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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Space Charge Driven Emittance Growth and the Effect of Octupoles in IOTA

The Integrable Optics Test Accelerator (IOTA) at Fermilab is a small machine dedicated to a broad frontier accelerator physics program. An important aspect of this program is to investigate the potential benefits of the resonance free tune spread achievable with integrable optics to store and accelerate high intensity proton beams for which space charge is significant. In this context, a good understanding of proton beam emittance growth and particle loss mechanisms is essential. Assuming nominal design parameters, simulations show that for a bunched beam, the bulk of emittance growth takes place immediately following injection, typically within tens of turns. We attempt to account for this growth using a simplified RMS mismatch theory; some of its limitations and possible improvements are briefly discussed. We then compare theoretical predictions to simulations performed using the PIC code pyORBIT. Further exploring ways to mitigate emittance growth and reduce particle loss, we compare two beam matching strategies: (1) matching at the injection point (2) matching at the center of the nonlinear (octupole) insertion region where $\beta_x = \beta_y$. To observe how nonlinearity affects emittance growth and whether it dominates growth due to mismatch, we track two different distributions. Finally, we explore the potential of using octupoles in a quasi-integrable configuration to mitigate growth using a variety of initial distributions both at reduced and full intensities.

43 PARTICLE ACCELERATORS↗
DOE OSTI2017

Predicted Extension of the Sagittarius Stream to the Milky Way Virial Radius

The extensive span of the Sagittarius (Sgr) stream makes it a promising tool for studying the gravitational potential of the Milky Way (MW). Characterizing its stellar kinematics can constrain halo properties and provide a benchmark for the paradigm of galaxy formation from cold dark matter. Accurate models of the disruption dynamics of the Sgr progenitor are necessary to employ this tool. Using a combination of analytic modeling and N -body simulations, we build a new model of the Sgr orbit and resulting stellar stream. In contrast to previous models, we simulate the full infall trajectory of the Sgr progenitor from the time it first crossed the MW virial radius 8 Gyr ago. An exploration of the parameter space of initial phase-space conditions yields tight constraints on the angular momentum of the Sgr progenitor. Our best-fit model is the first to accurately reproduce existing data on the 3D positions and radial velocities of the debris detected 100 kpc away in the MW halo. In addition to replicating the mapped stream, the simulation also predicts the existence of several arms of the Sgr stream extending to hundreds of kiloparsecs. The two most distant stars known in the MW halo coincide with the predicted structure. Additional stars in the newly predicted arms can be found with future data from the Large Synoptic Survey Telescope. Detecting a statistical sample of stars in the most distant Sgr arms would provide an opportunity to constrain the MW potential out to unprecedented Galactocentric radii.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Modeling, measurement, and 3-D equilibrium reconstruction of the bootstrap current in the Helically Symmetric Experiment

The bootstrap current for three electron cyclotron resonance heated plasma scenarios in a quasihelically symmetric stellarator (the Helically Symmetric Experiment) are analyzed and compared to a neoclassical transport code PENTA. The three conditions correspond to 50 kW input power with a resonance that is off-axis, 50 kW on-axis heating and 100 kW on-axis heating. When the heating location was moved from off-axis to on-axis with 50 kW heating power, the stored energy and the extrapolated steady-state current were both observed to increase. When the on-axis heating power was increased from 50 kW to 100 kW, the stored energy continued to increase while the bootstrap current slightly decreased. This trend is qualitatively in agreement with the calculations which indicate that a large positive electric field for the 100 kW case was driving the current negative in a small region close to the magnetic axis and accounting for the decrease in the total integrated current. This trend in the calculations is only observed to occur when momentum conservation between particle species is included. Without momentum conservation, the calculated bootstrap current increases monotonically. We show that the magnitude of the bootstrap current as calculated by PENTA agrees better with the experiment when momentum conservation between plasma species is included in the calculation. The total current was observed in all cases to flow in a direction to unwind the transform, unlike in a tokamak in which the bootstrap current adds to the transform. The 3-D inductive response of the plasma is simulated to predict the evolution of the current profile during the discharge. The 3-D equilibrium reconstruction code V3FIT is used to reconstruct profiles of the plasma pressure and current constrained by measurements with a set of magnetic diagnostics. The reconstructed profiles are consistent with the measured plasma pressure profile and the simulated current profile when the reconstruction is constrained by the measured data from a diagnostic array that is internal to the vacuum chamber.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

