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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 163 records · Page 9

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DOE OSTI2022

Computational studies of hydraulic stressors for biological performance assessment in a hydropower plant with Kaplan turbine

We report Hydropower is currently one of the preeminent sources of renewable energy in the United States and globally. Hydropower plants also have detrimental impacts on the environment and ecology, including direct impacts to anadromous fish populations. The computational fluid dynamics (CFD) – based Biological Performance Assessment (BioPA) toolset is used for biological evaluations of fish passage through hydropower plants. The hydraulic environment of a hydropower plant was evaluated using CFD coupled with discrete element method (DEM) simulations. The predicted flow field and particle collision rate were validated against the experimental data in a water flume that has an idealized hydroturbine distributor geometry. Flow simulations were conducted to evaluate the hydraulic stressors, such as nadir pressure, fluid shear, runner collision, in a physical scale in a hydropower plant with Kaplan turbine which are responsible for injury and mortality of fish in a downstream migration. The cumulative exposure probability for the nadir pressure and collision with turbine runner was found to decrease with increased discharge rate. The lowest discharge rate shows the higher value of cumulative shear exposure probability. The maximum value of collision velocity increases with increased discharge rate. We offer the conclusions that will help in understanding various hydraulic stressors for biological assessment for environmentally sustainable hydroturbine passage.

13 HYDRO ENERGY↗

DOE OSTI2024

A Reactor Scale-Up Methodology from Lab-Scale to Pilot-Scale Operations: Numerical Modeling of THFA Dehydration to DHP in Packed-Bed Reactors

This manuscript discusses developing a model-based scale-up methodology for a successful technology transfer of gas-phase catalytic reactors from a lab-scale to a pilot-scale operation. The manuscript demonstrates the methodology for gas-phase dehydration of tetrahydrofurfuryl alcohol (THFA) to dihydropyran (DHP) process over commercial Al 2 O 3 catalysts. A two-dimensional reactor model was developed using COMSOL Multiphysics 6.1 software. The model solves heat and mass transport equations in bed-scale and particle scales simultaneously. This powerful feature enables accurate prediction of the heat and mass transfer limitations in pilot-scale reactors, if any exists. Further, the model uses isothermal lab-scale experimental data to derive and validate the reaction chemistry, flow fields and boundary conditions. The model was then scaled-up to project conversion, selectivity, yield and formation rate of DHP in a pilot-scale reactor. The results highlight the complex nature of chemistry, heat, and mass transfer effects in lab-scale and pilot-scale reactors. The model results inform the possible operational limitations of the pilot-scale reactor and design strategies to improve process efficiency. Although the scale-up approach is explained through the THFA dehydration process, the methodology is applicable to any catalytic packed-bed reactor models for a successful process scale-up.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Micromagnetic Modeling of a Magnetically Unstable Zone and Its Geological Significances

Abstract Recent micromagnetic simulations have found that particles in the transitional zone between the single domain (SD) and single vortex (SV) zone are prone to thermal and external magnetic field instabilities that could adversely affect the accuracy of interpretations of paleomagnetic recordings. In this study, we attempt to evaluate the internal magnetization characteristics of these magnetically unstable (MU) particles and the influence on paleomagnetic observations by simulating the magnetic behavior of 68–104 nm truncated octahedral magnetite particles using the MERRILL modeling software. We found that: (a) The size region of the “MU zone” for grains of truncated octahedron shape is different from cubic octahedrons and spheres, indicating that the zone may be controlled by the geometry and shape of particles; (b) The MU zone has a range of 79–97 nm region, which is dominated by a hard‐axis aligned single vortex (HSV); and (c) MU particles are unstable as a function of temperature and have low coercive fields. Finally, the numerical fitting of hysteresis parameters for experimental data suggests that the influence of such MU particles in samples should not be ignored, especially for samples with fine‐grained magnetic minerals as the primary magnetic recording carriers. This research has extended our understanding of the behavior of the “MU zone” and its significance on paleomagnetic records.

Wang, Yuqin↗

DOE OSTI2025

Developing machine learning for heterogeneous catalysis with experimental and computational data

Machine learning techniques have emerged as a useful tool for identifying complex patterns and correlations in large datasets, such as associating catalyst performance to its physicochemical properties. In the heterogeneous catalysis communities, machine learning models have mostly been developed using high-throughput quantum chemistry calculations, with only a few case studies resulting in experimentally validated catalyst improvements. This limited success may be due to the use of simplified catalyst structures in computational studies and the lack of comprehensive experimental datasets. In this Review, we bring together studies integrating high-throughput approaches and machine learning for the advancement of solid heterogeneous catalysis, leveraging both experimental and computational data. We systematically analyze trends in the field, based on the descriptors used as model input and output; the materials, devices, or reactions investigated; the dataset size; and the overall achievements. Furthermore, for models reporting unitless R 2 values, we compare the performances based on these mentioned trends.

