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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Characterization of the porous structures of the green body and sintered biomedical titanium scaffolds with micro-computed tomography

The present research was aimed at gaining an understanding of the porous structure changes from the green body through water leaching and sintering to titanium scaffolds. Micro-computed tomography (micro-CT) was performed to generate 3D models of titanium scaffold preforms containing carbamide space-holding particles and sintered scaffolds containing macro- and micro-pores. The porosity values and structural parameters were determined by means of image analysis. The result showed that the porosity values, macro-pore sizes, connectivity densities and specific surface areas of the titanium scaffolds sintered at 1200 °C for 3 h did not significantly deviate from those of the green structures with various volume fractions of the space holder. Titanium scaffolds with a maximum specific surface area could be produced with an addition of 60–65 vol% carbamide particles to the matrix powder. The connectivity of pores inside the scaffold increased with rising volume fraction of the space holder. The shrinkage of the scaffolds prepared with > 50 vol% carbamide space holder, occurring during sintering, was caused by the reductions of macro-pore sizes and micro-pore sizes as well as the thickness of struts. In conclusion, the final porous structural characteristics of titanium scaffolds could be estimated from those of the green body. - Highlights: •Porous structures of green body and sintered titanium scaffolds was studied. •Porous structures of both samples were quantitatively characterized with micro-CT. •Porous structures of scaffolds could be controlled from the green body. •Shrinkage mechanisms of titanium scaffolds during sintering was established.

36 MATERIALS SCIENCE↗
DOE OSTI2021

An efficient method to estimate the probability density of seismic Green's functions

We present a computationally efficient method to approximate the probability distribution of seismic Green's functions given the uncertainty of an Earth model. The method is based on the Karhunen-Loève (KL) theorem and an approximation of the Green's function (or seismogram) covariance. Using Monte Carlo (MC) simulations as a control case, we demonstrate that our KL-based method can accurately reproduce a probability distribution of seismograms that results from an uncertain Earth model for a MC-derived seismogram covariance. We then describe a method to estimate the covariance of the seismograms resulting from those Earth models that is not based on MC simulations. We use the estimated Green's function covariance in conjunction with our KL-based method to produce a Green's function probability distribution, and compare that distribution to a Green's function probability distribution produced using a MC finite difference method. We find that the Green's function probability distribution approximated using our KL-based method generally mimics that produced using the MC simulations, especially for direct-arriving body waves. However the accuracy of the KL-based method generally decreases for later times in the simulated Green's function distribution.

58 GEOSCIENCES↗
DOE OSTI2021

Discrete Green’s functions and spectral graph theory for computationally efficient thermal modeling

Here, this work concerns solutions of the heat equation with the spectral graph method, for which the temperature is defined at discrete points in the domain and the spatial relationship among the points is described by a graph. The heat equation on the graph is solved using matrix techniques involving the eigenvectors and eigenvalues of the Laplacian matrix. The spectral graph approach precludes the computationally intensive meshing and numerous time-integration steps of the finite element method. In the present work, the spectral graph method is extended to include heat loss at the boundaries with a generalized boundary condition, and physics-based edge weights are introduced which simplify the calibration process. From this approach a discrete Green’s function is defined which allows for solutions under a variety of heating conditions including: space-varying initial conditions; time-and-space varying internal heating; and, time-and-space-varying heating at boundaries of type 1 (Dirichlet), type 2 (Neumann) and type 3 (Robin). Results are provided for benchmark heat transfer problems in one spatial dimension and in three spatial dimensions, and verification is provided by comparison with exact analytical solutions and finite difference solutions. The spectral graph method converges within 0.4% error of the analytical solution. The practical utility of the approach is demonstrated by thermal simulation of a multilayer additive manufacturing process. The spectral graph results are compared to experimentally-obtained temperature data for two metal parts, with error less than 5% of the experimental measurements, with computation time less than one minute on a desktop computer.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Improvement of Numerical Methods in Pronghorn

