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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 91 records · Page 5

On-Line Prediction of Resistant Force During Soil–Tool Interaction

For off-road vehicles such as excavators and wheel loaders, a large portion of energy is consumed to overcome the soil resistant force in the digging process. For optimal control of the digging tool, a high-fidelity model of the soil–tool interaction force is important to reduce energy consumption. Here, in this paper, an on-line soil resistant force prediction method is proposed. In this method, a hybrid model, which combines a physical model and a data-driven model, is used for the force prediction. In addition, the parameters of the hybrid model can be updated on-line based on real-time data. Comparisons with experimental data demonstrate that the proposed prediction method has an average error of around 12.7%.

42 ENGINEERING↗

Random Force Perturbations: A New Extension of the Cell Perturbation Method for Turbulence Generation in Multiscale Atmospheric Boundary Layer Simulations

Coupling between mesoscale and large eddy simulation (LES) is critically important for many atmospheric model applications, from predictions of wind energy to fire propagation. The grid-nesting technique enables bridging between vastly different scales without incurring prohibitive computational costs. Yet, the transition from coarser to finer resolutions often requires a large number of grid points from inflow boundaries for the development of fine-scale turbulence features in the LES domain. Recently, the cell perturbation method (CPM) was developed to reduce the turbulence development region with high computational efficiency. Herein, we explore a new method based on the CPM that uses force perturbations in both the horizontal and vertical directions (Force Cell Perturbation Method) instead of the potential temperature perturbations in the original CPM, as an attempt to further explore the performance of the random perturbation techniques. This method is tested for a neutral and a convective atmospheric boundary layer under idealized conditions. Overall, similar performance is found between the optimal configurations of the CPM and the Force Cell Perturbation Method pointing to the robustness of this family of perturbation methods in accelerating turbulence generation in nested domains. Vertical force perturbations performed better than horizontal force perturbations for both atmospheric stability conditions. The CPM performed best under convective stability conditions. The combination of the force and potential temperature perturbations is found to provide no additional performance improvement over the stand-alone application of the individual methods.

54 ENVIRONMENTAL SCIENCES↗

Analytic atomic gradients in the fermi‐löwdin orbital self‐interaction correction

We derived, implemented, and thoroughly tested the complete analytic expression for atomic forces, consisting of the Hellmann‐Feynman term and the Pulay correction, for the Fermi‐Löwdin orbital self‐interaction correction (FLO‐SIC) method. Analytic forces are shown to be numerically accurate through an extensive comparison to forces obtained from finite differences. Using the analytic forces, equilibrium structures for a small set of molecules were obtained. This work opens the possibility of routine self‐interaction free geometrical relaxations of molecules using the FLO‐SIC method. © 2018 Wiley Periodicals, Inc.

Trepte, Kai↗

Sharp front tracking with geometric interface reconstruction

Here, this paper presents a novel sharp front-tracking method designed to address limitations in classical front-tracking approaches, specifically their reliance on smooth interpolation kernels and extended stencils for coupling the front and fluid mesh. In contrast, the proposed method employs exclusively sharp, localized interpolation and spreading kernels, restricting the coupling to the interfacial fluid cells–those containing the interface/front. This localized coupling is achieved by integrating a divergence-preserving velocity interpolation method with a piecewise parabolic interface calculation (PPIC) and a polyhedron intersection algorithm to compute the indicator function and local interface curvature. Surface tension is computed using the Continuum Surface Force (CSF) method, maintaining consistency with the sharp representation. Additionally, we propose an efficient local roughness smoothing implementation to account for surface mesh undulations, which is easily applicable to any triangulated surface mesh. Building on our previous work, the primary innovation of this study lies in the localization of the coupling for both the indicator function and surface tension calculations. By reducing the interface thickness on the fluid mesh to a single cell, as opposed to the 4–5 cell spans typical in classical methods, the proposed sharp front-tracking method achieves a highly localized and accurate representation of the interface. This sharper representation mitigates parasitic currents and improves force balancing, making it particularly suitable for scenarios where the interface plays a critical role, such as microfluidics, fluid-fluid interactions, and fluid-structure interactions. The proposed method is comprehensively validated and tested on canonical interfacial flow problems, including stationary and translating Laplace equilibria, oscillating droplets, and rising bubbles. The presented results demonstrate that the sharp front-tracking method significantly outperforms the classical approach in terms of accuracy, stability, and computational efficiency. Notably, parasitic currents are reduced by approximately two orders of magnitude and stable results are obtained for parameter ranges where classical front tracking fails to converge.

