

Advanced Modeling Techniques to Study Anthropogenic Influences on Atmospheric Chemical Budgets

This research work is a collaborative effort between research groups at MCNC and the University of North Carolina at Chapel Hill. The overall objective of this research is to improve the level of understanding of the processes that determine the budgets of chemically and radiatively active compounds in the atmosphere through development and application of advanced methods for calculating the chemical change in atmospheric models. The research performed during the second year of this project focused on four major aspects: (1) The continued development and refinement of multiscale modeling techniques to address the issue of the disparate scales of the physico-chemical processes that govern the fate of atmospheric pollutants; (2) Development and application of analysis methods utilizing process and mass balance techniques to increase the interpretive powers of atmospheric models and to aid in complementary analysis of model predictions and observations; (3) Development of meteorological and emission inputs for initial application of the chemistry/transport model over the north Atlantic region; and, (4) The continued development and implementation of a totally new adaptive chemistry representation that changes the details of what is represented as the underlying conditions change.

Mathur, Rohit↗
NASA NTRS2021

Magnetospheric Multiscale Observations of an Expanding Oxygen Wave in Magnetic Reconnection

Heavier plasma species such as oxygen ions can have a large impact on the magnetic reconnection process. It has been hypothesized that the acceleration of demagnetized oxygen ions by the Hall electric field will lead to the formation of an oxygen wave that expands into the exhaust. By comparing data from NASA's Magnetospheric Multiscale mission to a fully kinetic particle-in-cell simulation, we can for the first time provide observational evidence of such an expanding oxygen wave. The wave is characterized by an oxygen jet consisting of cold ions directed toward the neutral sheet associated with a density cavity. This density cavity forms as the EO are subject to collective acceleration by the Hall electric field leaving behind a region of low-density oxygen ions. Our results are important for the understanding of the role and effect of oxygen ions in magnetic reconnection.

Hakon Midthun Kolsto↗
NASA NTRS2011

Modeling and Characterization of Damage Processes in Metallic Materials

This paper describes a broad effort that is aimed at understanding the fundamental mechanisms of crack growth and using that understanding as a basis for designing materials and enabling predictions of fracture in materials and structures that have small characteristic dimensions. This area of research, herein referred to as Damage Science, emphasizes the length scale regimes of the nanoscale and the microscale for which analysis and characterization tools are being developed to predict the formation, propagation, and interaction of fundamental damage mechanisms. Examination of nanoscale processes requires atomistic and discrete dislocation plasticity simulations, while microscale processes can be examined using strain gradient plasticity, crystal plasticity and microstructure modeling methods. Concurrent and sequential multiscale modeling methods are being developed to analytically bridge between these length scales. Experimental methods for characterization and quantification of near-crack tip damage are also being developed. This paper focuses on several new methodologies in these areas and their application to understanding damage processes in polycrystalline metals. On-going and potential applications are also discussed.

Glaessgen, E. H.↗
DOE OSTI2024

Approaches for the Simulation of Coupled Processes in Evolving Fractured Porous Media Enabled by Exascale Computing

Models have historically represented fractured porous media with continuum descriptions that characterize the media using bulk parameters. The impact of small-scale features is not captured in these models, although they may be controlling the performance of subsurface applications. Pore-scale models can simulate processes in small-scale features by representing the pore space geometry explicitly but are computationally expensive for large domains. The alternative multiscale approach entails the combination of pore-scale and continuum-scale descriptions in a single framework. We use Chombo-Crunch, a computational capability that discretizes complex geometries with an adaptive, embedded boundary method to contrast these two approaches. Chombo-Crunch takes advantage of recent computational performance and memory bandwidth improvements resulting from the emergence of exascale computing resources. These combined improvements enable the efficient simulation of reactive transport in fractured media with a high degree of fidelity and the ability to capture the control small-scale processes exert on the overall medium evolution.

