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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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At least 829 records · Page 46

Evaluating the De Hoffmann-Teller Cross-Shock 2 Potential at Real Collisionless Shocks

Shock waves are common in the heliosphere and beyond. The collisionless nature of most astrophysical plasmas allows for the energy processed by shocks to be partitioned amongst particle sub-populations and electromagnetic fields via physical mechanisms that are not well understood. The electrostatic potential across such shocks is frame dependent. In a frame where the incident bulk velocity is parallel to the magnetic field, the deHoffmann-Teller frame, the potential is linked directly to the ambipolar electric field established by the electron pressure gradient. Thus measuring and understanding this potential solves the electron partition problem, and gives insight into other competing shock processes. Integrating measured electric fields in space is problematic since the measurements can have offsets that change with plasma conditions. The offsets, once integrated, can be as large or larger than the shock potential. Here we exploit the high-quality field and plasma measurements from NASA’s Magnetospheric Multiscale mission to attempt this calculation. We investigate recent adaptations of the deHoffmann-Teller frame transformation to include time variability, and conclude that in practice these face difficulties inherent in the 3D time-dependent nature of real shocks by comparison to 1D simulations. Potential estimates based on electron fluid and kinetic analyses provide the most robust measures of the deHoffmann-Teller potential, but with some care direct integration of the electric fields can be made to agree. These results suggest that it will be difficult to independently assess the role of other processes, such as scattering by shock turbulence, in accounting for the electron heating.

Steven J Schwartz↗

Multiscale Modeling of Fracture Strength in Fibrous Thermal Protection System Materials

This work presents a multiscale modeling approach to predict the fracture strength of fibrous Thermal Protection System (TPS) materials. The model assumes that system failure is initiated at the joints between individual fibers. We investigated three distinct TPS compositions: amorphous silica, alumina and aluminosilicate fibers. Molecular dynamics (MD) simulations were employed to determine the fracture strength values of these fiber joints for both material systems. These fracture strength values were then integrated into simulations of 3D randomly populated fiber structures, where tensile load transfer occurs through the fiber joints. These microscale properties are upscaled through a renormalization approach [1] to predict macroscale tensile strength of 3D random fiber networks, accounting for joint-dominated failure and effective load-bearing area. The study concludes by demonstrating the resulting strength variation as a function of material composition, fiber density, and morphology. We also show validation of results by comparing them against explicit fiber finite element (FE) modeling [2] where fiber joint fracture is represented by cohesive elements.

Jaehyun Cho↗

Kinetic Growth of Multicomponent Microcompartment Shells

An important goal of systems and synthetic biology is to produce high value chemical species in large quantities. Microcompartments, which are protein nanoshells encapsulating catalytic enzyme cargo, could potentially function as tunable nanobioreactors inside and outside cells to generate these high value species. Modifying the morphology of microcompartments through genetic engineering of shell proteins is one viable strategy to tune cofactor and metabolite access to encapsulated enzymes. However, this is a difficult task without understanding how changing interactions between the many different types of shell proteins and enzymes affect microcompartment assembly and shape. Here, we use multiscale molecular dynamics and experimental data to describe assembly pathways available to microcompartments composed of multiple types of shell proteins with varied interactions. As the average interaction between the enzyme cargo and the multiple types of shell proteins is weakened, the shell assembly pathway transitions from (i) nucleating on the enzyme cargo to (ii) nucleating in the bulk and then binding the cargo as it grows to (iii) an empty shell. Atomistic simulations and experiments using the 1,2-propanediol utilization microcompartment system demonstrate that shell protein interactions are highly varied and consistent with our multicomponent, coarse-grained model. Furthermore, our results suggest that intrinsic bending angles control the size of these microcompartments. Altogether, our simulations and experiments provide guidance to control microcomparmtent size and assembly by modulating the interactions between shell proteins.

defects↗

Electro-reduction of organics on metal cathodes: A multiscale-modeling study of benzaldehyde on Au (111)

Here, we present a multiscale modeling study on the electro-reduction of benzaldehyde (BZY) on Au(111) under realistic electrochemical conditions. To model the electrochemical cell, we adopt a capacitor model in which complex solvents are confined between a Au cathode and a carbon anode. Classical molecular dynamics simulations reveal that electrode charge density and the presence of alcohol show strong effects on the density, adsorption geometry and dynamics of benzaldehyde on the Au electrode. Under charging conditions, the surface concentration of benzaldehyde on the Au electrode decreases, while the content of other species increases. Finally, we proposed a scheme that correlates the electric current running through the Au/solvent interface with the applied bias. This study provides a molecular level understanding of how solvent composition, in this case water/alcohol content, controls the activity of electrocatalytic hydrogenation