During the fiscal year of 2021, the finite-volume method (FVM) was deployed in Pronghorn to provide improved efficiency, stability, and accuracy for coarse-mesh, thermal-hydraulics problems. While the main goals of fiscal year 2021 were met, several issues emerged from the early deployment of the finite-volume method in Pronghorn. These issues were: The compressible and incompressible formulations that were implemented are inadequate for many nuclear reactor flow problems; Omission of terms accounting for the porosity and Darcy-Forchheimer body force discontinuities in the Rhie-Chow interpolation lead to oscillations in pressure and velocity at these discontinuities; The FVM lacks a correction for non-orthogonal grids for computing accurate pressure gradient leading to loss of accuracy in regions with skewed elements; The FVM currently uses a monolithic solver. Monolithic solvers have issues dealing with the saddle-point nature of the discretized fluid equations. The result are bad convergence if direct factorization is not used and large memory consumption when direct factorization is used. These four issues are addressed in this report. In particular, we report the completion of the following task: Implementation of a weakly compressible formulation in the MOOSE Navier-Stokes module; Implementation of Moukalled’s method for including body forces in the RCI. Additionally, we identified the need to smooth the porosity using Moukalled’s face-cell smoothing operator; Implementation of a non-orthogonal correction for the Green-Gauss gradient computation; Preliminary implementation of a SIMPLE segregated solver.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Geomechanical response due to nonisothermal fluid injection into a reservoir

The geomechanical response of a porous reservoir due to injection of fluid can result from a complex interplay between the changes in porepressure and temperature near the wellbore. As a result, predictions are usually made using either simplified analytical models, which may apply unrealistic assumptions in order to produce a tractable model, or detailed numerical simulations that can be computationally expensive.

58 GEOSCIENCES↗
DOE OSTI2019

Volume Flow Rate Estimation for Small Explosions at Mt. Etna, Italy, From Acoustic Waveform Inversion

Rapid assessment of the volume and the rate at which gas and pyroclasts are injected into the atmosphere during volcanic explosions is key to effective eruption hazard mitigation. Here, we use data from a dense infrasound network deployed in 2017 on Mt. Etna, Italy, to estimate eruptive volume flow rates (VFRs) during small gas-and-ash explosions. We use a finite-difference time-domain approximation to compute the acoustic Green's functions and perform a full waveform inversion for a multipole source, combining monopole and horizontal dipole terms. The inversion produces realistic estimates of VFR, on the order of 4 × 10 4 m 3 /s and well-defined patterns of source directivity. This is the first application of acoustic waveform inversion at Mt. Etna. Our results demonstrate that acoustic waveform inversion is a mature and robust tool for assessment of source parameters and holds potential as a tool to provide rapid estimates of VFR in near real time.

58 GEOSCIENCES↗
DOE OSTI2022

A mixed, unified forward/inverse framework for earthquake problems: fault implementation and coseismic slip estimate

SUMMARY We introduce a new finite-element (FE) based computational framework to solve forward and inverse elastic deformation problems for earthquake faulting via the adjoint method. Based on two advanced computational libraries, FEniCS and hIPPYlib for the forward and inverse problems, respectively, this framework is flexible, transparent and easily extensible. We represent a fault discontinuity through a mixed FE elasticity formulation, which approximates the stress with higher order accuracy and exposes the prescribed slip explicitly in the variational form without using conventional split node and decomposition discrete approaches. This also allows the first order optimality condition, that is the vanishing of the gradient, to be expressed in continuous form, which leads to consistent discretizations of all field variables, including the slip. We show comparisons with the standard, pure displacement formulation and a model containing an in-plane mode II crack, whose slip is prescribed via the split node technique. We demonstrate the potential of this new computational framework by performing a linear coseismic slip inversion through adjoint-based optimization methods, without requiring computation of elastic Green’s functions. Specifically, we consider a penalized least squares formulation, which in a Bayesian setting—under the assumption of Gaussian noise and prior—reflects the negative log of the posterior distribution. The comparison of the inversion results with a standard, linear inverse theory approach based on Okada’s solutions shows analogous results. Preliminary uncertainties are estimated via eigenvalue analysis of the Hessian of the penalized least squares objective function. Our implementation is fully open-source and Jupyter notebooks to reproduce our results are provided. The extension to a fully Bayesian framework for detailed uncertainty quantification and non-linear inversions, including for heterogeneous media earthquake problems, will be analysed in a forthcoming paper.