42 ENGINEERING↗
DOE OSTI2025

WigglyRivers: A tool to characterize the multiscale nature of meandering channels

Channel sinuosity is ubiquitous along river networks, producing complex patterns that encapsulate and influence morphodynamic processes and ecosystem services. Accurately characterizing these patterns is challenging with traditional curvature-based algorithms. Here, in this study, we present WigglyRivers, a Python package that builds on existing wavelet-based methods to create an unsupervised meander identification and characterization tool. The package uses planimetric information the user provides or from the USGS’s High-Resolution National Hydrography Dataset to characterize individual reaches or entire river networks. WigglyRivers also includes a supervised river identification tool for manually selecting individual meandering features. Here, we provide examples of idealized river transects and show the capabilities of WigglyRivers. We also use the supervised identification tool to validate the unsupervised identification on river transects across the continental US. WigglyRivers is a tool to understand better the multiscale characteristics of river networks and the link between river geomorphology and river corridor connectivity.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2021

Particle Acceleration by Dense Impulsive Structures Moving in Ambient Magnetospheric Plasma. 3-D Hybrid Kinetic Modeling and MMS Observations

High resolution observations of dense plasma impulsive structures moving through an ambient background magnetospheric flows were captured by the Magnetospheric Multiscale mission. The observations show particle heating and acceleration, shock-like wave formation, and whistler wave excitation inside the interface between the dense impulsive plasma structures and the ambient plasma. A multiscale hybrid kinetic simulation provides an explanation of the observed wave-particle interactions with the assumption that the dense plasma structures may be represented by plasma clouds which are formed at the magnetopause layer due to reconnection processes. Plain Language Summary: Dense, impulsive plasma structures moving through a background plasma were captured by the NASA Magnetospheric Multiscale mission. The observations show that the dense structures can generate strong perturbations in the electromagnetic field and shock-like waves. Interactions between these electromagnetic waves and the particles results in particle acceleration. 3-D hybrid kinetic modeling (particle description for ions and fluid description for electrons) was used to investigate the plasma physics of the observed structures. It was assumed that the plasma clouds were formed by magnetic field reconnection inside the magnetopause, which is the interface between the solar wind particles and the cold low-density magnetospheric plasma. The work helps us understand the plasma environment at the interface between the Earth and solar wind, near planetary moons, within astrophysical explosions, and possibly at the interface between the solar wind and local interstellar medium.

A. S. Lipatov↗
DOE OSTI2025

Gaussian Process Regression under Computational and Epistemic Misspecification

Gaussian process regression is a classical kernel method for function estimation and data interpolation. In large data applications, computational costs can be reduced using low-rank or sparse approximations of the kernel. This paper investigates the effect of such kernel approximations on the interpolation error. We introduce a unified framework to analyze Gaussian process regression under important classes of computational misspecification: Karhunen-Loève expansions that result in low-rank kernel approximations, multiscale wavelet expansions that induce sparsity in the covariance matrix, and finite element representations that induce sparsity in the precision matrix. Furthermore, our theory also accounts for epistemic misspecification in the choice of kernel parameters.

Gaussian process regression↗
NASA NTRS2004

Modeling Images of Natural 3D Surfaces: Overview and Potential Applications

Generative models of natural images have long been used in computer vision. However, since they only describe the of 2D scenes, they fail to capture all the properties of the underlying 3D world. Even though such models are sufficient for many vision tasks a 3D scene model is when it comes to inferring a 3D object or its characteristics. In this paper, we present such a generative model, incorporating both a multiscale surface prior model for surface geometry and reflectance, and an image formation process model based on realistic rendering, the computation of the posterior model parameter densities, and on the critical aspects of the rendering. We also how to efficiently invert the model within a Bayesian framework. We present a few potential applications, such as asteroid modeling and Planetary topography recovery, illustrated by promising results on real images.