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A multiscale anisotropic polymer network model coupled with phase field fracture

The study of polymers has continued to gain substantial attention due to their expanding range of applications, spanning essential engineering fields to emerging domains like stretchable electronics, soft robotics, and implantable sensors. These materials exhibit remarkable properties, primarily stemming from their intricate polymer chain network, which, in turn, increases the complexity of precisely modeling their behavior. Especially for modeling elastomers and their fracture behavior, accurately accounting for the deformations of the polymer chains is vital for predicting the rupture in highly stretched chains. Despite the importance, many robust multiscale continuum frameworks for modeling elastomer fracture tend to simplify network deformations by assuming uniform behavior among chains in all directions. Recognizing this limitation, our study proposes a multiscale fracture model that accounts for the anisotropic nature of elastomer network responses. At the microscale, damage in the chains is assumed to be driven by both the chain's entropy and the internal energy due to molecular bond distortions. In order to bridge the stretching in the chains to the macroscale deformation, we employ the maximal advance path constraint network model, inherently accommodating anisotropic network responses. As a result, chains oriented differently can be predicted to exhibit varying stretch and, consequently, different damage levels. To drive macroscale fracture based on damages in these chains, we utilize the micromorphic regularization theory, which involves the introduction of dual local-global damage variables at the macroscale. The macroscale local damage variable is obtained through the homogenization of the chain damage values, resulting in the prediction of an isotropic material response. The macroscale global damage variable is subjected to nonlocal effects and boundary conditions in a thermodynamically consistent phase field continuum formulation. Moreover, the total dissipation in the system is considered to be mainly due to the breaking of the molecular bonds at the microscale. To validate our model, we employ the double-edge notched tensile test as a benchmark, comparing simulation predictions with existing experimental data. Additionally, to enhance our understanding of the fracturing process, we conduct uniaxial tensile experiments on a square film made up of polydimethylsiloxane (PDMS) rubber embedded with a hole and notches and then compare our simulation predictions with the experimental observations. Furthermore, we visualize the evolution of stretch and damage values in chains oriented along different directions to assess the predictive capacity of the model. In conclusion, the results are also compared with another existing model to evaluate the utility of our model in accurately simulating the fracture behavior of rubber-like materials.

42 ENGINEERING↗

Multiscale Fatigue Life Prediction for Composite Panels

Fatigue life prediction capabilities have been incorporated into the HyperSizer Composite Analysis and Structural Sizing Software. The fatigue damage model is introduced at the fiber/matrix constituent scale through HyperSizer s coupling with NASA s MAC/GMC micromechanics software. This enables prediction of the micro scale damage progression throughout stiffened and sandwich panels as a function of cycles leading ultimately to simulated panel failure. The fatigue model implementation uses a cycle jumping technique such that, rather than applying a specified number of additional cycles, a specified local damage increment is specified and the number of additional cycles to reach this damage increment is calculated. In this way, the effect of stress redistribution due to damage-induced stiffness change is captured, but the fatigue simulations remain computationally efficient. The model is compared to experimental fatigue life data for two composite facesheet/foam core sandwich panels, demonstrating very good agreement.

Bednarcyk, Brett A.↗

Sensitivity of pore collapse heating to the melting temperature and shear viscosity of HMX

A multiscale modeling strategy is used to quantify factors governing the temperature rise in hot spots formed by pore collapse from supported and unsupported shock waves in the high explosive HMX (octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine). Two physical aspects are examined in detail, namely the melting temperature and liquid shear viscosity. All-atom molecular dynamics simulations of phase coexistence are used to predict the pressure-dependent melting temperature up to 5 GPa. Equilibrium simulations and the Green–Kubo formalism are used to obtain the temperature- and pressure-dependent liquid shear viscosity. Starting from a simplified continuum-based grain-scale model of HMX, in this study we systematically increase the complexity of treatments for the solid–liquid phase transition and liquid shear viscosity in simulations of pore collapse. Using a realistic pressure-dependent melting temperature completely suppresses melting for supported shocks, which is otherwise predicted when treating it as a constant determined at atmospheric pressure. Alternatively, melt pools form around collapsed pores when the pressure (and melting temperature) are reduced during the release stage of unsupported shocks. Capturing the pressure dependence of the shear viscosity increases the peak temperature of melt pools by hundreds of Kelvin through viscous work. The complicated interplay of the solid-phase plastic work, solid–liquid phase transition, and liquid-phase viscous work identified here motivate taking a systematic approach to building increasingly complex grain-scale models.

