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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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Goal-oriented adaptive modeling of random heterogeneous media and model-based multilevel Monte Carlo methods
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Modeling molecular interactions of sodium montmorillonite clay with 3D kerogen models
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Modeling aqueous multivalent polyelectrolytes systems with polyelectrolyte NRTL model
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Hydrogen Tunneling in Enzymes and Biomimetic Models
Hydrogen transfer reactions play an important role throughout chemistry and biology. In general, hydrogen transfer reactions encompass proton and hydride transfer, which are associated with the transfer of a positively or negatively charged species, respectively, and proton-coupled electron transfer (PCET), which corresponds to the net transfer of one electron and one proton in the simplest case. Such PCET reactions can occur by either a sequential mechanism, in which the proton or electron transfers first, or a concerted mechanism, in which the electron and proton transfer in a single kinetic step with no stable intermediate. Furthermore, concerted PCET reactions can be subdivided into hydrogen atom transfer (HAT), which corresponds to the transfer of an electron and proton between the same donor and acceptor (i.e., the transfer of a predominantly neutral species), and electron-proton transfer (EPT), which corresponds to the transfer of an electron and proton between different donors and acceptors, possibly even in different directions. In all of these types of hydrogen transfer reactions, hydrogen tunneling could potentially play a significant role. The biomimetic portion was supported as part of the Center for Molecular Electrocatalysis, an Energy Frontier Research Center funded by the U. S. Department of Energy, Office of Science, Office of Basic Energy Sciences.
Growth and modelling of spherical crystalline morphologies of molecular materials
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Structure-mining: screening structure models by automated fitting to the atomic pair distribution function over large numbers of models
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Evaluation of Solar Optical Modeling Tools for Modeling Complex Receiver Geometries.
Abstract not provided.
Modeling Electrochemical Decomposition of Fluoroethylene Carbonate on Silicon Anode Surfaces in Lithium Ion Batteries
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Non-Equilibrium Law-of-the-wall Modeling for Improved Heat Transfer Predictions: Model Development and Validation.
Abstract not provided.
What’s Driving Uncertainty? The Model or the Model Parameters (What’s Driving Uncertainty? The influences of model and model parameters in data analysis)
Here, one of the substantial improvements to the practice of data analysis in recent decades is the change from reporting just a point estimate for a parameter or characteristic, to now including a summary of uncertainty for that estimate. Understanding the precision of the estimate for the quantity of interest provides better understanding of what to expect and how well we are able to predict future behavior from the process. For example, when we report a sample average as an estimate of the population mean, it is good practice to also provide a confidence interval (or credible interval, if you are doing a Bayesian analysis) to accompany that summary. This helps to calibrate what ranges of values are reasonable given the variability observed in the sample and the amount of data that were included in producing the summary.
Capturing the two-way hydromechanical coupling effect on fluid-driven fracture in a dual-graph lattice beam model
Fluid-driven fractures of brittle rock is simulated via a dual-graph lattice model. The new discrete hydromechanical model incorporates a two-way coupling mechanism between the discrete element model and the flow network. Through adopting an operator-split algorithm, the coupling model is able to replicate the transient poroelasticity coupling mechanism and the resultant Mandel-Cryer hydromechanical coupling effect in a discrete mechanics framework. As crack propagation, coalescence and branching are all path-dependent and irreversible processes, capturing this transient coupling effect is important for capturing the essence of the fluid-driven fracture in simulations. Injection simulations suggest that the onset and propagation of fractures is highly sensitive to the ratio between the injection rate and the effective permeability. Moreover, we show that in a permeable rock, the borehole breakdown pressure, the pressure at which fractures start to grow from the borehole, depends on both the given ratio between injection rate and permeability and the Biot coefficient.