Computational chemistry↗

DOE OSTI2022

Ultrafast disruptive probing: Simultaneously keeping track of tens of reaction pathways

Ultrafast science depends on different implementations of the well-known pump–probe method. Here, we provide a formal description of ultrafast disruptive probing, a method in which the probe pulse disrupts a transient species that may be a metastable ion or a transient state of matter. Disruptive probing has the advantage of allowing for simultaneous tracking of the yield of tens of different processes. Our presentation includes a numerical model and experimental data on multiple products resulting from the strong-field ionization of two different molecules, partially deuterated methanol and norbornene. The correlated enhancement and depletion signals between all the different fragmentation channels offer comprehensive information on photochemical reaction pathways. In combination with ion imaging and/or coincidence momentum imaging or as complementary to atom-specific probing or ultrafast diffraction methods, disruptive probing is a particularly powerful tool for the study of strong-field laser–matter interactions.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Ti-6Al-4V to over 1.2 TPa: Shock Hugoniot experiments, ab initio calculations, and a broad-range multiphase equation of state

Titanium alloys are used in a large array of applications. In this work we focus our attention on the most used alloy, Ti-6Al-4V (Ti64), which has excellent mechanical and biocompatibility properties with applications in aerospace, defense, biomedical, and other fields. Here we present high-fidelity experimental shock compression data measured on Sandia’s Z machine. We extend the principal shock Hugoniot for Ti64 to more than threefold compression, up to over 1.2 TPa. We use the data to validate our ab initio molecular dynamics simulations and to develop a highly reliable, multiphase equation of state (EOS) for Ti64, spanning a broad range of temperature and pressures. The first-principles simulations show very good agreement with Z data and with previous three-stage gas gun data from Sandia’s STAR facility. The resulting principal Hugoniot and the broad-range EOS and phase diagram up to 10 TPa and 10 5 K are suitable for use in shock experiments and in hydrodynamic simulations. The high-precision experimental results and high-fidelity simulations demonstrate that the Hugoniot of the Ti64 alloy is stiffer than that of pure Ti and reveal that Ti64 melts on the Hugoniot at a significantly lower pressure and temperature than previously modeled.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

An Interactive Spectral Analysis Tool for Chemical Identification and Quantification of Gas-Phase Species in Complex Spectra

A spectral analysis tool has been developed to interactively identify and quantify individual gas-phase species from complex infrared absorbance spectra obtained from laboratory or field data. The SpecQuant program has an intuitive graphical interface that accommodates both reference and experimental data with varying resolution and instrumental lineshape, as well as algorithms to readily align the wavenumber axis of a sample spectrum with the raster of a reference spectrum. Using a classical least squares model in conjunction with reference spectra such as those from the Pacific Northwest National Laboratory (PNNL) gas-phase infrared database or simulated spectra derived from the HITRAN line-by-line database, the mixing ratio of each identified species is determined along with its associated estimation error. After correcting the wavelength and intensity of the field data, SpecQuant displays the calculated mixing ratio versus the experimental data for each analyte along with the residual spectrum with any or all analyte fits subtracted for visual inspection of the fit and residuals. The software performance for multianalyte quantification was demonstrated using moderate resolution (0.5 cm –1 ) infrared spectra that were collected during the time-resolved infrared photolysis of methyl iodide.

Thompson, Christopher J.↗

DOE OSTI2019

Kinetic Theory of the Wall Sheath for Arbitrary Conditions in a Gas-Discharge Plasma

The self-consistent problem of the structure of a perturbed wall sheath in a dc gas-discharge plasma near a flat surface under negative potential relative to the plasma has been solved for an arbitrary relation between the Debye radius and the ion mean free path. The solution has been obtained without artificial separation of this layer into the quasi-neutral “presheath” and the wall sheath in which quasi-neutrality is violated substantially. The actual ion distribution function in the unperturbed plasma, the dependence of the charge-exchange cross section on the ion energy, and the nonzero electric field in the unperturbed plasma have been considered. It is shown that when the average electron energy is conserved the structure of the perturbed wall sheath weakly depends on the form of the electron distribution function. It has been established that the mean energy of ions in the unperturbed plasma substantially affects the structure of the quasi-neutral presheath as well as the structure of a part of the wall sheath in which quasi-neutrality is not observed even under the assumption that the mean electron energy is much higher than the mean energy of ions. The calculations of ion flow parameters and the structure of the perturbed wall sheath are in conformity with experimental data obtained by other authors, which could not be adequately interpreted earlier.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Recent progress toward catalyst properties, performance, and prediction with data-driven methods