A simplified integrated framework for predicting the economic impacts of feedstock variations in a catalytic fast pyrolysis conversion process

Feedstock attributes of lignocellulosic biomass, such as particle size, compositional makeup, and moisture content, can vary substantially even within pre-processed materials and have a significant effect on conversion in fast pyrolysis-based processes. However, the economic impacts of these attributes are not well understood. To address this, biomass deconstruction phenomena captured with a versatile particle-scale simulation were linked to techno-economic impacts via reduced-order models. Parametric analysis of the particle-scale model, which was validated using literature data, was used in combination with multiple linear regression models to develop correlations between feedstock attributes and yields of pyrolysis oil, gas, and char. Yields were then correlated with the minimum fuel selling price (MFSP) using a techno-economic model, bridging the gap between physics-based biomass conversion simulations and predictions of MFSP for a catalytic fast-pyrolysis process. Empirical correlations derived from the literature regarding the impact of mineral matter (ash) on oil yield were also considered. The model correlations deployed in the integrated framework capture the impacts of variation in feedstock attributes on the MFSP. Variations in ash were shown to have the biggest impact, varying MFSP by -13%/+22% due to catalytic effects and lower relative amounts of convertible lignocellulosic material. It was also found that, if ash can be controlled to low levels, the increased extractives in forest residues can help compensate for some yield losses associated with increased ash. As a result, other inputs considered (particle size, moisture content, and reactor temperature) had relatively negligible effects on process economics within the ranges analyzed considering particle-scale effects alone.

BIOMASS FUELS↗
DOE OSTI2020

Cutting force and stability for inserted cutters using structured light metrology

This paper describes force and stability prediction for inserted end and face mills using a reverse engineering approach. Structured light scanning is used to identify the spatial coordinates of the points that define the multiple insert cutting edges. These points are used to extract the cutting edge radius and angle and are then incorporated in a time domain simulation that predicts cutting force and tool/workpiece deflection for user-selected operating parameters. Good agreement between predicted and measured cutting forces is demonstrated. The process stability is then predicted using the validated force model and measured structural dynamics.

Machining↗
DOE OSTI2017

Investigations into the Reusability of Amidoxime-Based Polymeric Adsorbents for Seawater Uranium Extraction

The ability to re-use amidoxime-based polymeric adsorbents is a critical component in reducing the overall cost of the technology to extract uranium from seawater. This report describes an evaluation of adsorbent reusability in multiple re-use (adsorption/stripping) cycles in real seawater exposures with potassium bicarbonate (KHCO3) elution using several amidoxime-based polymeric adsorbents. The KHCO3 elution technique achieved ~100% recovery of uranium adsorption capacity in the first re-use. Subsequent re-uses showed significant drops in adsorption capacity. After the 4th re-use with the ORNL AI8 adsorbent, the 56-day adsorption capacity dropped to 28% of its original capacity. FTIR spectra revealed that there was a conversion of the amidoxime ligands to carboxylate groups during extended seawater exposure, becoming more significant with longer the exposure time. Ca and Mg adsorption capacities also increased with each re-use cycle supporting the hypothesis that long term exposure resulted in converting amidoxime to carboxylate, enhancing the adsorption of Ca and Mg. Shorter seawater exposure (adsorption/stripping) cycles (28 vs. 42 days) had higher adsorption capacities after re-use, but the shorter exposure cycle time did not produce an overall better performance in terms of cumulative exposure time. Recovery of uranium capacity in re-uses may also vary across different adsorbent formulations. Through multiple re-use the adsorbent AI8 can harvest 10 g uranium/kg adsorbent in ~140 days, using a 28-day adsorption/stripping cycle, a performance much better than would be achieved with a single use of the adsorbent through very long-term exposure (saturation capacity = 7.4 g U/kg adsorbent). A time dependent seawater exposure model to evaluate the cost associated with reusing amidoxime-based adsorbents in real seawater exposures was developed. The cost to extract uranium from seawater ranged from $610-830/kg U was predicted. Model simulation suggests that a short seawater exposure cycle (< 15 days) is the optimal deployment period for lower uranium production cost in seawater uranium mining.