42 ENGINEERING↗

A new method for diagnosing effective radiative forcing from aerosol–cloud interactions in climate models

Aerosol–cloud interactions (ACIs) are a leading source of uncertainty in estimates of the historical effective radiative forcing (ERF). One reason for this uncertainty is the difficulty in estimating the ERF from aerosol–cloud interactions (ERFaci) in climate models, which typically requires multiple calls to the radiation code. Most commonly used methods also cannot disentangle the contributions from different processes to ERFaci. Here, we develop a new, computationally efficient method for estimating the shortwave (SW) ERFaci from liquid clouds using histograms of monthly averaged cloud fraction partitioned by cloud droplet effective radius (r e ) and liquid water path (LWP). Multiplying the histograms with SW cloud radiative kernels gives the total SW ERFaci from liquid clouds, which can be decomposed into contributions from the Twomey effect, LWP adjustments, and cloud fraction (CF) adjustments. We test the method with data from five CMIP6-era models, using the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument simulator to generate the histograms. Our method gives similar total SW ERFaci estimates to other established methods in regions of prevalent liquid cloud and indicates that the Twomey effect, LWP adjustments, and CF adjustments have contributed -0.34 ± 0.23, -0.22 ± 0.13, and -0.09 ± 0.11 W m -2 , respectively, to the effective radiative forcing of the climate since 1850 in the ensemble mean (95 % confidence). These results demonstrate that widespread adoption of a MODIS r e –LWP joint histogram diagnostic would allow the SW ERFaci and its components to be quickly and accurately diagnosed from climate model outputs, a crucial step for reducing uncertainty in the historical ERF.

54 ENVIRONMENTAL SCIENCES↗

Hydrodynamic irreversibility of non-Brownian suspensions in highly confined duct flow

The irreversible behaviour of a highly confined non-Brownian suspension of spherical particles at low Reynolds number in a Newtonian fluid is studied experimentally and numerically. In the experiment, the suspension is confined in a thin rectangular channel that prevents complete particle overlap in the narrow dimension and is subjected to an oscillatory pressure-driven flow. In the small cross-sectional dimension, particles rapidly separate to the walls, whereas in the large dimension, features reminiscent of shear-induced migration in bulk suspensions are recovered. Furthermore, as a consequence of the channel geometry and the development and application of a single-camera particle tracking method, three-dimensional particle trajectories are obtained that allow us to directly associate relative particle proximity with the observed migration. Companion simulations of a steadily flowing suspension highly confined between parallel plates are conducted using the force coupling method, which also show rapid migration to the walls as well as other salient features observed in the experiment. While we consider relatively low volume fractions compared to most prior work in the area, we nevertheless observe significant and rapid migration, which we attribute to the high degree of confinement.

42 ENGINEERING↗

Machine-learning force-field models for dynamical simulations of metallic magnets

We review recent advances in machine-learning (ML) force-field methods for Landau–Lifshitz–Gilbert simulations of itinerant electron magnets, focusing on their scalability and transferability. Built on the principle of locality, a deep neural-network model is developed to efficiently and accurately predict electron-mediated forces governing spin dynamics. Symmetry-aware descriptors constructed through a group-theoretical approach ensure rigorous incorporation of both lattice and spin-rotation symmetries. The framework is demonstrated using the prototypical s-d exchange model widely employed in spintronics. ML-enabled large-scale simulations reveal novel nonequilibrium phenomena, including anomalous coarsening of tetrahedral spin order on the triangular lattice and the freezing of phase-separation dynamics in lightly hole-doped, strong-coupling square-lattice systems. These results establish ML force-field frameworks as scalable, accurate, and versatile tools for modeling nonequilibrium spin dynamics in itinerant magnets.