58 GEOSCIENCES↗
DOE OSTI2018

Thermal conductivity of InN with point defects from first principles

We present ab initio calculations of thermal conductivity of InN with vacancies and substitutional defects using a full solution of the Peierls-Boltzmann transport equation. Our parameter-free calculations are in good agreement with experimental measurements demonstrating the predictive power of this approach. Phonon-defect scattering rates are computed from a Green's function methodology that is nonperturbative and includes interatomic force constant variance induced near the defects. Restricting calculations to first-order perturbation approaches can overestimate optic phonon scattering rates by nearly three orders of magnitude. On the other hand, neglecting the force variance weakens the scattering rates by about an order of magnitude, mostly in the low-frequency region below 2 THz. Here, this work elucidates important properties of phonon-defect scattering in thermal transport and demonstrates the predictive power of the coupling of Peierls-Boltzmann transport, Green's function methods, and density functional theory.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Natively Periodic Fast Multipole Method: Approximating the Optimal Green’s Function

The fast multipole method (FMM) obeys periodic boundary conditions "natively" if it uses a periodic Green's function for computing the multipole expansion in the interaction zone of each FMM oct-tree node. One can define the "optimal" Green's function for such a method that results in the numerical solution that converges to the equivalent particle-mesh (PM) solution in the limit of sufficiently high order of multipoles. A discrete functional equation for the optimal Green's function can be derived, but is not practically useful as methods for its solution are not known. Instead, this paper presents an approximation for the optimal Green's function that is accurate to better than 10 -3 in ${L}_{\mathrm{MAX}}$ norm and 10 -4 in L 2 norm for practically useful multipole counts. Such an approximately optimal Green's function offers a practical way for implementing the FMM with periodic boundary conditions natively, without the need to compute lattice sums or to rely on hybrid FMM-PM approaches.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2012

A DATABASE OF >20 keV ELECTRON GREEN'S FUNCTIONS OF INTERPLANETARY TRANSPORT AT 1 AU

We use interplanetary transport simulations to compute a database of electron Green's functions, i.e., differential intensities resulting at the spacecraft position from an impulsive injection of energetic (>20 keV) electrons close to the Sun, for a large number of values of two standard interplanetary transport parameters: the scattering mean free path and the solar wind speed. The nominal energy channels of the ACE, STEREO, and Wind spacecraft have been used in the interplanetary transport simulations to conceive a unique tool for the study of near-relativistic electron events observed at 1 AU. In this paper, we quantify the characteristic times of the Green's functions (onset and peak time, rise and decay phase duration) as a function of the interplanetary transport conditions. We use the database to calculate the FWHM of the pitch-angle distributions at different times of the event and under different scattering conditions. This allows us to provide a first quantitative result that can be compared with observations, and to assess the validity of the frequently used term beam-like pitch-angle distribution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Microscopic optical potentials for medium-mass isotopes derived at the first order of Watson multiple-scattering theory

We perform a first-principles calculation of optical potentials for nucleon elastic scattering off medium-mass isotopes. Fully based on a saturating chiral Hamiltonian, the optical potentials are derived by folding nuclear density distributions computed with self-consistent Green's function theory with a nucleon-nucleon t matrix computed with a consistent chiral interaction. The dependence on the folding interaction as well as the convergence of the target densities are investigated. Numerical results are presented and discussed for differential cross sections and analyzing powers, with focus on elastic proton scattering off calcium and nickel isotopes. Our optical potentials generally show a remarkable agreement with the available experimental data for laboratory energies in the range 65–200 MeV. We study the evolution of the scattering observables with increasing proton-neutron asymmetry by computing theoretical predictions of the cross section and analyzing power over the calcium and nickel isotopic chains. Published by the American Physical Society 2024

Physics↗
DOE OSTI2014

Shear viscosity of the quark-gluon plasma in a kinetic theory approach

One of the main results of heavy ions collision (HIC) at relativistic energy experiments is the very small shear viscosity to entropy density ratio of the Quark-Gluon Plasma, close to the conjectured lower bound η/s=1/4π for systems in the infinite coupling limit. Transport coefficients like shear viscosity are responsible of non-equilibrium properties of a system: Green-Kubo relations give us an exact expression to compute these coefficients. We compute shear viscosity numerically using Green-Kubo relation in the framework of Kinetic Theory solving the relativistic transport Boltzmann equation in a finite box with periodic boundary conditions. We investigate a system of particles interacting via anisotropic and energy dependent cross-section in the range of temperature of interest for HIC. Green-Kubo results are in agreement with Chapman-Enskog approximation while Relaxation Time approximation can underestimates the viscosity of a factor 2. The correct analytic formula for shear viscosity can be used to develop a transport theory with a fixed η/s and have a comparison with physical observables like elliptic flow.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