Kuo, Li-Jung↗
DOE OSTI2018

Effect of Solvent and Substrate on the Surface Binding Mode of Carboxylate-Functionalized Aromatic Molecules

Here, the efficiency of dye-sensitized solar cells (DSSCs) is strongly influenced by dye molecule orientation and interactions with the substrate. Understanding the factors controlling the surface orientation of sensitizing organic molecules will aid in the improvement of both traditional DSSCs and other devices that integrate molecular linkers at interfaces. Here, we describe a general approach to understand relative dye–substrate orientation and provide analytical expressions predicting orientation. We consider the effects of substrate, solvent, and protonation state on dye molecule orientation. In the absence of solvent, our model predicts that most carboxylic acid-functionalized molecules prefer to lie flat (parallel) on the surface, due to van der Waals interactions, as opposed to a tilted orientation with respect to the surface that is favored by covalent bonding of the carboxylic acid group to the substrate. When solvation effects are considered, however, the molecules are predicted to orient perpendicular to the surface. We extend this approach to help understand and guide the orientation of metal–organic framework (MOF) thin-film growth on various metal–oxide substrates. A two-part analytical model is developed on the basis of the results of DFT calculations and ab initio MD simulations that predicts the binding energy of a molecule by chemical and dispersion forces on rutile and anatase TiO 2 surfaces, and quantifies the dye solvation energy for two solvents. The model is in good agreement with the DFT calculations and enables rapid prediction of dye molecule and MOF linker binding preference on the basis of the size of the adsorbing molecule, identity of the surface, and the solvent environment. We establish the threshold molecular size, governing dye molecule orientation, for each condition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

First principles prediction of the Al-Li phase diagram including configurational and vibrational entropic contributions

The whole Al-Li phase diagram is predicted from first principles calculations and statistical mechanics including the effect of configurational and vibrational entropy. The formation enthalpy of different configurations at different temperatures was accurately predicted by means of cluster expansions that were fitted from first principles calculations. The vibrational entropic contribution of each configuration was determined from the bond length vs. bond stiffness relationships for each type of bond and the Gibbs free energy of the different phases was obtained as a function of temperature from Monte Carlo simulations. The predicted phase diagram was in excellent agreement with the currently accepted experimental one in terms of the stable (AlLi, Al 2 Li 3 , AlLi 2 , Al 4 Li 9 ) and metastable (Al 3 Li) phases, of the phase boundaries between them and of the maximum stability temperature of line compounds. In addition, it provided accurate information about the gap between Al 3 Li and AlLi solvus lines. Finally, the influence of the vibrational entropy on the correct prediction of the phase diagram is discussed. Overall, the methodology shows that accurate phase diagrams of alloys of technological interest can be predicted from first principles calculations.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Coupled Process/Device Modeling and Point Defect Engineering of Cu(In,Ga)Se 2 Solar Cells

Point defects directly impact solar cell device performance by limiting the carrier lifetime. In this work, density functional theory calculations are first used to determine the formation energy and diffusion energy barriers of dominant defects in Cu(In,Ga)Se 2 . Next, continuum reaction–diffusion models are developed to analyze the redistribution of defects during manufacturing processes. We estimate defect capture cross sections using a first-principles-based approach. Here, these cross sections are combined with our calculated defect profiles and trap energy levels to parameterize a Shockley–Read–Hall recombination model, which we implement into a device simulator to predict carrier lifetimes and device performance. In that way, a predictive technology computer aided design model is built to predict and optimize the performance of Cu(In,Ga)Se 2 solar cells.