Herein, data-driven approaches are currently renovating the field of heterogenous catalysis and open a door to advance catalyst design. Their success depends heavily on the synergy among machine learning (ML), experimental data, and quantum mechanical (QM) calculations. In this brief survey of recent progress, we examine catalysis informatics in the context of (1) ML-aided catalyst characterizations, (2) knowledge extractions from experimental data, (3) predictions of catalytic properties and constructions of reaction networks, and (4) ML-enabled large-scale QM simulations. An outlook on the current challenges of this rapidly evolving field is also provided.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Influence of tower shadow on downwind flexible rotors: Field tests and simulations

Abstract As wind turbine rotors become larger, the blades become more flexible, requiring extra stiffness and cost to avoid the risk of tower strike. Wind turbines in a downwind configuration have a reduced risk of tower strike because the rotor thrust acts away from the tower. However, downwind blades pass through the wake of the tower, and the resulting load variation may contribute to blade fatigue. To date, there have been no field tests to quantify this tower shadow effect on unsteady blade moments. The present study reports on the first field testing of a flexible, downwind, coned rotor and compares the experimental data against simulations run in OpenFAST. The tower shadow effect is simulated using the conventional Powles model and a new Eames model (developed herein), which includes the influence of upstream turbulence. Both models reasonably predict the blade root out‐of‐plane bending moment data and the tower shadow dip magnitude when compared to field test data in Region 3. Tower shadow was found to increase the short‐term Damage Equivalent Loads (DELs) by less than 10% compared to other effects (gravity, shear, and turbulence), and the predictions were consistent with experiments. These results indicate that the tower shadow effect can be reasonably modeled with the simpler Powles model and that the tower shadow effect can be small compared to the effect of turbulence. However, long‐term fatigue due to tower shadow should be included in detailed structural analysis and design of the rotor and the tower.

Simpson, Juliet G.↗

DOE OSTI2023

Visualizing Uranium Crystallization from Melt: Experiment-Informed Phase Field Modeling and Machine Learning

The focus of this project was to observe and simulate the solidification of uranium metal at the crystallographic level from its molten state. Melting experiments were conducted at two different scales to observe microstructural evolution using either a laboratory-scale induction furnace (hundreds of grams of metal) or a microscope heating stage (hundreds of milligrams of metal), respectively. Experimental parameters and characterization data were then used to inform a phase field model of gamma-U crystal growth as dendrites with or without secondary phase impurities in the form of uranium carbide particles. Finally, training datasets were generated by the phase field model as inputs to a neural network, developed with the aim of providing a faster, cheaper surrogate model for microstructural simulations within a given parameter space. Progress is reported herein for each of these task areas. Ultimately, 1) an optical microscope heating stage capability has been stood-up for uranium metal solidification studies, 2) a phase field model was advanced to simulate multiple uranium grains growing in the presence of carbide impurity particles and 3) a neural network was constructed and optimized to predict the microstructure features of individually growing uranium crystals.

36 MATERIALS SCIENCE↗

DOE OSTI2023

magnetoARPES: Angle Resolved Photoemission Spectroscopy with magnetic field control

Angle-Resolved Photoemission Spectroscopy (ARPES) is a premier technique for understanding the electronic excitations in conductive, crystalline matter, in which the induced photocurrent is collected and dispersed in energy and angle of emission to reveal the energy- and momentum-dependent single particle spectral function A (k,ω). So far, ARPES in a magnetic field has been precluded due to the need to preserve the electron paths between the sample and detector. Here, in this paper we report progress towards “magnetoARPES”, a variant of ARPES that can be conducted in a magnetic field. It is achieved by applying a microscopic probe beam (≲10 μm) to a thinned sample mounted upon a special sample holder that generates magnetic field confined to a thin layer near the sample surface. In this geometry we could produce ARPES in magnetic fields up to around ±100 mT. The magnetic fields can be varied from purely in-plane to nearly purely out-of-plane, by scanning the probe beam across different parts of the device. We present experimental and simulated data for graphene to explore the aberrations induced by the magnetic field. These results demonstrate the viability of the magnetoARPES technique for exploring symmetry breaking effects in weak magnetic fields.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