36 MATERIALS SCIENCE↗

Numerical investigation of thermomechanical response of multiscale porous Ultra-High Temperature Ceramics

Recent advances in Ultra-High Temperature Ceramics (UHTC) manufacturing have permitted the development of multiscale porous UHTC microstructures. Within the target application of hypersonic vehicles, dense UHTCs are suitable for thermal protection on leading edges, whereas porous UHTCs may find a role in providing thermally insulated interfaces for temperature-sensitive interior components. Designing vehicles incorporating porous UHTCs requires a characterization of their thermomechanical properties across the full range of expected operating temperatures spanning –20 °C–2500 °C. This research represents a preliminary study in performing this characterization. Several numerical experiments are performed using a coupled thermomechanical implementation of the Material Point Method to determine the temperature dependence of effective material properties both with and without damage. Furthermore, complex time-dependent boundary conditions derived from known hypersonic flight profiles are simulated in order to probe the various couplings between deformation, damage and heat transfer. It is shown that the model reveals the importance of micro-buckling in determining effective material stiffness and thermal conductivity.

36 MATERIALS SCIENCE↗

Identifying the Growth Phase of Magnetic Reconnection Using Pressure‐Strain Interaction

Abstract Magnetic reconnection often initiates abruptly and then rapidly progresses to a nonlinear quasi‐steady state. While satellites frequently detect reconnection events, ascertaining whether the system has achieved steady‐state or is still evolving in time remains challenging. Here, we propose that the relatively rapid opening of the reconnection separatrices within the electron diffusion region serves as an indicator of the growth phase of reconnection. The opening of the separatrices is produced by electron flows diverging away from the neutral line downstream of the X‐line and flowing around a dipolarization front. This flow pattern leads to characteristic spatial structures in the electron pressure‐strain interaction that could be a useful indicator for the growth phase of a reconnection event. We employ two‐dimensional particle‐in‐cell numerical simulations of anti‐parallel magnetic reconnection to validate this prediction. We find that the signature discussed here, alongside traditional reconnection indicators, can serve as a marker of the growth phase. This signature is potentially accessible using multi‐spacecraft single‐point measurements, such as with NASA's Magnetospheric Multiscale satellites in Earth's magnetotail. Applications to other settings where reconnection occurs are also discussed.

Barbhuiya, M. Hasan [Department of Physics and Ast↗

Topology induced crossover between Langevin, subdiffusion, and Brownian diffusion regimes in supercooled water

Despite extensive studies of supercooled water, it remains challenging to understand its peculiar dynamic anomalous properties. In this work, we integrated full atomistic simulations of supercooled water over the temperature range of room temperature to 200 K using a quantum-mechanics-based polarizable force field with the dressed dynamics method that couples fast collision events and slow reorganization dynamics of hydrogen-bond networks. Our analysis unveils the salient multiscale features in the transient relaxation dynamics of supercooled water. A classical Langevin behavior dominates at fast timescales, while long-time relaxations unveil two different activation barriers in two temperature regions: below and above 230 K. The modulation of the entropy spectrum by temperature is elucidated in terms of a three-state model underlined by the complexity of the water dynamics associated with a topological transition of a strong hydrogen-bond network. This state-dependent network topology is quantitatively characterized by power-law exponents of inverse network connectivity from 200 to 298 K. Finally, this work provides valuable guidance for further studies on the transient relaxation dynamics of supercooled water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Impacts of Biomass Feedstock Pre-Processing on Heat and Mass Transfer During Pyrolysis Using X-Ray Computed Tomography and Multiscale Modeling

Knowledge of the transport properties of biomass particles such as porosity, tortuosity, and permeability is paramount for high-fidelity modeling of biomass pyrolysis due to the heat and mass transfer limitations imposed by particle microstructure. X-ray computed tomography (XCT) is a non-destructive imaging method that enables full 3D reconstructions of the biomass particle microstructure with high resolution, permitting direct calculation of porosity, tortuosity, and permeability from real particle geometries. In this study, XCT imaging revealed the 3D microstructures of particles and chars from pyrolytic conversion of cylindrically cut or milled/pelletized loblolly pine samples. The porosity, tortuosity, and permeability were calculated directly from the XCT geometries via open-source microstructural analysis tool MATBOX+TauFactor (https://github.com/NREL/MATBOX_Microstructure_analysis_toolbox) and computational fluid dynamics (CFD) simulations using our solver, Mesoflow (https://github.com/NREL/mesoflow). These properties were used in a reactor scale model developed in COMSOL of the single particle reactor at NREL to investigate the impact of feedstock pre-processing on biomass conversion during pyrolysis with rigorous experimental validation.

biomass↗

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↗

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↗

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↗