Artificial neural networks↗

Modular Approach for the Synthesis of Bottlebrush Diblock Copolymers from Poly(Glycidyl Methacrylate)-block-Poly(Vinyldimethylazlactone) Backbones

A strategy that enables the facile synthesis of bottlebrush block copolymers with flexible backbones was developed. A demonstration of the strategy’s utility was carried out by grafting end-functionalized polymethylmethacrylate (PMMA) and polystyrene (PS) to the dually reactive block copolymer, poly(glycidyl methacrylate)-block-poly(vinyldimethylazlactone) (PGMA-b-PVDMA). Five different bottlebrush diblock copolymers were investigated by size-exclusion chromatography (SEC), 1H NMR, Fourier transform infrared (FT-IR), differential scanning calorimetry (DSC), X-ray scattering methods, atomic force microscopy (AFM), rheology and computational simulations using molecular dynamics (MD), and self-consistent field theory (SCFT). A relationship between the glass transition temperature and the fraction of chain ends was demonstrated by DSC and highlights the potential of this synthetic method to tailor polymer properties. All five samples were found to be in a disordered phase exhibiting multiscale structures revealed by two broad peaks in small-angle X-ray scattering (SAXS) that can be attributed to graft-to-graft and backbone-to-backbone density correlations using MD simulations. The SCFT-based simulations justify the observation of a disordered phase due to its stabilization by the grafts. Additionally, this modular approach can be easily extended to other grafts, including responsive, conducting, and charged polymers with the prerequisite end groups. The versatility and ease of assembling these functional bottlebrushes constitute a powerful “toolbox” method for the rapid and scalable synthesis of novel bottlebrush block copolymers with desired properties.

36 MATERIALS SCIENCE↗

Benchmarking universal machine learning interatomic potentials for rapid analysis of inelastic neutron scattering data

The accurate calculation of phonons and vibrational spectra remains a significant challenge, requiring highly precise evaluations of interatomic forces. Traditional methods based on the quantum description of the electronic structure, while widely used, are computationally expensive and demand substantial expertise. Emerging universal machine learning interatomic potentials (uMLIPs) offer a transformative alternative by employing pre-trained neural network surrogates to predict interatomic forces directly from atomic coordinates. This approach dramatically reduces computation time and minimizes the need for technical knowledge. In this paper, we produce a phonon database comprising nearly 5000 inorganic crystals to benchmark the performance of several leading uMLIPs. We further assess these models in real-world applications by using them to analyze experimental inelastic neutron scattering data collected on a variety of materials. Through detailed comparisons, we identify the strengths and limitations of these uMLIPs, providing insights into their accuracy and suitability for fast calculations of phonons and related properties, as well as the potential for real-time interpretation of neutron scattering spectra. Our findings highlight how the rapid advancement of AI in science is revolutionizing experimental research and data analysis.

inelastic neutron scattering↗

SSAGES: Software Suite for Advanced General Ensemble Simulations

Molecular simulation has emerged as an essential tool for modern-day research, but obtaining proper results and making reliable conclusions from simulations requires adequate sampling of the system under consideration. To this end, a variety of methods exist in the literature that can enhance sampling considerably, and increasingly sophisticated, effective algorithms continue to be developed at a rapid pace. Implementation of these techniques, however, can be challenging for experts and non-experts alike. There is a clear need for software that provides rapid, reliable, and easy access to a wide range of advanced sampling methods, and that facilitates implementation of new techniques as they emerge. Here we present SSAGES, a publicly available Software Suite for Advanced General Ensemble Simulations designed to interface with multiple widely used molecular dynamics simulations packages. SSAGES allows facile application of a variety of enhanced sampling techniques—including adaptive biasing force, string methods, and forward flux sampling—that extract meaningful free energy and transition path data from all-atom and coarse grained simulations. A noteworthy feature of SSAGES is a user-friendly framework that facilitates further development and implementation of new methods and collective variables. In this study, the use of SSAGES is illustrated in the context of simple representative applications involving distinct methods and different collective variables that are available in the current release of the suite.