Jalobeanu, Andre↗
DOE OSTI2025

Interactive multiscale modeling to bridge atomic properties and electrochemical performance in Li-CO 2 battery design

Li-CO 2 batteries are promising energy storage systems due to their high theoretical energy density and CO 2 fixation capability, relying on reversible Li 2 CO 3 /C formation during discharge/charge cycles. Here, we present a multiscale modeling framework integrating Density Functional Theory (DFT), Ab-Initio Molecular Dynamics (AIMD), classical Molecular Dynamics (MD), and Finite Element Analysis (FEA) to investigate atomic and cell-level properties. The considered Li-CO 2 battery consists of a lithium metal anode, an ionic liquid electrolyte, and a carbon cloth cathode with Sb 0.67 Bi 1.33 Te 3 catalyst. DFT and AIMD determined the electrical conductivities of Sb 0.67 Bi 1.33 Te 3 and Li 2 CO 3 using the Kubo–Greenwood formalism and studied the CO 2 reduction mechanism on the cathode catalyst. MD simulations calculated the CO 2 diffusion coefficient, Li + transference number, ionic conductivity, and Li + solvation structure. The FEA model, parameterized with atomistic simulation data, reproduced the available experimental voltage–capacity profile at 1 mA/cm 2 and revealed spatio-temporal variations in Li 2 CO 3 /C deposition, porosity, and CO 2 concentration dependence on discharge rates in the cathode. Accordingly, Li 2 CO 3 can form large and thin film deposits, leading to dispersed and local porosity changes at 0.1 mA/cm 2 and 1 mA/cm 2 , respectively. The capacity decreases exponentially from 81,570 mAh/g at 0.1 mA/cm 2 to 6200 mAh/g at 1 mA/cm 2 , due to pore clogging from excessive discharge product deposition that limits CO 2 transport to the cathode interior. Therefore, the performance of Li-CO 2 batteries can be improved by enhancing CO 2 transport, regulating Li 2 CO 3 deposition, and optimizing cathode architecture.

Battery performance↗
DOE OSTI2026

Non-Equilibrium Actinide Radiation Chemistry and the Nuclear Fuel Cycle

Actinides are inherently unstable elements that frequently coexist with other radioisotopes, generating intense ionizing radiation fields that drive the formation of non equilibrium oxidation states. These transient species exert a profound mechanistic influence on the radiation response of actinide containing systems due to their unique redox chemistry. Despite their importance, they remain poorly understood, yet such insight is essential for advancing actinide science and accurately predicting radiation driven behavior. Actinide separations—critical for nuclear energy technologies, strategic deterrence, space exploration, and nuclear medicine—depend on precise control of actinide oxidation states to recover targeted elements from complex matrices such as used nuclear fuel. However, during these processes, actinides, their coordination complexes, and the separation media are all exposed to intense, multicomponent (alpha, beta, gamma, etc.) radiation fields that can alter process efficiency, selectivity, and chemical stability. Understanding, controlling, and mitigating radiation induced reactions is therefore key to innovating and optimizing next generation separation technologies. This seminar will provide an overview of the nuclear fuel cycle and non equilibrium actinide radiation chemistry in the context of recovering actinides from used nuclear fuel, with a particular emphasis on direct dissolution–based reprocessing strategies. We will explore time resolved electron pulse radiolysis and alpha and gamma dose accumulation studies, integrated with multiscale computational modeling, to elucidate the molecular level roles of radiation driven, non equilibrium actinide species in process performance and in the radiolytic stability of organic ligands used for actinide recovery. These insights offer new pathways for designing advanced separation methods and next generation solvent systems, with broad implications for the future of the nuclear fuel cycle.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗
DOE OSTI2024

Structural characterization of high-protein system through ultra-small and small-angle X-ray scattering

High-protein systems exhibit a hierarchical structure consisting of interconnected multiscale length assemblies. Recent investigations are directed toward identifying these structural units under various processing and environmental conditions to establish structure–function correlations. Ultra-small and small-angle X-ray scattering (USAXS/SAXS) has become a crucial tool for characterizing the structures of proteins and their clusters/aggregates, ranging from nanometers to micrometers, with minimal disruption to their original state. Here, this review first describes the facilities and principles of X-ray scattering, followed by discussions on the analysis of scattering data, including the interpretation of fitting models. It then delves into the main applications of USAXS/SAXS in plant and dairy protein-rich systems. Future strategies to enhance the utilization of scattering techniques for elucidating the structure of high-protein systems are also included.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Understanding the Performance Gap between Polycrystalline and Single-Crystal Nickel-Rich Layered Oxide Cathodes

