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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

A Cartesian cut cell method for rarefied flow simulations around moving obstacles

For accurate simulations of rarefied gas flows around moving obstacles, we propose a cut cell method on Cartesian grids: it allows exact conservation and accurate treatment of boundary conditions. Our approach is designed to treat Cartesian cells and various kinds of cut cells by the same algorithm, with no need to identify the specific shape of each cut cell. This makes the implementation quite simple, and allows a direct extension to 3D problems. Such simulations are also made possible by using an adaptive mesh refinement technique and a hybrid parallel implementation. This is illustrated by several test cases, including a 3D unsteady simulation of the Crookes radiometer.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1999

Experimental Verification of the Use of Metal Filled Via Hole Fences for Crosstalk Control of Microstrip Lines in LTCC Packages

Coupling between microstrip lines in dense RF packages is a common problem that degrades circuit performance. Prior 3D-FEM electromagnetic simulations have shown that metal filled via hole fences between two adjacent microstrip lines actually increases coupling between the lines; however, if the top of the via posts are connected by a metal Strip, coupling is reduced. In this paper, experimental verification of the 3D-FEM simulations Is demonstrated for commercially fabricated LTCC packages.

Ponchak, George E.↗
DOE OSTI2020

3D full wave fast wave modeling with realistic antenna geometry and SOL plasma

This paper reports the significant advancement of our ability to model and to understand how RF waves interact with the SOL plasma, by simulating the full torus 3D SOL plasma together with the antenna and core plasma. We introduce and use a recently developed and open source code, Petra-M, which was constructed on the scalable MFEM C++ finite element library, and performed 3D full wave simulations in the HHFW regime for both NSTX-U and LAPD plasmas. A first full wave simulation for a full 3D torus including a realistic antenna geometry and SOL plasma region for NSTX-U is presented. A scan of the antenna phasing shows a strong interaction between FWs and the SOL plasma for lower antenna phasing, which is consistent with previous NSTX HHFW observations. The effect of the 3D wave field on the fast ion population from NBI beams in NSTX-U is also discussed by using the 3D field obtained from the Petra-M simulations in the full-orbit following particle SPIRAL code. On LAPD, 3D full wave simulations of a new HHFW 4-strap antenna recently installed by TAE Technologies on LAPD are performed showing a qualitative agreement with experimental data.