Coverage-Dependent Adsorption of Phenol on Pt(111) from First Principles

In this work, we quantify the coverage dependence of the adsorbate-adsorbate and metal-adsorbate interactions for phenol on Pt(111) using density functional theory. For the four most favorable adsorption sites, we find that the adsorption energy of phenol decreases linearly as a function of coverage. As such, the repulsive phenol-phenol lateral interactions are strongest near saturation when the inter-molecular distances are less than ~4.5 Å, manifesting in a decrease of the C-O dihedral bond angle of ~4°. The linear dependence of the adsorption energy on coverage allows for the construction of a mean-field model. We validate our mean-field model for phenol adsorption by comparing the theoretically predicted differential heat of adsorption to the experimental data, where a maximum deviation of 0.11 eV is found. This compares well to earlier reported results that used a similar mean-field approach for the adsorption of benzene on Pt(111), suggesting that lateral interactions between functionalized aromatics can be parameterized using a simpler approximation. Overall, this work demonstrates a simple method toward the improvement in current state-of-the-art hydrodeoxygenation modeling at surfaces by allowing for the incorporation of coverage effects in systems with large, aromatic compounds without resorting to overly complex models.

09 BIOMASS FUELS↗

DOE OSTI2021

Selection rules and dynamic magnetoelectric effect of the spin waves in multiferroic Bi Fe O 3

Here, we report the magnetic-field dependence of the THz absorption and nonreciprocal directional dichroism spectra of BiFeO 3 measured on the three principal crystal cuts for fields applied along the three principal directions of each cut. From the systematic study of the light polarization dependence, we deduced the optical selection rules of the spin-wave excitations. Our THz data, combined with small-angle neutron scattering results showed that (i) an in-plane magnetic field rotates the q vectors of the cycloids perpendicular to the magnetic field and (ii) the selection rules are mostly determined by the orientation of the q vector with respect to the electromagnetic fields. We observed a magnetic field history-dependent change in the strength and the frequency of the spin-wave modes, which we attributed to the change of the orientation and the length of the cycloidal q vector, respectively. Finally, we compared our experimental data with the results of linear spin-wave theory that reproduces the magnetic-field dependence of the spin-wave frequencies and most of the selection rules, from which we identified the spin-polarization coupling terms relevant for the optical magnetoelectric effect.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

Diagnosing Field Strengths and Plasma Conditions in Magnetically Insulated Transmission Lines Using Active Dopant Spectroscopy

Experimental validation data is needed to inform simulations of large pulsed power devices which are in development to understand and improve existing accelerators and inform future pulsed power capabilities. Using current spectroscopic techniques on the Z-machine, we have been unable to reliably diagnose plasma conditions and electric and magnetic fields within power flow regions. Laser ablation of a material produces a low density plasma, resulting in narrow spectroscopic line widths. By introducing a laser ablated plasma to the anode cathode gap of the Mykonos accelerator, we can monitor how the line shapes change due the current pulse by comparing these line shapes to spectral measurements taken without power flow. In this report we show several examples of measurements conducted on Mykonos on various dopant materials. We also show a negligible effect on power flow due to the presence of the ablation plasma for a range of parameters.

43 PARTICLE ACCELERATORS↗

DOE OSTI2022

Simulations of Low Mach Number Reactive Flows Coupled with Electric Fields

Applying electric fields to flames can provide an effective, non-invasive control of the combustion process. In this work, an algorithm recently introduced to handle the interactions between reactive flows and an electric field is extended to handle multiple dimensions and adaptive mesh refinement (AMR), and applied to a series of laminar flames. Experimental data allows to validate the ability of the algorithm to capture the mechanisms driving the flame response to electric fields.

electric fields↗

DOE OSTI2022

Simulations of Low Mach Number Reactive Flows Coupled with Electric Fields: Preprint

electric field↗

DOE OSTI2020

Comparative analysis of the methods for quantitative determination of water content in skin from diffuse reflectance spectroscopy data

The predictive properties of methods aimed for estimating the water content in skin from the spectral diffuse reflection characteristics near the water absorption line in the near-IR spectral range are analysed. Numerical simulation data, experimental data on diffuse reflection from human skin phantoms, and data from the reference data set of human skin reflectance spectra are used to consider the possibility of gaining additional information about the water distribution in skin. The influence of variations in the scattering coefficient and oxyhaemoglobin concentration on the water content estimates is investigated. (paper)

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