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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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NASA NTRS2019

Global Evolution of Solar Magnetic Fields and Prediction of Solar Activity Cycles

Prediction of solar activity cycles is challenging because the physical processes inside the Sun involve a broad range of multiscale dynamics that no model can reproduce, and the available observations are highly limited and cover mostly surface layers. Helioseismology makes it possible to probe solar dynamics in the convective zone, but variations in the differential rotation and meridional circulation are currently available for only two solar activity cycles. It has been demonstrated that sunspot observations, which cover over 400 years, can be used to calibrate the Parker-Kleeorin-Ruzmaikin model and that the Ensemble Kalman Filter (EnKF) method can be used to link the model magnetic fields to sunspot observations to make reliable predictions of a following cycle. However, for more accurate predictions, it is necessary to use actual observations of the solar magnetic fields, which are available for only four solar cycles. This raises the question of how limitations in observational data and model uncertainties affect predictive capabilities and implies the need for the development of new forecast methodologies and validation criteria. In this presentation, I will discuss the influence of the limited number of available observations on the accuracy of EnKF estimates of solar cycle parameters.

Kitiashvili, Irina N.↗

DOE OSTI2022

Uncertainty quantification in elastic constants of SiC f /SiC m tubular composites using global sensitivity analysis

Silicon carbide fiber and silicon carbide matrix (SiC f /SiC m ) tubes produced through the chemical vapor infiltration process have become a candidate cladding material in nuclear applications. The performance of this composite is influenced by many variables such as braiding angle, porosity, material properties, etc., which vary over a range of values due to the inherent fluctuations in the manufacturing process. In this study, the variability in elastic constants of SiC f /SiC m composite has been quantified through multiscale finite element (FE) simulations, variable screening, and high-fidelity surrogate modeling. The key variables dominantly affecting the elastic constants of SiC f /SiC m tubes were identified using global sensitivity analysis. A surrogate to the high-fidelity FE-based model was used in Monte Carlo simulations to generate a hundred thousand samples from which the uncertainty in elastic constants was assessed. It turned out that the coefficient of variation was less than 10%.

Materials Science↗

DOE OSTI2024

Predicting Critical Transitions in Multiscale Data

Predicting the dynamics of complex nonlinear systems remains a challenging problem both in dynamical systems theory as well as real world science and engineering applications. Data-driven methods utilizing the latest advances in machine learning (ML) provide a promising new paradigm for this task. Our work centered on Reservoir Computing (RC), which has shown itself to be capable of skillfully predicting chaotic dynamics in multiscale systems. In the first part of the work, the focus is on how to improve predictions of critical transitions in a class of slow-fast metastable systems in which the equations are known. An additional goal was to determine whether a relationship exists between RC and Koopman operator theory, to improve the efficiency and broaden the applicability of the approach. In the second part of this work, a variation on the RC model known as Reconstructive Reservoir Computing (RRC) is applied to real-world data to identify anomalies.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

The Role of Topography in Controlling Evapotranspiration Age

Abstract Evapotranspiration (ET) age is a key metric of water sustainability but a major unknown partly due to the extreme difficulty in modeling it. Groundwater is found to be important in ET age variations in small‐scale studies, yet our understanding is insufficient because groundwater systems are nested across scales. Here, we conducted GPU‐accelerated particle tracking with integrated hydrologic modeling to quantify the variations in ET age at a regional scale of ∼0.4 M km 2 . Simulation results reveal topography‐driven flow paths shaping the spatial and temporal patterns of ET age variations. On ridges, where root zone decoupling with deep subsurface storage, ET age is generally young, with seasonal variations dominated by meteorological conditions. In the valley bottom, ET age is generally old, with significant subseasonal variations caused by the convergence of subsurface flow paths. On hillslopes with water table depths ranging from 1 to 10 m, ET age shows strong seasonal variations caused by the connections with lateral groundwater regulated by ET demand. Our modeling approach provides insights into the basic linkages between ET age and topography at large scale. Our work highlights the perspective of multiscale studies of ET age, suggesting new field experiments to test these process connections and to determine if such linkages warrant inclusion in Earth System Models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Multiscale in-situ characterization of static recrystallization using dark-field X-ray microscopy and high-resolution X-ray diffraction