97 MATHEMATICS AND COMPUTING↗

Unified Approach to Implicit and Explicit Solvent Simulations of Electrochemical Reaction Energetics

One of the major open challenges in ab initio simulations of the electrochemical interface is the determination of electrochemical barriers under a constant driving force. Existing methods to do so include extrapolation techniques based on fully explicit treatments of the electrolyte, as well as implicit solvent models which allow for a continuous variation in electrolyte charge. Emerging hybrid continuum models have the potential to revolutionize the field, since they account for the electrolyte with little computational cost while retaining some explicit electrolyte, representing a “best of both worlds” method. In this work, we present a unified approach to determine reaction energetics from fully explicit, implicit, and hybrid treatments of the electrolyte based on a new multicapacitor model of the electrochemical interface. A given electrode potential can be achieved by a variety of interfacial structures; a crucial insight from this work is that the effective surface charge gives a good proxy of the local potential, the true driving force of electrochemical processes. In contrast, we show that the traditionally considered work function gives rise to multivalued functions depending on the simulation cell size. Furthermore, we show that the reaction energetics are largely insensitive to the countercharge distribution chosen in hybrid implicit/explicit models, which means that any of the myriad implicit electrolyte models can be equivalently applied. Furthermore, this work thus paves the way for the accurate treatment of ab initio reaction energetics of general surface electrochemical processes using both implicit and explicit electrolytes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Simulation study of particle clouds in oscillating shear flow

Simulations of cylindrical clouds of concentrated, neutrally buoyant, suspended particles are used to investigate the dispersion of the particles in an oscillating Couette flow. In experiments by Metzger & Butler ( Phys. Fluids , vol. 24 (2), 2012, 021703) with spherical clouds of non-Brownian particles, the clouds are shown to elongate at volume fraction $\unicode[STIX]{x1D719}=0.4$ but form ‘galaxies’ where the cloud rotates as a single body with extended arms when $\unicode[STIX]{x1D719}>0.4$ and the ratio of the cloud radius to particle radius, $R/a$ , is sufficiently large. The simulations, which use the force coupling method, are completed for $\unicode[STIX]{x1D719}=0.4$ and $\unicode[STIX]{x1D719}=0.55$ , with $R/a$ between $5$ and $20$ . The cloud shape for $\unicode[STIX]{x1D719}=0.4$ is shown to be reversible at low strain amplitude, and extend in the streamwise direction along the centre of the cloud at moderate strain amplitude. For higher strain amplitude the clouds extend near the channel walls to form a parallelogram. The results demonstrate that the particle contact force determines the transition between these states and plays a large role in the irreversibility of the parallelograms. Rotating galaxies form at $\unicode[STIX]{x1D719}=0.55$ with $R/a\geqslant 15$ , and are characterized by a particle-induced flow in the wall-normal direction.

Mechanics↗

Sensitivity of Surface Temperature to Oceanic Forcing via q -Flux Green’s Function Experiments. Part I: Linear Response Function