An Approach for Simulating Transport of Nonspherical, Sublimating Particles in Rarefied Gas Flows via the Direct Simulation Monte Carlo Method

This paper extends the particle Green’s function approach of Gallis et al. [Phys. Fluids 13, 3482–3492 (2001)] to compute the force and heat transfer on nonspherical, sublimating particles in rarefied gas flows. Green’s functions are derived for rods and plates, which are representative of ice particle shapes, and a numerical procedure is developed for computing the Green’s functions for a general discretized convex shape. Additionally, a sublimation model is developed to simulate the evolution of ice particles in rarefied gas flows. These models are implemented in a direct simulation Monte Carlo code and demonstrated for the case of ice-particle-laden hypersonic flow over a ramp.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Machine learning nonequilibrium electron forces for spin dynamics of itinerant magnets

Abstract We present a generalized potential theory for conservative as well as nonconservative forces for the Landau-Lifshitz magnetization dynamics. Importantly, this formulation makes possible an elegant generalization of the Behler-Parrinello machine learning (ML) approach, which is a cornerstone of ML-based quantum molecular dynamics methods, to the modeling of force fields in adiabatic spin dynamics of out-of-equilibrium itinerant magnetic systems. We demonstrate our approach by developing a deep-learning neural network that successfully learns the electron-mediated exchange fields in a driven s-d model computed from the nonequilibrium Green’s function method. We show that dynamical simulations with forces predicted from the neural network accurately reproduce the voltage-driven domain-wall propagation. Our work also lays the foundation for ML modeling of spin transfer torques and opens a avenue for ML-based multi-scale modeling of nonequilibrium dynamical phenomena in itinerant magnets and spintronics.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Phonon thermal conductance across GaN-AlN interfaces from first principles

The vibrational thermal conductances (G) across GaN-AlN interfaces are computed using a nonequilibrium Green's function formalism in the harmonic limit with bulk and interfacial interatomic force constants (IFCs) fully from density functional theory. Several numerical methods and supercell configurations are employed to examine the sensitivity of G to variances of IFCs. In particular, the effects of supercell size, the enforcement of symmetry constraints, and truncation of IFCs near the interface, and atomic relaxation on phonon transmission and conductance are explored. Our fully first-principles calculations are compared with common approximations and measured G values inferred from thermal conductivity measurements for GaN-AlN superlattices. Here, our calculated value, G~300MWm -2 K -1 , is nearly half that from measurements. This discrepancy is critically analyzed in terms of the physical assumptions of the calculations and the derivation of the experimental values. This work provides guidelines to determine “physically correct” sets of interfacial IFCs from first principles for thermal conductance calculations using minimal computational resources. It also contributes toward developing predictive calculations and a more complete picture of thermal conduction across interfaces, a step toward first-principles multiscale thermal transport.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Harvest Initiated Volatile Organic Compound Emissions from In-Field Tall Wheatgrass

While crop and grassland usage continues to increase, the full diversity of plant-specific volatile organic compounds (VOCs) emitted from these ecosystems, including their implications for atmospheric chemistry and carbon cycling, remains poorly understood. It is particularly important to investigate VOCs in the context of potential biofuels: aside from the implications of largescale land use, harvest may shift both the flux and speciation of emitted VOCs. To this point, we evaluate the diversity of VOCs emitted both pre and postharvest from “Alkar” tall wheatgrass (Thinopyrum ponticum), a candidate biofuel that exhibits greater tolerance to frost and saline land compared to other grass varieties. Mature plants grown under field conditions (n = 6) were sampled for VOCs both pre- and postharvest (October 2022). Via hierarchical clustering of emitted VOCs from each plant, we observe distinct “volatilomes” (diversity of VOCs) specific to the pre- and postharvest conditions despite plant-to-plant variability. In total, 50 VOCs were found to be unique to the postharvest tall wheatgrass volatilome, and these unique VOCs constituted a significant portion (26%) of total postharvest signal. While green leaf volatiles (GLVs) dominate the speciation of postharvest emissions (e.g., 54% of unique postharvest VOC signal was due to 1-penten-3-ol), we demonstrate novel postharvest VOCs from tall wheatgrass that are under characterized in the context of carbon cycling and atmospheric chemistry (e.g., 3-octanone). Continuing evaluations will quantitatively investigate tall wheatgrass VOC fluxes, better informing the feasibility and environmental impact of tall wheatgrass as a biofuel.

09 BIOMASS FUELS↗