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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Predictive Large-Eddy Simulation of Supercritical-Pressure Reactive Flows in the Cold Ignition Regime

This report describes a one-year study performed under DOE sponsorship, continuing the investigation of high-pressure turbulent reactive flows. The interest is in the effect of the chemical species distribution in high-pressure turbulent flows in the presence of strong temperature gradients as would occur during reactions in realistic flows. The prime example of such flows are boundary layers in which the wall is at a lower temperature than that of the fluid, as would be the case in Diesel engines. Previous DOE BES work in the program further highlighted the importance of the boundary layer as a configuration for fundamental studies: soot formation in boundary layers is still a problem poorly understood and depends on the availability of particular chemical species at that location, and when boundary layer Large Eddy Simulations results were compared with measurements, the agreement was unfavorable, showing that this important ‘unit’ problem is not well understood. To understand this unit problem, modeling and Direct Numerical Simulations of this unit problem were conducted for the simplest possible multispecies system, that is a binary-species system. The results discovered a new phenomenon, that is, Soret effect induced uphill diffusion. The far-reaching implication is that through an imposed wall/fluid temperature difference it is possible to control the distribution of the species in the boundary layer. Because the results have been documented in one paper published in the refereed literature, and also in conference papers, this final report is in the form of an Executive Summary succinctly describing the results and putting them in perspective with respect to existing information. The refereed and conference papers published are individually listed as Appendices and attached to this report. One manuscript is still in progress and is thus not listed.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2016

A radial basis function Galerkin method for inhomogeneous nonlocal diffusion

We introduce a discretization for a nonlocal diffusion problem using a localized basis of radial basis functions. The stiffness matrix entries are assembled by a special quadrature routine unique to the localized basis. Combining the quadrature method with the localized basis produces a well-conditioned, sparse, symmetric positive definite stiffness matrix. We demonstrate that both the continuum and discrete problems are well-posed and present numerical results for the convergence behavior of the radial basis function method. As a result, we explore approximating the solution to anisotropic differential equations by solving anisotropic nonlocal integral equations using the radial basis function method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Multidimensional Cyclic Voltammetry Simulations of Pseudocapacitive Electrodes with a Conducting Nanorod Scaffold

This paper aims to understand the effect of nanoarchitecture on the performance of pseudocapacitive electrodes consisting of conducting scaffold coated with pseudocapacitive material. To do so, two-dimensional numerical simulations of ordered conducting nanorods coated with a thin film of pseudocapacitive material were performed. The simulations reproduced three-electrode cyclic voltammetry measurements based on a continuum model derived from first principles. Two empirical approaches commonly used experimentally to characterize the contributions of surface-controlled and diffusion-controlled charge storage mechanisms to the total current density with respect to scan rate were theoretically validated for the first time. Moreover, the areal capacitive capacitance, attributed to EDL formation, remained constant and independent of electrode dimensions, at low scan rates. However, at high scan rates, it decreased with decreasing conducting nanorod radius and increasing pseudocapacitive layer thickness due to resistive losses. By contrast, the gravimetric faradaic capacitance, due to reversible faradaic reactions, decreased continuously with increasing scan rate and pseudocapacitive layer thickness but was independent of conducting nanorod radius. Note that the total gravimetric capacitance predicted numerically featured values comparable to experimental measurements. Finally, an optimum pseudocapacitive layer thickness that maximizes total areal capacitance was identified as a function of scan rate and confirmed by scaling analysis.

42 ENGINEERING↗
DOE OSTI2020

An optimization-based approach to parameter learning for fractional type nonlocal models

Nonlocal operators of fractional type are a popular modeling choice for applications that do not adhere to classical diffusive behavior; however, one major challenge in nonlocal simulations is the selection of model parameters. In this work we propose an optimization-based approach to parameter identification for fractional models with an optional truncation radius. We formulate the inference problem as an optimal control problem where the objective is to minimize the discrepancy between observed data and an approximate solution of the model, and the control variables are the fractional order and the truncation length. For the numerical solution of the minimization problem we propose a gradient-based approach, where we enhance the numerical performance by an approximation of the bilinear form of the state equation and its derivative with respect to the fractional order. Several numerical tests in one and two dimensions illustrate the theoretical results and show the robustness and applicability of our method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

A mathematical and numerical framework for the analysis of compressible thermal convection in gases at very high temperatures