Bertelli, Nicola↗
DOE OSTI2022

Kimberlina 1.2 CCUS Geophysical Models and Synthetic Data Sets

This synthetic multi-scale and multi-physics data set was produced in collaboration with teams at the Lawrence Berkeley National Laboratory, National Energy Technology Laboratory, Los Alamos National Laboratory, and Colorado School of Mines through the Science-informed Machine Learning for Accelerating Real-Time Decisions in Subsurface Applications (SMART) Initiative. Data are associated with the following publication: Alumbaugh, D., Gasperikova, E., Crandall, D., Commer, M., Feng, S., Harbert, W., Li, Y., Lin, Y., and Samarasinghe, S., “The Kimberlina Synthetic Geophysical Model and Data Set for CO2 Monitoring Investigations”, The Geoscience Data Journal, 2023, DOI: 10.1002/gdj3.191. The dataset uses the Kimberlina 1.2 CO2 reservoir flow model simulations based on a hypothetical CO2 storage site in California (Birkholzer et al., 2011; Wainwright et al., 2013). Geophysical properties models (P- and S-wave seismic velocities, saturated density, and electrical resistivity) were produced with an approach similar to that of Yang et al. (2019) and Gasperikova et al. (2022) for 100 Kimberlina 1.2 reservoir models. Links to individual resources are provided below: [CO2 Saturation Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-co2-saturation-models); Resistivity Models – [part 1](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-1), [part 2](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-2), and [part 3](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-3); [Vp Velocity Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-vp-velocity-models); [Vs Velocity Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-vs-velocity-models); [Density Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-density-models). The 3D distributions of geophysical properties for the 33 time stamps of the SIM001 model were used to generate synthetic seismic, gravity, and electromagnetic (EM) responses for 33 times between zero and 200 years. Synthetic surface seismic data were generated using 2D and 3D finite-difference codes that simulate the acoustic wave equation (Moczo et al., 2007). 2D data were simulated for six point-pressure sources along a 2D line with 10 m receiver spacing and a time spacing of 0.0005 s. 3D simulations were completed for 25 surface pressure sources using a source separation of 1 km in both the x and y directions and a time spacing of 0.001 s. Links to individual resources are provided below: [2D velocity models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-2d-velocity-models) and [2D surface seismic data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-2d-surface-seismic-data). [3D velocity models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-velocity-models), and 3D seismic data [year0](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year0), [year1](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year1), [year2](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year2), [year5](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year5), [year10](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year10), [year15](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year15), [year20](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year20), [year25](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year25), [year30](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year30), [year35](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year35), [year40](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year40), [year45](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year45), [year49](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year49), [year50](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year50), [year51](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year51), [year52](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year52), [year55](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year55), [year60](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year60), [year65](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year65), [year70](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year70), [year75](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year75), [year80](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year80), [year85](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year85), [year90](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year90), [year95](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year95), [year100](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year100), [year110](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year110), [year120](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year120), [year130](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year130), [year140](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year140), [year150](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year150), [year175](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year175), [year200](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year200). The Python scripts to read these models and data are provided [here](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-python-scripts). EM simulations used a borehole-to-surface survey configuration, with the source located near the reservoir level and receivers on the surface using the code developed by Commer and Newman (2008). Pseudo-2D data for the source at [2500 m](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-pseudo-2d-csem-data-tz2500m) and [3025 m](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-pseudo-2d-csem-data-tz3025m), used a 2D inline receiver configuration to simulate a response over 3D resistivity models. The [3D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-csem-data) contain electric fields generated by borehole sources at monitoring well locations and measured over a surface receiver grid. Vector gravity data, both on the surface and in boreholes, were simulated using a modeling code developed by Rim and Li (2015). The simulation scenarios were parallel to those used for the EM: [pseudo-2D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-gravity-data) were calculated along the same lines and within the same boreholes, and [3D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-gravity-data) were simulated over 3D models on the surface and in three monitoring wells. A series of [synthetic well logs](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-well-logs) of CO2 saturation, acoustic velocity, density, and induction resistivity in the injection well and three monitoring wells are also provided at 0, 1, 2, 5, 10, 15, and 20 years after the initiation of injection. These were constructed by combining the low-frequency trend of the geophysical models with the high-frequency variations of actual well logs collected in the Kimberlina 1 well that was drilled at the proposed site. Measurements of permeability and pore connectivity were made on cores of Vedder Sandstone, which forms the primary reservoir unit: [CT micro scans](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-ct-micro-scans-of-vedder-formation) and [Industrial CT Images](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-industrial-ct-images-vedder-formation). These measurements provide the range of scales in the otherwise synthetic data set to be as close to a real-world situation as possible. References: Birkholzer, J.T., Zhou, Q., Cortis, A. and Finsterle, S., 2011. A sensitivity study on regional pressure buildup from large-scale CO2 storage projects. Energy Procedia, 4, 4371-4378. Commer, M., and Newman, G.A., 2008. New advances in three-dimensional controlled-source electromagnetic inversion, Geophysical Journal International, 172, 513-535. Gasperikova, E., Appriou, D., Bonneville, A., Feng, Z., Huang, L., Gao, K., Yang, X., Daley, T., 2022, Sensitivity of geophysical techniques for monitoring secondary CO2 storage plumes, Int. J. Greenh. Gas Control, Volume 114, 103585, ISSN 1750-5836, https://doi.org/10.1016/j.ijggc.2022.103585. Moczo, P., J.O. Robertsson and L. Eisner, 2007, The finite-difference time-domain method for modeling of seismic wave propagation: Advances in geophysics, 48, 421-516. Rim, H., and Y. Li, 2015, Advantages of borehole vector gravity in density imaging, Geophysics, 80, G1-G13. Wainwright, H. M.; Finsterle, S.; Zhou, Q.; Birkholzer, J. T., 2013. Modeling the Performance of Large-Scale CO2 Storage Systems: A Comparison of Different Sensitivity Analysis Methods. International Journal of Greenhouse Gas Control, 17, 189205. https://doi.org/10.1016/j.ijggc.2013.05.007, DOI: 10.18141/1603331. Yang, X., Buscheck, T.A., Mansoor, K., Wang, Z., Gao, K., Huang, L., Appriou, D., and Carroll, S.A., 2019. Assessment of geophysical monitoring methods for detection of brine and CO2 leakage in drinking water aquifers, International Journal of Greenhouse Gas Control, 90, 102803, https://doi.org/10.1016/j.ijggc.2019.102803.