This paper explores the use of the linear response function (LRF) to relate the mean sea surface temperature (SST) response to prescribed ocean heat convergence ( q flux) forcings. Two methods for constructing the LRF based on the fluctuation–dissipation theorem (FDT) and Green’s function (GRF) are examined. A 900-yr preindustrial simulation by the Community Earth System Model coupled with a slab ocean model (CESM–SOM) is used to estimate the LRF using FDT. For GRF, 106 pairs of CESM–SOM simulations with warm and cold q-flux patches are performed. FDT is found to have some skill in estimating the SST response to a q-flux forcing when the local SST response is strong, but it fails in inverse estimation of the q-flux forcing for a given SST pattern. In contrast, GRF is shown to be reasonably accurate in estimating both SST response and q-flux forcing. Possible degradation in FDT may be attributed to insufficient data sampling, significant departure of the SST distribution from Gaussianity, and the nonnormality of the constructed operator. The GRF-based LRF is then used to (i) generate a global surface temperature sensitivity map that shows the q-flux forcing in higher latitudes to be 3–4 times more effective than low latitudes in producing global surface warming, and (ii) identify the most excitable SST mode (neutral vector) that shows marked resemblance to the interdecadal Pacific oscillation (IPO). The latter discovery suggests that the IPO-like fluctuation exists in the absence of the coupling to the ocean dynamics. Coupling to the ocean dynamics in CESM, on the other hand, only enhances the spectral power of the IPO at interannual time scales.

54 ENVIRONMENTAL SCIENCES↗

Stopping Force Analysis of 235 U Elemental Fission Product Yields for $E_n$ = 0.11–92.4 MeV

We report most evaluated elemental fission product yield distributions are not experimentally measured. Instead, the majority of evaluated distributions are based on analytic expressions of the Zp-model for relevant cumulative yields. Here we report independent elemental fission product yield distributions of a 235 U target for incident neutron energies ranging from 0.11 MeV through 92.4 MeV. Atomic numbers are calculated by an approach that combines a 2E analysis with a stopping force analysis method, developed within this paper. These analyses are applied to more than 6.1 × 10 6 fission fragment ionization tracks captured within the NIFFTE (Neutron Induced Fission Fragment Tracking Experiment) collaboration fission time projection chamber (fissionTPC). A 3-Z resolution was obtained with the fissionTPC spatial and energy resolutions. Tabulated results are presented for the atomic yield and experimentally derived Zp values as a function of pre-neutron-emission fragment masses for the complete range of incident neutron energies. The stopping-force-derived Zp values tend to support the unchanged charge distribution theory within uncertainty.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Liquid Phase Modeling in Porous Media: Adsorption of Methanol and Ethanol in H-MFI in Condensed Water

Zeolites are used in the chemical and separation industries for their exceptional selectivity, adsorption capacity, regenerability, and stability in gas and liquid phase processing. Here, we developed an explicit solvation method for predicting solvent/condensed phase effects on adsorption free energies in microporous media such as zeolites based on the hybrid quantum mechanical/molecular mechanical free energy perturbation (QM/MM-FEP) technique. Our explicit solvation method for zeolite systems, called eSZS, aims to capture site-specific interactions during the adsorption process at the Brønsted acid sites of H-MFI zeolite while still considering the diverse configuration space of the solvent molecules. This strategy is ideal for chemical reactions or adsorbates that interact with the microporous medium in few distinct adsorbate/transition state configurations, i.e., the harmonic or similar approximations are acceptable for the adsorbate/transition state while such approximations break down for the solvent molecules that require extensive configuration space sampling. In this way, our approach effectively overcomes the limitations of implicit solvation models and classical force field methods for describing solvation effects on chemical reactions within porous materials such as zeolites. Specifically, in this study, we investigated various aspects of our hybrid QM/MM approach, including QM cluster size dependencies in a periodic electrostatically embedded cluster model (PEECM), rules for link atoms at the QM/MM boundary, and functional and basis set considerations for converged and reasonably accurate gas and aqueous phase methanol and ethanol adsorption free energy predictions in H-MFI. For gas phase adsorption of methanol and ethanol in H-MFI at a Brønsted acid site in T12 position, we compute adsorption free energies at 298 K of −0.61 and −0.75 eV, respectively, using a PEECM containing 50 Si and 1 Al atom with ωB97x-D/def2-TZVP level of theory. For solvent effect calculations, we sample the aqueous phase using grand canonical Monte Carlo (GCMC) simulations to (1) obtain a mean field of electrostatic interactions in the reaction system and (2) perform a rigorous free energy perturbation calculation. Similar to the experimentally and computationally observed endergonic solvation effects observed for hydrocarbon adsorption on metal surfaces, we also observe that a condensed aqueous environment destabilizes methanol and ethanol at these acid sites in H-MFI at 298 K. Specifically, the computed solvation free energies of adsorption (ΔΔG solv ) for methanol and ethanol are +0.44 and +0.54 eV, respectively. From this study, it is evident that adsorbates (methanol and ethanol) are competing with water for adsorption space inside the H-MFI zeolite, leading to an endergonic solvation effect. Here, we expect that the endergonic, aqueous solvent effect during adsorption in microporous zeolites is highly tunable by changing the pore size and hydrophobicity of the microporous material as this will affect the water density inside the pore structure.