Influence of multi-species solute transport on modeling of hydrated Portland cement leaching in strong nitrate solutions
The differences between the predictions of Fickian diffusion and Nernst-Planck electro-diffusion based reactive transport models are investigated in the context of an important practical problem – leaching of Portland cement in strong nitrate porewater solutions under saturated conditions. Numerical results are presented for three distinct porewater solutions: deionized water, ammonium nitrate solution, and diluted porewater from a cementitious low-activity nuclear waste form. Solute concentrations predicted by the two transport models show significant differences: as much as a factor of two for ammonium nitrate leaching and as much as a factor of four for waste form leaching; whereas, negligible differences are observed for deionized water leaching. The major conclusion is that Fickian diffusion may be accurate enough for deionized water leaching, but electro-diffusion should be considered in the reactive solute transport modeling of ammonium nitrate decalcification and in the degradation modeling of cementitious materials exposed to nuclear waste form solutions.
Smoothed particle hydrodynamics model for Landau-Lifshitz-Navier-Stokes and advection-diffusion equations
We propose a novel smoothed particle hydrodynamics (SPH) discretization of the fully coupled Landau-Lifshitz-Navier-Stokes (LLNS) and stochastic advection-diffusion equations. The accuracy of the SPH solution of the LLNS equations is demonstrated by comparing the scaling of velocity variance and the self-diffusion coefficient with kinetic temperature and particle mass obtained from the SPH simulations and analytical solutions. The spatial covariance of pressure and velocity fluctuations is found to be in a good agreement with theoretical models. To validate the accuracy of the SPH method for coupled LLNS and advection-diffusion equations, we simulate the interface between two miscible fluids. We study formation of the so-called “giant fluctuations” of the front between light and heavy fluids with and without gravity, where the light fluid lies on the top of the heavy fluid. We find that the power spectra of the simulated concentration field are in good agreement with the experiments and analytical solutions. In the absence of gravity, the power spectra decay as the power −4 of the wavenumber—except for small wavenumbers that diverge from this power law behavior due to the effect of finite domain size. Gravity suppresses the fluctuations, resulting in much weaker dependence of the power spectra on the wavenumber. Finally, the model is used to study the effect of thermal fluctuation on the Rayleigh-Taylor instability, an unstable dynamics of the front between a heavy fluid overlaying a light fluid. The front dynamics is shown to agree well with the analytical solutions.
Modeling the SHG activities of diverse protein crystals
The origins of the diversity in the SHG signal from protein crystals are investigated and potential protein-crystal coverage by SHG microscopy is assessed. A symmetry-additive ab initio model for second-harmonic generation (SHG) activity of protein crystals was applied to assess the likely protein-crystal coverage of SHG microscopy. Calculations were performed for 250 proteins in nine point-group symmetries: a total of 2250 crystals. The model suggests that the crystal symmetry and the limit of detection of the instrument are expected to be the strongest predictors of coverage of the factors considered, which also included secondary-structural content and protein size. Much of the diversity in SHG activity is expected to arise primarily from the variability in the intrinsic protein response as well as the orientation within the crystal lattice. Two or more orders-of-magnitude variation in intensity are expected even within protein crystals of the same symmetry. SHG measurements of tetragonal lysozyme crystals confirmed detection, from which a protein coverage of ∼84% was estimated based on the proportion of proteins calculated to produce SHG responses greater than that of tetragonal lysozyme. Good agreement was observed between the measured and calculated ratios of the SHG intensity from lysozyme in tetragonal and monoclinic lattices.
Quantifying the impact of material-model error on macroscale quantities-of-interest using multiscale a posteriori error-estimation techniques
An a posteriori error-estimation framework is introduced to quantify and reduce modeling errors resulting from approximating complex mesoscale material behavior with a simpler macroscale model. Such errors may be prevalent when modeling welds and additively manufactured structures, where spatial variations and material textures may be present in the microstructure. We consider a case where a <100> fiber texture develops in the longitudinal scanning direction of a weld. Transversely isotropic elastic properties are obtained through homogenization of a microstructural model with this texture and are considered the reference weld properties within the error-estimation framework. Conversely, isotropic elastic properties are considered approximate weld properties since they contain no representation of texture. Errors introduced by using isotropic material properties to represent a weld are assessed through a quantified error bound in the elastic regime. Lastly, an adaptive error reduction scheme is used to determine the optimal spatial variation of the isotropic weld properties to reduce the error bound.