CCUS↗
DOE OSTI2019

Formation of Power-law Electron Energy Spectra in Three-dimensional Low- β Magnetic Reconnection

While observations have suggested that power-law electron energy spectra are a common outcome of strong energy release during magnetic reconnection, e.g., in solar flares, kinetic simulations have not been able to provide definite evidence of power-laws in energy spectra of nonrelativistic reconnection. By means of 3D large-scale fully kinetic simulations, we study the formation of power-law electron energy spectra in nonrelativistic low-β reconnection. We find that both the global spectrum integrated over the entire domain and local spectra within individual regions of the reconnection layer have power-law tails with a spectral index p ~ 4 in the 3D simulation, which persist throughout the nonlinear reconnection phase until saturation. In contrast, the spectrum in the 2D simulation rapidly evolves and quickly becomes soft. We show that 3D effects such as self-generated turbulence and chaotic magnetic field lines enable the transport of high-energy electrons across the reconnection layer and allow them to access several main acceleration regions. This leads to a sustained and nearly constant acceleration rate for electrons at different energies. Here, we construct a model that explains the observed power-law spectral index in terms of the dynamical balance between particle acceleration and escape from main acceleration regions, which are defined based upon a threshold for the curvature drift acceleration term. This result could be important for explaining the formation of power-law energy spectrum in solar flares.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2013

Effects of the LBV Primary's Mass-loss Rate on the 3D Hydrodynamics of eta Carinae's Colliding Winds

At the heart of eta Carinae's spectacular "Homunculus" nebula lies an extremely luminous (L(sub Total) greater than approximately 5 × 10(exp 6) solar luminosity) colliding wind binary with a highly eccentric (e approximately 0.9), 5.54-year orbit (Figure 1). The primary of the system, a Luminous Blue Variable (LBV), is our closest (D approximately 2.3 kpc) and best example of a pre-hypernova or pre-gamma ray burst environment. The remarkably consistent and periodic RXTE X-ray light curve surprisingly showed a major change during the system's last periastron in 2009, with the X-ray minimum being approximately 50% shorter than the minima of the previous two cycles1. Between 1998 and 2011, the strengths of various broad stellar wind emission lines (e.g. Halpha, Fe II) in line-of-sight (l.o.s.) also decreased by factors of 1.5 - 3 relative to the continuum2. The current interpretation for these changes is that they are due to a gradual factor of 2 - 4 drop in the primary's mass-loss rate over the last approximately 15 years1, 2. However, while a secular change is seen for a direct view of the central source, little to no change is seen in profiles at high stellar latitudes or reflected off of the dense, circumbinary material known as the "Weigelt blobs"2, 3. Moreover, model spectra generated with CMFGEN predict that a factor of 2 - 4 drop in the primary's mass-loss rate should lead to huge changes in the observed spectrum, which thus far have not been seen. Here we present results from large- (plus or minus 1620 AU) and small- (plus or minus 162 AU) domain, full 3D smoothed particle hydrodynamics (SPH) simulations of eta Car's massive binary colliding winds for three different primary-star mass-loss rates (2.4, 4.8, and 8.5 × 10(exp -4) solar mass/yr). The goal is to investigate how the mass-loss rate affects the 3D geometry and dynamics of eta Car's optically-thick wind and spatially-extended wind-wind collision (WWC) regions, both of which are known sources of observed X-ray, optical, UV, and near-IR emission and absorption. We use two domain sizes in order to better understand how the primary's mass-loss rate influences the various observables that form at different length scales. The 3D simulations provide information important for helping constrain η Car's recent mass-loss history and future state.

lavestigate↗
DOE OSTI2024

Electron and Proton Energization in 3D Reconnecting Current Sheets in Semirelativistic Plasma with Guide Magnetic Field