Abstract Dark-field X-ray microscopy (DFXM) is a high-resolution, X-ray-based diffraction microstructure imaging technique that uses an objective lens aligned with the diffracted beam to magnify a single Bragg reflection. DFXM can be used to spatially resolve local variations in elastic strain and orientation inside embedded crystals with high spatial (~ 60 nm) and angular (~ 0.001°) resolution. However, as with many high-resolution imaging techniques, there is a trade-off between resolution and field of view, and it is often desirable to enrich DFXM observations by combining it with a larger field-of-view technique. Here, we combine DFXM with high-resolution X-ray diffraction (HR-XRD) applied to an in-situ investigation of static recrystallization in an 80% hot-compressed Mg–3.2Zn–0.1Ca wt.% (ZX30) alloy. Using HR-XRD, we track the relative grain volume of > 8000 sub-surface grains during annealing in situ. Then, at several points during the annealing process, we “zoom in” to individual grains using DFXM. This combination of HR-XRD and DFXM enables multiscale characterization, used here to study why particular grains grow to consume a large volume fraction of the annealed microstructure. This technique pairing is particularly useful for small and/or highly deformed grains that are often difficult to resolve using more standard diffraction microstructure imaging techniques.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Observation of Kolmogorov turbulence due to multiscale vortices in dusty plasma experiments

We report the experimental observation of fully developed Kolmogorov turbulence originating from self-excited vortex flows in a three-dimensional (3D) dust cloud. The characteristic -5/3 scaling of 3D Kolmogorov turbulence is consistent in both the spatial and temporal energy spectra within a statistical variation of experimental data. Additionally, the 2/3 scaling in the second-order structure function further supports the presence of Kolmogorov turbulence. We also identified a slight deviation in the tails of the probability distribution functions for velocity gradients, a reflection of intermittency. The experiment showed the formation of a dust cloud in the diffused plasma region away from the electrodes. The dust rotation was observed in multiple experimental campaigns under different discharge conditions at different spatial locations and background plasma environments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1991

Environmental analysis using integrated GIS and remotely sensed data - Some research needs and priorities

This paper discusses some basic scientific issues and research needs in the joint processing of remotely sensed and GIS data for environmental analysis. Two general topics are treated in detail: (1) scale dependence of geographic data and the analysis of multiscale remotely sensed and GIS data, and (2) data transformations and information flow during data processing. The discussion of scale dependence focuses on the theory and applications of spatial autocorrelation, geostatistics, and fractals for characterizing and modeling spatial variation. Data transformations during processing are described within the larger framework of geographical analysis, encompassing sampling, cartography, remote sensing, and GIS. Development of better user interfaces between image processing, GIS, database management, and statistical software is needed to expedite research on these and other impediments to integrated analysis of remotely sensed and GIS data.

Davis, Frank W.↗

NASA NTRS2019

Lunisolar Perturbations of High-Eccentricity Orbits Such as the Magnetospheric Multiscale Mission

For highly eccentric orbits such as that of the Magnetospheric Multiscale (MMS)mission, with apogee radius now 29.34 Earth radii, the third-body effects of Sun andMoon are the major perturbations. One key consequence is an oscillation in MMSperigee altitude, on an approximately 6 year cycle. This variation has already requiredperigee-raise maneuvers to avoid an untimely reentry. There is also a long-termevolution in the orientation of the MMS orbit, with period roughly twice as long. Thiseffect may potentially be useful for MMS science studies, as it can bring the spacecraftinto new regions of the magnetosphere.

Williams, Trevor↗

NASA NTRSDate not supplied

Space Needle Returns

STEP is imported into Engineering Sketch Pad. Some bodies where slightly scaled and translated in OpenCSM to create a manifold solid for the downstream meshing process. The braces at the base and columns around the core are omitted because their solids are malformed or created nonmanifold intersections. EGADS provides an initial tessellation of the surface. refine adapted the surface mesh to a curvature and feature size metric. TetGen initially filled the volume. The TetGen mesh is adapted to the Spalding Law of the Wall u+ with refine to provide the initial mesh for flow solution. Solution-based mesh adaptation is performed where FUN3D-FV computes the flow solution with the Reynolds-averaged Navier-Stokes equations coupled to the Spalart-Allmaras turbulence model. The freestream Mach number is 4 approaching 40° from the central axis of the Space Needle. The volume and surface mesh is adapted with refine to reduce estimated interpolation error in Mach number via the multiscale metric. The adapted mesh implicitly resolves the boundary layers, shocks, and expansions. The surface mesh is shown for the lee side with a slice through the volume on the left. Computational schlieren in the lower right shows density variations. A slice of the mesh is colored with Mach number in the upper right where mesh with freestream Mach number is not rendered. The volume mesh contains 64 million vertices. A NASA worm logo is sketched and extruded into a solid in OpenCSM. The worm is unioned to the Space Needle roof to produce the inset mesh image.

mesh↗

DOE OSTI2024

Elucidating the role of Cr migration in Ni-Cr exposed to molten FLiNaK via multiscale characterization