14 SOLAR ENERGY↗
DOE OSTI2017

ACCRETION AND MAGNETIC RECONNECTION IN THE CLASSICAL T TAURI BINARY DQ TAU

The theory of binary star formation predicts that close binaries ( a < 100 au) will experience periodic pulsed accretion events as streams of material form at the inner edge of a circumbinary disk (CBD), cross a dynamically cleared gap, and feed circumstellar disks or accrete directly onto the stars. The archetype for the pulsed accretion theory is the eccentric, short-period, classical T Tauri binary DQ Tau. Low-cadence (∼daily) broadband photometry has shown brightening events near most periastron passages, just as numerical simulations would predict for an eccentric binary. Magnetic reconnection events (flares) during the collision of stellar magnetospheres near periastron could, however, produce the same periodic, broadband behavior when observed at a one-day cadence. To reveal the dominant physical mechanism seen in DQ Tau’s low-cadence observations, we have obtained continuous, moderate-cadence, multiband photometry over 10 orbital periods, supplemented with 27 nights of minute-cadence photometry centered on four separate periastron passages. While both accretion and stellar flares are present, the dominant timescale and morphology of brightening events are characteristic of accretion. On average, the mass accretion rate increases by a factor of five near periastron, in good agreement with recent models. Large variability is observed in the morphology and amplitude of accretion events from orbit to orbit. We argue that this is due to the absence of stable circumstellar disks around each star, compounded by inhomogeneities at the inner edge of the CBD and within the accretion streams themselves. Quasiperiodic apastron accretion events are also observed, which are not predicted by binary accretion theory.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Theoretical prediction and atomic kinetic Monte Carlo simulations of void superlattice self-organization under irradiation

Nano-structured superlattices may have novel physical properties and irradiation is a powerful mean to drive their self-organization. However, the formation mechanism of superlattice under irradiation is still open for debate. Here we use atomic kinetic Monte Carlo simulations in conjunction with a theoretical analysis to understand and predict the self-organization of nano-void superlattices under irradiation, which have been observed in various types of materials for more than 40 years but yet to be well understood. The superlattice is found to be a result of spontaneous precipitation of voids from the matrix, a process similar to phase separation in regular solid solution, with the symmetry dictated by anisotropic materials properties such as one-dimensional interstitial atom diffusion. This discovery challenges the widely accepted empirical rule of the coherency between the superlattice and host matrix crystal lattice. The atomic scale perspective has enabled a new theoretical analysis to successfully predict the superlattice parameters, which are in good agreement with independent experiments. The theory developed in this work can provide guidelines for designing target experiments to tailor desired microstructure under irradiation. Furthermore, it may also be generalized for situations beyond irradiation, such as spontaneous phase separation with reaction.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Nonlinear coherent structures of Alfvén wave in a collisional plasma

The Alfvén wave dynamics is investigated in the framework of two-fluid approach in a compressible collisional magnetized plasma. In the finite amplitude limit, the dynamics of the nonlinear Alfvén wave is found to be governed by a modified Korteweg-de Vries Burgers equation (mKdVB). In this mKdVB equation, the electron inertia is found to act as a source of dispersion, and the electron-ion collision serves as a dissipation. The collisional dissipation is eventually responsible for the Burgers term in mKdVB equation. In the long wavelength limit, this weakly nonlinear Alfvén wave is shown to be governed by a damped nonlinear Schrödinger equation. Furthermore, these nonlinear equations are analyzed by means of analytical calculation and numerical simulation to elucidate the various aspects of the phase-space dynamics of the nonlinear wave. Results reveal that nonlinear Alfvén wave exhibits the dissipation mediated shock, envelope, and breather like structures. Numerical simulations also predict the formation of dissipative Alfvénic rogue wave, giant breathers, and rogue wave holes. These results are discussed in the context of the space plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Machine learning interatomic potential for predicting the thermal properties of uranium nitride