Abstract Using 3D particle-in-cell simulation, we characterize energy conversion, as a function of guide magnetic field, in a thin current sheet in semirelativistic plasma, with relativistic electrons and subrelativistic protons. There, magnetic reconnection, the drift-kink instability (DKI), and the flux-rope kink instability all compete and interact in their nonlinear stages to convert magnetic energy to plasma energy. We compare fully 3D simulations with 2D in two different planes to isolate reconnection and DKI effects. In zero guide field, these processes yield distinct energy conversion signatures: ions gain more energy than electrons in 2Dxy(reconnection), while the opposite is true in 2Dyz(DKI), and the 3D result falls in between. The flux-rope instability, which occurs only in 3D, allows more magnetic energy to be released than in 2D, but the rate of energy conversion in 3D tends to be lower. Increasing the guide magnetic field strongly suppresses DKI, and in all cases slows and reduces the overall amount of energy conversion; it also favors electron energization through a process by which energy is first stored in the motional electric field of flux ropes before energizing particles. Understanding the evolution of the energy partition thus provides insight into the role of various plasma processes, and is important for modeling radiation from astrophysical sources such as accreting black holes and their jets.

Astronomy & Astrophysics↗
DOE OSTI2020

Optimization of Geometric Perturbations on a Rod Moving Through a High Explosive Target

After completing a study to ensure the simulation results were converged, several high resolution 3D Smoothed Particle Hydrodynamic (SPH) simulations of copper rods impacting a high explosive (LX14) target were performed. This was then formulated into an optimization problem: I wanted to find the optimum shape and location of a perturbation on the rod that would maximize its erosion after it left the target. The shape of the perturbation was modeled as a 2D Gaussian bump and parameterized by its location along the rod axis (z 0 ) and amplitude (A). The final mass of the coherent part of the rod as it leaves the target was used as a metric to represent the erosion of the rod, and the optimization was formulated to maximize this metric with respect to the aforementioned design variables. Due to the expensive nature of the high-fidelity 3D SPH simulations, a surrogate model needed to be chosen so that many function calls to the optimizer would be feasible. Thus, a strategic full factorial sampling plan was chosen to build a dataset, which consisted of 24 high-fidelity simulations. Two surrogate models, a third order polynomial regression model and a Gaussian Process Model, were analyzed using a 14%/86% test/train holdout technique. The root mean square and R2 score of the test set was used to determine the best model, and the third order polynomial regression model was chosen as the surrogate model. Finally, the Nelder-Mead Simplex and Basin-hopping optimization algorithms were implemented, and it was found that the two algorithms gave slightly different optimum values. Nelder-Mead gave an optimum point of [z* 0 ;A*] = [9:9;0:4] and Basin-Hopping gave an optimum value of x* = [z* 0 ;A*] = [9:2;0:1].

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2013

Simulating HFIR Core Thermal Hydraulics Using 3D-2D Model Coupling

A model utilizing interdimensional variable coupling is presented for simulating the thermal hydraulic interactions of the High Flux Isotope Reactor (HFIR) core at Oak Ridge National Laboratory (ORNL). The model s domain consists of a single, explicitly represented three-dimensional fuel plate and a simplified two-dimensional coolant channel slice. In simplifying the coolant channel, and thus the number of mesh points in which the Navier-Stokes equations must be solved, the computational cost and solution time are both greatly reduced. In order for the reduced-dimension coolant channel to interact with the explicitly represented fuel plate, however, interdimensional variable coupling must be enacted along all shared boundaries. The primary focus of this paper is in detailing the collection, storage, passage, and application of variables across this interdimensional interface. Comparisons are made showing the general speed-up associated with this simplified coupled model.

HFIR↗
NASA NTRSDate not supplied

Relevant Environment Additive Construction Technology (REACT)