Structural materials used in nuclear reactor environments are subjected to coupled extremes such as high temperature, irradiation, and corrosion which act in concert to degrade their functional performance. Connecting alloy microstructure such as grain boundaries, and accumulating point defects with corrosion attack and pore morphology is critical to understanding underlying mechanisms. We uncover the compositional variations and morphology at multiple length scales in corrosion-damaged Ni-Cr alloy after exposure to oxidants in molten fluoride salts. A complex network of dense corrosion pores is detected by surface-level SEM observations. The corrosion pores take on a 1-dimensional morphology and are enriched with Ni and depleted of Cr 1–5 µm from the pore surface. STEM-EDS and 4D-STEM strain maps acquired simultaneously highlight the local variations in composition and structure of a ≤ 200 nm Cr-rich layer identified from a cross-section taken at the bottom of an isolated corrosion pore between the Ni-Cr alloy matrix and the embedded salt. However, the absence of an observed interface between the Ni-Cr alloy matrix and the FCC-structured Cr-rich layer suggests that Cr plating from the salt did not transpire. These findings support a proposed Cr lattice diffusion mechanism rather than Cr-precipitation from the salt to accommodate temperature transient conditions during sample cooling. Through the development of a 1D phase field model, these results are rationalized by formation energies for the Ni- and Cr-oxidation into the molten salt. This study reveals the locally altered microstructure caused by high temperature corrosion in non-steady-state molten salt nuclear reactor environments.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Microscale Constitutive Model Sensitivity on Multiscale Modeling of Fiber Reinforced Composites

Fiber reinforced composites are desirable in applications where low weight and high strength are needed, but are susceptible to microscale variability during manufacturing, making failure predictions difficult. The impact microscale variability has on macroscale mechanical response is difficult to predict due to the computational efficiency needed to simulate many, large, high fidelity, microscale models. In this study, a multiscale approach was taken to model 3-point bend, 4-point bend, and tensile experiments of a unidirectional composite from only having microstructure scans of these samples and constituent properties from literature. These scans were sampled with different sized windows, and statistically equivalent microstructures were generated, then simulated for stiffness, strength, and fracture toughness using an efficient micromechanical. Mesoscale models were created where element sizes equaled microstructure size, and properties were assigned through sampling of microscale simulation results. First, this study showed the effect of using Weibull scaling on constituent matrix strength on macroscale response. Then, a comparison was made between different element sizes and experiments. Finally, model dimensions were fixed, and the effect of randomly distributed local properties alone was examined. Results showed that the scatter of strength and stiffness in the experiments could be predicted well using images of the microscale fiber morphologies and that using stochastic properties produced a 3% coefficient of variation of strength for all experiments.

statistical microstructure↗

DOE OSTI2022

Three-dimensional inhomogeneity of electron-temperature-gradient turbulence in the edge of tokamak plasmas

Nonlinear multiscale gyrokinetic simulations of a Joint European Torus edge pedestal are used to show that electron-temperature-gradient (ETG) turbulence has a rich three-dimensional structure, varying strongly according to the local magnetic-field configuration. In the plane normal to the magnetic field, the steep pedestal electron temperature gradient gives rise to anisotropic turbulence with a radial (normal) wavelength much shorter than in the binormal direction. In the parallel direction, the location and parallel extent of the turbulence are determined by the variation in the magnetic drifts and finite-Larmor-radius (FLR) effects. The magnetic drift and FLR topographies have a perpendicular-wavelength dependence, which permits turbulence intensity maxima near the flux-surface top and bottom at longer binormal scales, but constrains turbulence to the outboard midplane at shorter electron-gyroradius binormal scales. Here our simulations show that long-wavelength ETG turbulence does not transport heat efficiently, and significantly decreases overall ETG transport—in our case by ~40%—through multiscale interactions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Topologically derived dislocation theory for twist and stretch moiré superlattices in bilayer graphene

In this work, we develop a continuum dislocation description of twist and stretch moiré superlattices in two-dimensional material bilayers. The continuum formulation is based on the topological constraints introduced by the periodic dislocation network associated with the moiré structure. The approach is based on solving analytically for the structural distortion and displacement fields that satisfy the topological constraints and that minimize the total energy. The total energy is described by both the strain energy of each individual distorted layer and a Peierls-Nabarro-like interfacial contribution arising from stacking disregistry. The dislocation core emerges naturally within the formalism as a result of the competition between the two contributions. The approach presented here captures the structure and energetics of twist and stretch moiré superlattices of dislocations with arbitrary direction and character, without assuming an analytical solution a priori and while accounting naturally for dislocation-dislocation image interactions. In comparisons to atomistic simulations using classical potentials, the maximum structure deviation is 6%, while the maximum line energy deviation is 0.019 eV/Å. Several applications of our model are shown, including predicting the variation of structure with twist angle and describing dislocation line tension and junction energies.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Multiscale and Machine Learning Modeling for Additive Manufacturing