The relevance of non-equilibrium phenomena, nonlinear behavior, gravitational effects and fluid compressibility in a wide range of problems related to high-temperature gas-dynamics, especially in thermal, mechanical and nuclear engineering, calls for a concerted approach using the tools of the kinetic theory of gases, statistical physics, quantum mechanics, thermodynamics and mathematical modeling in synergy with advanced numerical strategies for the solution of the Navier–Stokes equations. The reason behind such a need is that in many instances of relevance in this field one witnesses a departure from canonical models and the resulting inadequacy of standard CFD approaches, especially those traditionally used to deal with thermal (buoyancy) convection problems. Starting from microscopic considerations and typical concepts of molecular dynamics, passing through the Boltzmann equation and its known solutions, we show how it is possible to remove past assumptions and elaborate an algorithm capable of targeting the broadest range of applications. Moving beyond the Boussinesq approximation, the Sutherland law and the principle of energy equipartition, the resulting method allows most of the fluid properties (density, viscosity, thermal conductivity, heat capacity and diffusivity, etc.) to be derived in a rational and natural way while keeping empirical contamination to the minimum. Special attention is deserved as well to the well-known pressure issue. With the application of the socalled multiple pressure variables concept and a projection-like numerical approach, difficulties with such a term in the momentum equation are circumvented by allowing the hydrodynamic pressure to decouple from its thermodynamic counterpart. The final result is a flexible and modular framework that on the one hand is able to account for all the molecule (translational, rotational and vibrational) degrees of freedom and their effective excitation, and on the other hand can guarantee adequate interplay between molecular and macroscopic-level entities and processes. Performances are demonstrated by computing some incompressible and compressible benchmark test cases for thermal (gravitational) convection, which are then extended to the high-temperature regime taking advantage of the newly developed features.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Collisional transport across the magnetic field in drift-fluid models

Drift ordered fluid models are widely applied in studies of low-frequency turbulence in the edge and scrape-off layer regions of magnetically confined plasmas. Here, we show how collisional transport across the magnetic field is self-consistently incorporated into drift-fluid models without altering the drift-fluid energy integral. We demonstrate that the inclusion of collisional transport in drift-fluid models gives rise to diffusion of particle density, momentum, and pressures in drift-fluid turbulence models and, thereby, obviates the customary use of artificial diffusion in turbulence simulations. We further derive a computationally efficient, two-dimensional model, which can be time integrated for several turbulence de-correlation times using only limited computational resources. The model describes interchange turbulence in a two-dimensional plane perpendicular to the magnetic field located at the outboard midplane of a tokamak. The model domain has two regions modeling open and closed field lines. The model employs a computational expedient model for collisional transport. Numerical simulations show good agreement between the full and the simplified model for collisional transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Analytical closure to the spatially-filtered Euler equations for shock-dominated flows

To ensure numerical stability in the vicinity of shocks, a variety of methods have been used, including shock-capturing schemes such as weighted essentially non-oscillatory schemes, as well as the addition of artificial diffusivities to the governing equations. Centered finite difference schemes are often avoided near discontinuities due to the tendency for significant oscillations. However, such schemes have desirable conservation properties compared to many shock-capturing schemes. The objective of this work is to derive all necessary viscous/diffusion terms from first principles and then demonstrate the performance of these analytical terms within a centered differencing framework. The physical Euler equations are spatially-filtered with a Gaussian-like filter. Sub-filter scale (SFS) terms arise in the momentum and energy equations. Analytical closure is provided for each of them by leveraging the jump conditions for a shock. No SFS terms are present in the continuity or species equations. Here, this approach is tested for several problems involving shocks in one and two dimensions. Implemented within a centered difference code, the SFS terms perform well for a range of flow conditions without introducing excessive diffusion.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Multilevel Sequential Monte Carlo Samplers for Normalizing Constants

This article considers the sequential Monte Carlo (SMC) approximation of ratios of normalizing constants associated to posterior distributions which in principle rely on continuum models. Therefore, the Monte Carlo estimation error and the discrete approximation error must be balanced. A multilevel strategy is utilized to substantially reduce the cost to obtain a given error level in the approximation as compared to standard estimators. Two estimators are considered and relative variance bounds are given. The theoretical results are numerically illustrated for two Bayesian inverse problems arising from elliptic partial differential equations (PDEs). The examples involve the inversion of observations of the solution of (i) a 1-dimensional Poisson equation to infer the diffusion coefficient, and (ii) a 2-dimensional Poisson equation to infer the external forcing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

On the Equilibrium Electrostatic Potential and Light-Induced Charge Redistribution in Halide Perovskite Structures

Lead halide perovskites are semiconductor materials which are employed as nonintentionally doped absorbers inserted between two selective carrier transport layers (SCTL), realizing a p-i-n or n-i-p heterojunction. In our study, we have developed and investigated a lateral device, based on methylammonium lead iodide (MAPbI3) in which the p-i-n heterojunction develops in the horizontal direction. Our research suggests that the effective doping level in the MAPbI3 film should be very low, below 1012 cm-3. Along the vertical direction, this doping level is not enough to screen the electric field of the buried heterojunction with the SCTL. The perovskite work function is therefore affected by the work function of the SCTL underneath. From drift-diffusion simulations, we show that intrinsic perovskite-SCTL structures develop mV range surface photovoltages (SPVs) under continuous illumination. However, perovskite-SCTL structures can develop SPVs of hundreds of mV, as confirmed by our measurements. We therefore analyzed the compatibility between low doping and low defect densities in the perovskite layer and such high SPV values using numerical modeling. It is shown that these high SPV values could originate from electronic processes due to large band offsets in the buried perovskite-SCTL heterojunctions, or at the SCTL-transparent conductive oxide (TCO) buried heterojunction. However, such electronic processes can hardly explain the long SPV persistence after switching off the illumination.