Adsorption↗

Toward continuum gyrokinetic study of high-field mirrors

High-temperature superconducting (HTS) magnetic mirrors under development exploit strong fields with high mirror ratio to compress loss cones and enhance confinement and may offer cheaper, more compact fusion power plant candidates. This new class of devices could exhibit largely unexplored interchange and gradient-driven modes. Such instabilities, and methods to stabilize them, can be studied with gyrokinetics, given the strong magnetization and prevalence of kinetic effects. Our focus here is to (a) determine if oft-used gyrokinetic models for open field lines produce the electron-confining (Pastukhov) electrostatic potential and (b) examine and address challenges faced by gyrokinetic codes in studying HTS mirrors. Here, we show that a one-dimensional limit of said models self-consistently develops a potential qualitatively approaching the analytical Pastukhov level. Additionally, we describe the computational challenges of studying high mirror ratios with open field line gyrokinetic solvers and offer a force softening method to mitigate small time steps needed for time integration in colossal magnetic field gradients produced by HTS coils, providing a 19X speedup.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Surrogate Hessian accelerated structural optimization for stochastic electronic structure theories

In this work, we present an efficient energy-based method for structural optimization with stochastic electronic structure theories, such as diffusion quantum Monte Carlo (DMC). This method is based on robust line-search energy minimization in reduced parameter space, exploiting approximate but accurate Hessian information from a surrogate theory, such as density functional theory. The surrogate theory is also used to characterize the potential energy surface, allowing for simple but reliable ways to maximize statistical efficiency while retaining controllable accuracy. We demonstrate the method by finding the minimum DMC energy structures of the selected flake-like aromatic molecules, such as benzene, coronene, and ovalene, represented by 2, 6, and 19 structural parameters, respectively. In each case, the energy minimum is found within two parallel line-search iterations. The method is near-optimal for a line-search technique and suitable for a broad range of applications. It is easily generalized to any electronic structure method where forces and stresses are still under active development and implementation, such as diffusion Monte Carlo, auxiliary-field Monte Carlo, and stochastic configuration interaction, as well as deterministic approaches such as the random-phase approximation. Accurate and efficient means of geometry optimization could shed light on a broad class of materials and molecules, showing high sensitivity of induced properties to structural variables.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Thermodynamic characteristics of praseodymium in the gallium–aluminum eutectic melt

The Ga–Al eutectic melt saturated with praseodymium was studied in the temperature range 572–1076 K by electromotive force (emf) method relative to the reference electrode (In{sub L} + PrIn{sub 3}, where L is the liquid phase) in a LiCl–KCl–CsCl eutectic electrolyte. The partial molar thermodynamic functions (enthalpy, entropy, and Gibbs energy) of praseo dymium in a Ga–Al eutectic melt were calculated. According to the emf measurements of the two-phase Pr–Ga–Al{sub L} + intermetallic compound alloys equilibrated with the Ga–Al eutectic melt saturated with praseodymium, there are intermetallic compounds PrGa{sub 6}, PrGa{sub 4}, and Pr{sub 0.22}Ga{sub 0.78}(PrGa{sub 2}) in the temperature ranges 572–741, 741–883, and 883–1076 K, respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