Project Overview This project is focused on developing technologies that enable construction of a Lunar Safe Haven type structure on the moon. A full scale architectural and structural design will be completed based on lunar conditions and Artemis mission needs. A scaled structure will be 3D printed in simulated lunar environments. Technical Approach Polymer bound regolith composite materials will be developed and characterized for lunar additive construction applications. A full scale architectural and structural design will be completed based on the latest scientific data on lunar environments including radiation, meteoroids, thermal conditions, reduced gravity, and moonquakes. The project will culminate with a demonstration of additive construction in simulated lunar vacuum, thermal, regolith, and UV conditions. Results/Summary Preliminary material specifications have been developed and an initial batch has been produced. A first iteration of the architectural and structural designs have been completed. Hardware for 3D printing in simulated lunar conditions is under development. Contributing Partners AI Space Factory – Winner of the NASA 3D Printed Habitat Centennial Challenge Infusion and Transition Plan On-surface construction of infrastructure is a critical capability of the sustainable phase of the Artemis Program and eventual sustainable human presence on Mars. It provides the ability to create protective shelters on-demand using local resources. The 3D-printing technology will achieve TRL 6 in 1g/vacuum tests with thermal/UV exposure in this project. CLPS missions will be pursued for infusion to demonstrate vertical construction with lunar regolith and conditions. Modeling and simulation will be used to define the pilot-scale shelter construction mission for long-term exposure on the lunar surface to validate the system for Artemis operational deployment.

Lunar Construction↗
DOE OSTI2023

Enhancing Lithium-Ion Battery Aging Simulations: Coupling a High-Resolution, 3D, Grain-Scale Electromechanical Model to a Single-Particle Model

One of the main goals in modeling lithium-ion batteries is to improve/predict longevity and resilience of new chemistries. Unfortunately, this requires simulation of thousands of charge/discharge cycles, which can be rather time consuming depending on the fidelity of the simulation. The purpose of this talk is to discuss a new modeling framework that couples a high-resolution, continuous damage model (CDM) to a single particle model (SPM) resulting in a good combination of speed and fidelity. In previous work, a 3D, continuum-level chemo-mechanical model was developed to investigate cracking within a single cathode particle comprised of hundreds to thousands of randomly oriented grains. The CDM predicted that particle fracture is primarily due to non-ideal grain interactions with slight dependence on high-rate charge demands. Essentially, when neighboring grains were misaligned, they expanded different rates relative to one another leading to high stresses and ultimately the formation of intraparticle cracks. The model predicted that small particles with large grains develop significantly less damage than larger particles with small grains. Finally, the model predicted most of the chemo-mechanical damage accumulates in the first charge after formation. This chemo-mechanical "damage saturation" effect indicated that initial particle fracture occurs within the first few cycles, while long-term cathode degradation is not solely chemo-mechanically induced. This led to a need for simulating fatigue-like mechanism that degrade the battery over longer time scales. In order to reach the time scales, need to resolve fatigue-like degradation, the CDM needs to be complemented by a faster model. Therefore, recent efforts have been focused on using results from the CDM to inform parameters within the SPM. These parameters are homogenization factors that are associated with diffusion, particle radius, and/or exchange current density. By coupling the CDM to the SPM, the aging simulation is broken up into two domains: short-term and long-term degradation. The short-term degradation occurs over a single cycle and is handled by the CDM due of its high fidelity, but relatively expensive computational cost. Such mechanism include break-in crack caused by mismatches in grain orientation. The long-term degradation occurs over tens of cycles and is handled by the SPM due it's computational efficiency. Most of the fatigue-like mechanism fall into this category. The eventual goal of this modeling framework is to upscale to a psudo-2D model allowing for full electrode simulation, which are informed by high-fidelity grain-scale simulations.

electrochemistry↗
NASA NTRS2009

3D Visualization of Monte-Carlo Simulation's of HZE Track Structure and Initial Chemical Species

Heavy ions biophysics is important for space radiation risk assessment [1] and hadron-therapy [2]. The characteristic of heavy ions tracks include a very high energy deposition region close to the track (<20 nm) denoted as the track core, and an outer penumbra region consisting of individual secondary electrons (6-rays). A still open question is the radiobiological effects of 6- rays relative to the track core. Of importance is the induction of double-strand breaks (DSB) [3] and oxidative damage to the biomolecules and the tissue matrix, considered the most important lesions for acute and long term effects of radiation. In this work, we have simulated a 56Fe26+ ion track of 1 GeV/amu with our Monte-Carlo code RITRACKS [4]. The simulation results have been used to calculate the energy depiction and initial chemical species in a "voxelized" space, which is then visualized in 3D. Several voxels with dose >1000 Gy are found in the penumbra, some located ~0.1 mm from the track core. In computational models, the DSB induction probability is calculated with radial dose [6], which may not take into account the higher RBE of electron track ends for DSB induction. Therefore, these simulations should help improve models of DSB induction and our understanding of heavy ions biophysics.