We present a combined computational and experimental investigation of the thermal properties of uranium nitride (UN), focusing on the development of a machine learning interatomic potential (MLIP) using the moment tensor potential framework. The MLIP was trained on density functional theory (DFT) data and validated against various quantities including energies, forces, elastic constants, phonon dispersion, and defect formation energies, achieving excellent agreement with DFT calculations, prior experimental results, and our thermal conductivity measurement. The potential was then employed in molecular dynamics simulations to predict key thermal properties such as melting point, thermal expansion, specific heat, and lattice thermal conductivity. To further assess model accuracy, we fabricated a UN sample and performed new thermal conductivity measurements representative of single-crystal properties, which showed strong agreement with the MLIP predictions. This work confirms the reliability and predictive capability of the developed potential for determining the thermal properties of UN.

36 - MATERIALS SCIENCE↗
DOE OSTI2026

Establishment of a Vertically Integrated Domestic Manufacturing Process for Production of Substrates Needed for Manufacture of Gas Diffusion Layers

In this project, AvCarb, LLC evaluated the baseline performance metrics of commercial carbon veils and their corresponding Gas Diffusion Layers (GDLs) with the goal of establishing an optimized, vertically integrated production system for wet-laid nonwoven substrates used in gas diffusion media for electrochemical energy storage and conversion devices. Mechanical testing and microstructural characterization were conducted and used to develop a multiscale computational model capable of simulating and predicting the performance of GDLs in fuel cells. Although the project successfully generated foundational transport and modeling data, it was terminated prior to identifying the critical GDL design parameters necessary for full optimization. The program aimed to improve carbon veil fabrication through enhanced fiber dispersion, fiber-fiber adhesion control, and improved web formation, enabling the production of high-quality, uniform substrates. Simulations were intended to guide mixing and solution delivery system design and process conditions, followed by production-scale trials to evaluate fiber dispersion, web uniformity, and mechanical robustness. At full deployment, the proposed production line would have been capable of producing approximately 650,000 m² of carbon veil annually. This capability remains strategically important, as the United States currently lacks a domestic source of wet-laid nonwoven carbon substrates that satisfy the stringent quality requirements for fuel-cell GDLs and electrolyzers representing an ongoing supply-chain vulnerability. Beyond supply-chain benefits, the project established a robust benchmarking dataset for existing commercial carbon veils while advancing next-generation material concepts targeting improved performance and manufacturing consistency.

Olson, Cynthia Lemay↗
DOE OSTI2024

An Empirical Model For Intrinsic Alignments: Insights From Cosmological Simulations

We extend current models of the halo occupation distribution (HOD) to include a flexible, empirical framework for the forward modeling of the intrinsic alignment (IA) of galaxies. A primary goal of this work is to produce mock galaxy catalogs for the purpose of validating existing models and methods for the mitigation of IA in weak lensing measurements. This technique can also be used to produce new, simulation-based predictions for IA and galaxy clustering. Our model is probabilistically formulated, and rests upon the assumption that the orientations of galaxies exhibit a correlation with their host dark matter (sub)halo orientation or with their position within the halo. We examine the necessary components and phenomenology of such a model by considering the alignments between (sub)halos in a cosmological dark matter only simulation. We then validate this model for a realistic galaxy population in a set of simulations in the Illustris-TNG suite. We create an HOD mock with Illustris-like correlations using our method, constraining the associated IA model parameters, with the $\mathcal{X}$$^{2}_{dof}$ between our model’s correlations and those of Illustris matching as closely as 1.4 and 1.1 for orientation–position and orientation–orientation correlation functions, respectively. By modeling the misalignment between galaxies and their host halo, we show that the 3-dimensional two-point position and orientation correlation functions of simulated (sub)halos and galaxies can be accurately reproduced from quasi-linear scales down to 0.1 $\mathcal{h}$ –1 Mpc. We also find evidence for environmental influence on IA within a halo. Our publicly-available software provides a key component enabling efficient determination of Bayesian posteriors on IA model parameters using observational measurements of galaxy-orientation correlation functions in the highly nonlinear regime.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Improvement in the Modeled Representation of North American Monsoon Precipitation Using a Modified Kain–Fritsch Convective Parameterization Scheme