defects↗
DOE OSTI2016

Are oxygen limitations under recognized regulators of organic carbon turnover in upland soils?

Understanding the processes controlling organic matter (OM) stocks in upland soils, and the ability to management them, is crucial for maintaining soil fertility and carbon (C) storage as well as projecting change with time. OM inputs are balanced by the mineralization (oxidation) rate, with the difference determining whether the system is aggrading, degrading or at equilibrium with reference to its C storage. In upland soils, it is well recognized that the rate and extent of OM mineralization is affected by climatic factors (particularly temperature and rainfall) in combination with OM chemistry, mineral–organic associations, and physical protection. Here we examine evidence for the existence of persistent anaerobic microsites in upland soils and their effect on microbially mediated OM mineralization rates. Further, we corroborate long-standing assumptions that residence times of OM tend to be greater in soil domains with limited oxygen supply (aggregates or peds). Moreover, the particularly long residence times of reduced organic compounds (e.g., aliphatics) are consistent with thermodynamic constraints on their oxidation under anaerobic conditions. Incorporating (i) pore length and connectivity governing oxygen diffusion rates (and thus oxygen supply) with (ii) ‘hot spots’ of microbial OM decomposition (and thus oxygen consumption), and (iii) kinetic and thermodynamic constraints on OM metabolism under anaerobic conditions will thus improve conceptual and numerical models of C cycling in upland soils. We conclude that constraints on microbial metabolism induced by oxygen limitations act as a largely unrecognized and greatly underestimated control on overall rates of C oxidation in upland soils.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

A comparison of Redlich-Kister polynomial and cubic spline representations of the chemical potential in phase field computations

Free energies play a central role in many descriptions of equilibrium and non-equilibrium properties of solids. Continuum partial differential equations (PDEs) of atomic transport, phase transformations and mechanics often rely on first and second derivatives of a free energy function. The stability, accuracy and robustness of numerical methods to solve these PDEs are sensitive to the particular functional representations of the free energy. In this communication we investigate the influence of different representations of thermodynamic data on phase field computations of diffusion and two-phase reactions in the solid state. First-principles statistical mechanics methods were used to generate realistic free energy data for HCP titanium with interstitially dissolved oxygen. While Redlich-Kister polynomials have formed the mainstay of thermodynamic descriptions of multi-component solids, they require high order terms to fit oscillations in chemical potentials around phase transitions. Here, we demonstrate that high fidelity fits to rapidly fluctuating free energy functions are obtained with spline functions. As a result, spline functions that are many degrees lower than Redlich-Kister polynomials provide equal or superior fits to chemical potential data and, when used in phase field computations, result in solution times approaching an order of magnitude speed up relative to the use of Redlich-Kister polynomials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Quantifying local and global mass balance errors in physics-informed neural networks

Physics-informed neural networks (PINN) have recently become attractive for solving partial differential equations (PDEs) that describe physics laws. By including PDE-based loss functions, physics laws such as mass balance are enforced softly in PINN. This paper investigates how mass balance constraints are satisfied when PINN is used to solve the resulting PDEs. We investigate PINN’s ability to solve the 1D saturated groundwater flow equations (diffusion equations) for homogeneous and heterogeneous media and evaluate the local and global mass balance errors. We compare the obtained PINN’s solution and associated mass balance errors against a two-point finite volume numerical method and the corresponding analytical solution. We also evaluate the accuracy of PINN in solving the 1D saturated groundwater flow equation with and without incorporating hydraulic heads as training data. We demonstrate that PINN’s local and global mass balance errors are significant compared to the finite volume approach. Tuning the PINN’s hyperparameters, such as the number of collocation points, training data, hidden layers, nodes, epochs, and learning rate, did not improve the solution accuracy or the mass balance errors compared to the finite volume solution. Mass balance errors could considerably challenge the utility of PINN in applications where ensuring compliance with physical and mathematical properties is crucial.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Era of entropy: Synthesis, structure, properties, and applications of high-entropy materials