Plante, Ianik↗
NASA NTRSDate not supplied

ROCKE-3D 2.0: An Updated General Circulation Model for Simulating the Climates of Rocky Planets

We present the second generation of ROCKE-3D (Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics), the generalized 3-dimensional General Circulation Model (GCM) for use in Solar System and exoplanetary simulations of rocky planet climates. ROCKE-3D version 2.0 is a descendant of GISS ModelE2.1, the flagship GCM of the NASA Goddard Institute for Space Studies (GISS) used in the most recent Intergovernmental Panel for Climate Change (IPCC) assessment. ROCKE-3D is a continuous effort to expand the capabilities of GISS ModelE to handle a broader range of atmospheric conditions, including different atmospheric planet sizes, gravities, pressures, rotation rates, more diverse chemistries and atmospheric compositions, diverse ocean and land distributions and topographies, and potential basic biosphere functions. We present in this release many more supported configurations which can serve as starting points to simulate terrestrial planets of interest. Two different radiation schemes are supported, the GISS radiation, valid for Earth-like planets, and SOCRATES, which is more generalized but requires more CPU resources. In addition, three different atmospheric compositions are supported, three ocean configurations (prescribed, q-flux, and dynamic), and two resolutions: the medium resolution (4 x 5 degrees in latitude x longitude) used in ROCKE-3D 1.0, and the fine resolution, which has double the resolution in the atmosphere and 4 times the resolution in the ocean. We quantify how the different component choices affect model results, and discuss strengths and limitations of using each component, together with how one can select which component to use. ROCKE-3D is publicly available and tutorial sessions are available for the community, greatly facilitating its use by any interested group.

ROCKE-3D↗
NASA NTRS2018

Analysis of Simulated and Experimental Noise Sources of Boeing 777 Main Gear Model via CLEAN in 3D

Previously obtained experimental and simulated phased microphone array data for the NASA 26%-scale model of a six-wheel main landing gear, with and without a toboggan-shaped noise reduction fairing, were analyzed using the CLEAN technique in three dimensions. The model is a high-fidelity representation of the Boeing 777-200 aircraft main landing gear. The reprocessing of the acoustic data was undertaken to address the deficiencies encountered in the source localization (beamform) maps and the integrated farfield spectra at mid to high frequencies in our previous study, where conventional array processing techniques were applied to the same data sets. Application of the CLEAN approach resulted in higher quality beamform maps with many of the previously observed side lobes either eliminated or suppressed significantly. As a result, integration of the experimentally and computationally based maps showed substantial improvement in the quality of the high-frequency spectral content relative to the corresponding spectra generated via conventional array processing, thus extending the good agreement achieved between the measured and predicted farfield spectra from 8 kHz to 14 kHz in model-scale frequencies. In addition, an examination of the simulated surface pressure fluctuations, off-surface flow field, and three-dimensionally constructed noise sources was conducted to determine the cause of the subtle discrepancies between measured and predicted sound pressure levels that occur in the 1,800 Hz to 4,000 Hz model-scale frequency range.

Ravetta, Patricio↗
DOE OSTI2021

Accurate Effective Stress Measures: Predicting Creep Life for 3D Stresses Using 2D and 1D Creep Rupture Simulations and Data

Operating structural components experience complex loading conditions resulting in 3D stress states. Current design practice estimates multiaxial creep rupture life by mapping a general state of stress to a uniaxial creep rupture correlation using effective stress measures. The data supporting the development of effective stress measures are nearly always only uniaxial and biaxial, as 3D creep rupture tests are not widely available. This limitation means current effective stress measures must extrapolate from 2D to 3D stress states, potentially introducing extrapolation error. In this work, we use a physics-based, crystal plasticity finite element model to simulate uniaxial, biaxial, and triaxial creep rupture. Here, we use the virtual dataset to assess the accuracy of current and novel effective stress measures in extrapolating from 2D to 3D stresses and also explore how the predictive accuracy of the effective stress measures might change if experimental 3D rupture data was available. We confirm these conclusions, based on simulation data, against multiaxial creep rupture experimental data for several materials, drawn from the literature. The results of the virtual experiments show that calibrating effective stress measures using triaxial test data would significantly improve accuracy and that some effective stress measures are more accurate than others, particularly for highly triaxial stress states. Results obtained using experimental data confirm the numerical findings and suggest that a unified effective stress measure should include an explicit dependence on the first stress invariant, the maximum tensile principal stress, and the von Mises stress.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Intermittency, coherent structures and dissipation in plasma turbulence