Additive manufacturing (AM) techniques provide the opportunity to simultaneously design new materials and components with complex structures in less time, enabling faster material developments. Even though compositionally similar, the texture of the materials produced by such techniques is significantly different from conventionally manufactured materials. Additively manufactured materials produces highly heterogeneous microstructure within a single build. Such variations in the microstructure make qualifying AM products challenging for extreme environment applications. Understanding the AM process and its influence on the materials’ microstructures/properties is paramount for evaluating the workability and performance of the manufactured materials. The performance of AM materials for advanced nuclear reactor applications is of interest to the Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy. Hence, considering the microstructural variabilities in the AM products and their impact on the performance of the material, it is important to correlate the process conditions to the final product and establish a process-structure-property- performance (PSPP) correlation for AM materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Multiscale Electrothermal Design of a Modular Multilevel Converter for Grid-Tied Applications

As a key feature of modular multilevel converters (MMCs), a large number of semiconductor devices are employed in the converter and distributed over a stack of submodules. Each submodule has a strict temperature limit that imposes constraints on the operating range of the converter. Different loading conditions/losses in the submodules lead to unavoidable temperature variations inside the MMC, which consequently affect the system-level performance and reliability. This paper is focused on the electrothermal analysis and design of a medium-voltage silicon carbide (SiC)-based MMC system, from submodule power semiconductors to the overall MMC system integration of multiple submodules. Loss calculations are performed to estimate the cooling requirements and aid thermal design at different levels. The performance of forced-air cooling approach is analyzed within a numerical modeling framework. Maximum temperature of the SiC power modules is predicted using numerical tools. Thermal design of the MMC cabinet with various arrangement of air inlet(s) and outlet(s) is investigated and compared from a cooling performance perspective.

CFD↗

NASA NTRSDate not supplied

Magnetic reconnection for low-density inflow conditions

Like in all environments, magnetic reconnection in the Earth’s magnetotail and its efficacy depend on plasma conditions in the inflow region. The Earth’s magnetotail is a particularly interesting environment to study this dependency, because plasma densities in the inflow region can vary widely. Under conditions of strong magnetospheric convection, high density plasma from ionospheric or solar wind origin can impact reconnection significantly, whereas at other times, particle density in the inflow region can be extremely low. The present study is motivated by recent observations by the Magnetospheric Multiscale Mission, which indicate an unusually large level of plasma turbulence when the plasma inflow density is very low. In this simulation-based study, we aim to shed light on the question, whether low density in the inflow region intrinsically leads to enhanced turbulence, or whether density variations are essential to create significant deviations from the usual, more laminar, picture of reconnection. Finally, we will comment on the implications of extremely low inflow density on the reconnection process.

heliophysics↗

DOE OSTI2022

Three‐Dimensional Permeability Inversion Using Convolutional Neural Networks and Positron Emission Tomography

Abstract Quantification of heterogeneous multiscale permeability in geologic porous media is key for understanding and predicting flow and transport processes in the subsurface. Recent utilization of in situ imaging, specifically positron emission tomography (PET), enables the measurement of three‐dimensional (3‐D) time‐lapse radiotracer solute transport in geologic media. However, accurate and computationally efficient characterization of the permeability distribution that controls the solute transport process remains challenging. Leveraging the relationship between local permeability variation and solute advection behavior, an encoder‐decoder based convolutional neural network (CNN) is implemented as a permeability inversion scheme using a single PET scan of a radiotracer pulse injection experiment as input. The CNN can accurately capture the 3‐D spatial correlation between the permeability and the radiotracer solute arrival time difference maps in geologic cores. We first test the inversion accuracy using synthetic test datasets and then test the accuracy on a suite of experimental PET imaging datasets acquired on four different geologic cores. The network‐predicted permeability maps from the geologic cores are used to parameterize forward numerical models that are directly compared with the experimental PET imaging data. The results indicate that a single trained network can generate robust 3‐D permeability inversion maps in seconds. Numerical models parameterized with these permeability maps closely capture the experimentally observed solute arrival time behavior. This work provides an unprecedented approach for efficiently characterizing multiscale permeability heterogeneity in complex geologic samples.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Multiscale Land-Atmosphere Interaction in Tropical Ecosystems

A leading source of uncertainty in the magnitude of future climate change arises from feedback between the physical climate system and the carbon cycle. Output from 15 Earth System Models (ESMs) in the Coupled Model Intercomparison Project (CMIP5) shows that when forced by identical emissions, predicted atmospheric CO 2 concentrations in 2100 ranged from 780 ppm to 1120 ppm due to variations in carbon cycle feedback among the models. The resulting difference in radiative forcing of climate is almost 2 W m -2 , comparable to the total uncertainty in the physical climate system for the representative concentration pathway (RCP) 8.5 scenario in 2100. Scaling future carbon sources and sinks to match contemporary atmospheric CO 2 reduced this uncertainty by a factor of five, suggesting that contemporary observations might dramatically constrain future predictions, but their scaling had no mechanistic basis, so it provides little insight on carbon cycle processes.

54 ENVIRONMENTAL SCIENCES↗