The field of high-entropy materials (HEMs) has emerged as a dynamic area of scientific exploration, driven by the exceptional properties arising from their compositional complexity. Encompassing both high-entropy alloys (HEAs) and high-entropy ceramics (HECs), these materials have garnered significant attention across diverse research domains. From investigations into phase evolution and mechanical characteristics to studies of ionic, electronic, and magnetic behaviors, HEMs demonstrate remarkable potential for a wide array of applications. These range from catalysis and tribology to energy storage and superconductivity. Fundamental research has shed light on crucial phenomena such as configurational entropy, lattice distortion, and sluggish diffusion. These discoveries are paving the way for materials design strategies that enable new functional tunability and resistance to application-specific harsh environments. This burgeoning field promises to revolutionize material design and performance across numerous technological sectors. Here, this special collection between Applied Physics Letters and the Journal of Applied Physics provides a timely overview of the latest research in this area. It highlights the growing interest in understanding the impact of high compositional complexity on conventional structure–process–property–performance relationships in HEMs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Generative unfolding with distribution mapping

Machine learning enables unbinned, highly-differential cross section measurements. A recent idea uses generative models to morph a starting simulation into the unfolded data. We show how to extend two morphing techniques, Schrödinger Bridges and Direct Diffusion, in order to ensure that the models learn the correct conditional probabilities. This brings distribution mapping (DM) to a similar level of accuracy as the state-of-the-art conditional generative unfolding methods. Numerical results are presented with a standard benchmark dataset of single jet substructure as well as for a new dataset describing a 22-dimensional phase space of Z+2 -jets.

Butter, Anja↗
DOE OSTI2026

Multiscale Modeling and Experimental Insights into High-Temperature Soil Biodegradation Dynamics of Semi-Crystalline Poly(Lactic Acid) Nonwoven Fabrics

This study investigates the biodegradation of semi-crystalline poly(lactic acid) (PLA) nonwovens (NWs) in soil at 58 °C using both experimental and mathematical modeling approaches. The model utilizes a system of parabolic diffusion-reaction partial differential equations (PDEs) to elucidate chemical transformations over time and in space. It accounts for phenomena such as the diffusion of water and lactic acid monomers through the polymer matrix and into the surrounding soil, along with their microbial breakdown. It also accounts for the initial PLA crystallinity and predicts its evolution in time. The model is solved numerically for a single filament, and the results were used to shed light on PLA NW transformations observed in soil over a 180-day incubation period. Various characterization techniques, including scanning electron microscopy (SEM), differential scanning calorimetry (DSC), and Raman spectroscopy, were employed to assess morphological changes, crystallinity, and molecular changes in the NWs throughout the experiment. By comparing the experimental data with the model predictions, the hydrolysis rate coefficient was found to be 3.37 × 10 -7 s -1 , while the rate of microbial degradation of lactic acid monomers was faster, of the order of 9.63 × 10 -7 s -1 . The findings highlight the significant role of crystallinity in the biodegradation process. The PLA degradation ceases when no amorphous material remains, and the crystallinity reaches 0.8, as observed in the experiments by day 120. Furthermore, this research contributes to a deeper understanding of PLA biodegradation dynamics and offers insights for effectively managing biodegradable materials in environmental settings.

Diffusion−reaction modeling↗
DOE OSTI2017

Leith diffusion model for homogeneous anisotropic turbulence

Here, a proposal for a spectral closure model for homogeneous anisotropic turbulence. The systematic development begins by closing the third-order correlation describing nonlinear interactions by an anisotropic generalization of the Leith diffusion model for isotropic turbulence. The correlation tensor is then decomposed into a tensorially isotropic part, or directional anisotropy, and a trace-free remainder, or polarization anisotropy. The directional and polarization components are then decomposed using irreducible representations of the SO(3) symmetry group. Under the ansatz that the decomposition is truncated at quadratic order, evolution equations are derived for the directional and polarization pieces of the correlation tensor. Here, numerical simulation of the model equations for a freely decaying anisotropic flow illustrate the non-trivial effects of spectral dependencies on the different return-to-isotropy rates of the directional and polarization contributions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

3D numerical modeling of the carrier transport and radiative efficiency for InGaN/GaN light emitting diodes with V-shaped pits

In this paper, influence of a V-pit embedded inside the multiple quantum wells (MQWs) LED was studied. A fully three-dimensional stress-strain solver and Poisson-drift-diffusion solver are employed to study the current path, where the quantum efficiency and turn-on voltage will be discussed. Our results show that the hole current is not only from top into lateral quantum wells (QWs) but flowing through shallow sidewall QWs and then injecting into the deeper lateral QWs in V-pit structures, where the V-pit geometry provides more percolation length for holes to make the distribution uniform along lateral MQWs. The IQE behavior with different V-pit sizes, threading dislocation densities, and current densities were analyzed. Substantially, the variation of the quantum efficiency for different V-pit sizes is due to the trap-assisted nonradiative recombination, effective QW ratio, and ability of hole injections.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