Collisionless dissipation in turbulent plasmas such as the solar wind and the solar corona has been an intensively studied subject recently, with new insights often emerging from numerical simulation. Here we report results from high resolution, fully kinetic simulations of plasma turbulence in both two (2D) and three (3D) dimensions, studying the relationship between intermittency and dissipation. The simulations show development of turbulent coherent structures, characterized by sheet-like current density structures spanning a range of scales. An approximate dissipation measure is employed, based on work done by the electromagnetic field in the local electron fluid frame. This surrogate dissipation measure is highly concentrated in small subvolumes in both 2D and 3D simulations. Fully kinetic simulations are also compared with magnetohydrodynamics (MHD) simulations in terms of coherent structures and dissipation. The interesting result emerges that the conditional averages of dissipation measure scale very similarly with normalized current density J in 2D and 3D particle-in-cell and in MHD. To the extent that the surrogate dissipation measure is accurate, this result implies that on average dissipation scales as ∼J{sup 2} in turbulent kinetic plasma. Multifractal intermittency is seen in the inertial range in both 2D and 3D, but at scales ∼ion inertial length, the scaling is closer to monofractal.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Micro Reactor Simulation Using the PROTEUS Suite in FY19

Two micro reactor cores were simulated using the MOC solver of PROTEUS: MegaPower for a heat pipe micro reactor and Holos-Quad for a high-temperature gas-cooled micro reactor. Verification of PROTEUS standalone was performed by simulating 2D and 3D core benchmark problems developed based on MegaPower and Holos-Quad. Simulation results indicated that PROTEUS successfully modelled 2D and 3D cores of the MegaPower and Holos-Quad micro reactors and PROTEUS eigenvalues agreed well with the SERPENT Monte Carlo solutions. For a heat pipe cooled micro reactor, multiphysics simulations were performed using PROTEUS / FLUENT / ANLHTP. The coupling system of the three codes were developed using Python-based drivers, which exchange the data (power, temperature, and heat rate) required for the coupling and control the boundary conditions of FLUENT and ANLHTP. The coupled system was qualitatively verified using a 3D unit assembly problem composed of six fuel rods and seven heat pipes, which was developed based on the MegaPower compositions. The steady-state problem was solved using FLUENT / ANLHTP with given asymmetric fuel powers, demonstrating the reasonable convergence of temperatures of 7 heat pipes. Transient simulations were also performed by making one out of 7 heat pipes fail. For the transient, the coupled system of PROTEUS / FLUENT / ANLHTP demonstrated reasonable changes of total power and heat pipe temperatures with time, accounting for temperature feedback effects. In this simulation, no effect of structural change was accounted for, which will be performed using ANSYS-mechanical in future along with further verification with larger or whole-core 3D problems.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

Phase field modeling of chemomechanical fracture of intercalation electrodes: Role of charging rate and dimensionality

We investigate the fracture of Li-ion battery cathodic particles using a thermodynamically consistent phase-field approach that can describe arbitrarily complex crack paths and captures the full coupling between Li-ion diffusion, stress, and fracture. Building on earlier studies that introduced the concept of electrochemical shock, we use this approach to quantify the relationships between stable or unstable crack propagation, flaw size, and C-rate for 2D disks and 3D spherical particles. We find that over an intermediate range of flaw sizes, the critical flaw size for the onset of crack propagation depends on charging rate as an approximate power-law that we derive analytically. This scaling law is quantified in 2D by exhaustive simulations and is also supported by 3D simulations. In addition, our results reveal a significant difference between 2D and 3D geometries. In 2D, cracks propagate deep inside the particle in a rectilinear manner while in 3D they propagate peripherally on the surface and bifurcate into daughter cracks, thereby limiting inward penetration and giving rise to complex crack geometries.

36 MATERIALS SCIENCE↗