Singe-crystal (SC) nickel-rich layered oxide cathodes, composed of boundary-free particles with high tap density, offer significant advantages in volumetric energy density and mechanical strength compared with polycrystalline (PC) cathode materials. However, as the nickel content increases (≥80%), SC Ni-rich cathodes often suffer from faster performance degradation than PC cathodes of the same composition, and the underlying causes of this discrepancy remain poorly understood. Herein, we reveal the distinct Ni redox behaviors that govern the electrochemical performance of SC and PC Ni-rich cathodes using multiscale and operando characterization techniques. Our results indicate that the increasingly heterogeneous Ni oxidation process in SC cathodes leads to the additional irreversible oxygen redox activity that deteriorates both the mechanical and chemical structures. In contrast, PC cathodes, despite with more pronounced surface reconstruction, exhibit greater chemomechanical stability due to homogeneous redox reactions during charging. Consequently, we find that bulk degradation, more than surface reactions, ultimately leads to fast capacity decay of SC Ni-rich cathodes during cycling. In conclusion, this work offers a comprehensive view on the impact of Ni redox evolutions on the chemomechanical stability in Ni-rich layered oxide cathodes, providing new insights into the longstanding performance gap between SC and PC cathodes, and guiding the rational design of Ni-rich cathode architectures.

36 MATERIALS SCIENCE↗
NASA NTRS2004

The Role of Auroral Imaging in Understanding Ionosphere-Inner Magnetosphere Interactions

The more ways we probe the ionosphere and inner magnetosphere, the better we can understand their interaction. For example, the multifaceted imaging of geospace with the IMAGE mission complements the more traditional in situ measurements made with many previous missions. Together they have enabled new knowledge of the ionosphere-magnetosphere (IM) coupling. The role of imaging the aurora in understanding this interaction has received renewed attention recently. Based on in situ data, such as FAST or DMSP, and our recent theories, we believe that imaging multiscale features of the aurora is a key component to gaining insight into the processes and mechanisms at work. This talk will explore how auroral imaging can be used to provide improved insight of the dynamics of IM interaction on micro and meso scales, with an emphasis on the current limitations and future possibilities of quantitative analyses.

Spann, Jim↗
NASA NTRSDate not supplied

Geometric Sensitivity of Residual Fields in Metal Additive Manufacturing

The sensitivity of geometrical parameters on the residual stress and distortion as computed by a metal additive manufacturing simulation is presented. A nozzle-like geometry was chosen with its length, wall thickness, and outer radius varied. A Latin hypercube sampling of 300 specimens produced the combinations of the geometrical parameters. Full thermomechanical simulations predicted the residual fields. Statistical analysis including regression curves shows that there is a strong correlation between these residual fields and the geometry, hinting that it may be possible to predictably influence the residual displacements and residual stresses by varying the overall geometry.

Multiscale Modeling↗
NASA NTRS2017

Comparison of Multiscale Method of Cells-Based Models for Predicting Elastic Properties of Filament Wound C/C-SiC

Three different multiscale models, based on the method of cells (generalized and high fidelity) micromechanics models were developed and used to predict the elastic properties of C/C-SiC composites. In particular, the following multiscale modeling strategies were employed: Concurrent multiscale modeling of all phases using the generalized method of cells, synergistic (two-way coupling in space) multiscale modeling with the generalized method of cells, and hierarchical (one-way coupling in space) multiscale modeling with the high fidelity generalized method of cells. The three models are validated against data from a hierarchical multiscale finite element model in the literature for a repeating unit cell of C/C-SiC. Furthermore, the multiscale models are used in conjunction with classical lamination theory to predict the stiffness of C/C-SiC plates manufactured via a wet filament winding and liquid silicon infiltration process recently developed by the German Aerospace Institute.

multiscale modeling↗