A commonly noted problem in the simulation of warm season convection in the North American monsoon region has been the inability of atmospheric models at the meso-β scales (10 s to 100 s of kilometers) to simulate organized convection, principally mesoscale convective systems. With the use of convective parameterization, high precipitation biases in model simulations are typically observed over the peaks of mountain ranges. To address this issue, the Kain–Fritsch (KF) cumulus parameterization scheme has been modified with new diagnostic equations to compute the updraft velocity, the convective available potential energy closure assumption, and the convective trigger function. The scheme has been adapted for use in the Weather Research and Forecasting (WRF). A numerical weather prediction-type simulation is conducted for the North American Monsoon Experiment Intensive Observing Period 2 and a regional climate simulation is performed, by dynamically downscaling. In both of these applications, there are notable improvements in the WRF model-simulated precipitation due to the better representation of organized, propagating convection. The use of the modified KF scheme for atmospheric model simulations may provide a more computationally economical alternative to improve the representation of organized convection, as compared to convective-permitting simulations at the kilometer scale or a super-parameterization approach.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

INTEGRATION OF COST MODELS AND PROCESS SIMULATION TOOLS FOR OPTIMUM COMPOSITE MANUFACTURING PROCESS

Manufacturing cost of resin transfer molded composite parts is significantly influenced by the cycle time, which is strongly related to the time for both filling and curing of the resin in the mold. The time for filling can be optimized by various injection strategies, and by suitably reducing the length of the resin flow distance during the injection. The curing time can be reduced by the usage of faster curing resins, but it requires a high pressure injection equipment, which is capital intensive. Predictive manufacturing simulation tools that are being developed recently for composite materials are able to provide various scenarios of processing conditions virtually well in advance of manufacturing the parts. In the present study, we integrate the cost models with process simulation tools to study the influence of various parameters such as injection strategies, injection pressure, compression control to minimize high pressure injection, resin curing rate, and demold time on the manufacturing cost as affected by the annual part volume. A representative automotive component was selected for the study and the results are presented in this paper

42 ENGINEERING↗
DOE OSTI2021

Ocean fronts and eddies force atmospheric rivers and heavy precipitation in western North America

Atmospheric rivers (ARs) are responsible for over 90% of poleward water vapor transport in the mid-latitudes and can produce extreme precipitation when making landfall. However, weather and climate models still have difficulty simulating and predicting landfalling ARs and associated extreme precipitation, highlighting the need to better understand AR dynamics. Here, using high-resolution climate models and observations, we demonstrate that mesoscale sea-surface temperature (SST) anomalies along the Kuroshio Extension can exert a remote influence on landfalling ARs and related heavy precipitation along the west coast of North America. Inclusion of mesoscale SST forcing in the simulations results in approximately a 40% increase in landfalling ARs and up to a 30% increase in heavy precipitation in mountainous regions and this remote impact occurs on two-week time scales. The asymmetrical response of the atmosphere to warm vs. cold mesoscale SSTs over the eddy-rich Kuroshio Extension region is proposed as a forcing mechanism that results in a net increase of moisture flux above the planetary boundary layer, prompting AR genesis via enhancing moisture transport into extratropical cyclones in the presence of mesoscale SST forcing.

54 ENVIRONMENTAL SCIENCES↗