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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Load Mitigation on Floating Offshore Wind Turbines with Advanced Controls and Tuned Mass Dampers

General Electric, the National Renewable Energy Laboratory (NREL), the University of Massachusetts Amherst (UMass), and Glosten have recently completed a US Department of Energy (DOE)-funded research program to study technologies for mitigating loads on floating offshore wind turbines through the use of advanced turbine controls and tuned mass dampers (TMDs). The analysis was based upon the Glosten PelaStar tension leg platform (TLP) with GE Haliade 150 turbine, a system developed in a previous front end engineering design (FEED) study funded by the Energy Technology Institute (ETI) in the UK. The platform was designed for the WaveHub wave energy research site, with a mean water depth of 59-m. Loads were analyzed by running time-domain simulations in four 50-year return period (50-YRP) ultimate load state (ULS) conditions and 77 fatigue load state (FLS) environmental conditions. In 50-YRP conditions advanced controls are not active. The influence of TMDs on ULS loads have been reported previously (Park et al. [2]). In FLS conditions advanced controls and TMDs afford dramatic reductions in fatigue damage, offering the potential of significant savings in tower structural requirements. Simulations in turbine idling conditions were run in OrcaFlex, and simulations in operating conditions were run in FAST. Simulations were run with a baseline turbine controller, representative of the current state of the art, and an advanced controller developed by NREL to use collective and individual blade pitch control to maintain rotor speed and reduce tower loads. UMass developed a number of TMD types, with varying system configurations, including passive nonlinear dampers and semi-actively controlled dampers with an inverse velocity groundhook control algorithm. Loads and accelerations in FLS conditions were evaluated on the basis of damage equivalent loads (DELs), and fatigue damage was computed by Miner's summations of stress cycles at the tower base. To study sensitivity to water depth, loads were analyzed at both the 59-m WaveHub depth and a more commercially realistic depth of 100 m. TMDs reduce fatigue damage at the tower-column interface flange by up to 52% in 59-m water depth and up to 28% in 100 m water depth. Advanced controls reduce fatigue damage at the tower-column flange by up to 22% in 59-m water depth and up to 40% in 100 m water depth. The most effective load-mitigation strategy is combining advanced controls with TMDs. This strategy affords a 71% reduction in fatigue damage in both 59-m and 100-m water depths.

17 WIND ENERGY↗
DOE OSTI2024

Identifying point defects and ordering in the high-entropy layered oxide Li 1.5 MO 3-δ (M=Mn, Al, Fe, Co, Ni) for energy storage applications

High-entropy layered oxides (HELOs) represent a very promising class of next-generation battery cathodes, combining the well-studied properties of layered cathode materials such as LiCoO 2 with the chemical tunability and stability of high-entropy materials. HELO materials often form particles with complex defects and domain structures, complicating accurate characterization of structure and cation mixing. Understanding disorder and order in HELO materials is necessary for understanding their performance and utility as cathodes. Here we demonstrate the characterization of the HELO Li 1.5 MO 3-δ (M = Mn, Al, Fe, Co, Ni), wherein X-ray powder diffraction, transmission electron microscopy imaging, and electron diffraction patterns are analyzed to reveal the presence of ordering in the HELO, with imaging and diffraction simulation employed to compare experimental results to atomic modeling. Finally, without rigorous characterization at the atomic scale, important features such as defect ordering can be easily overlooked and therefore remain unconsidered when interpreting experimental results.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Roles for Countercharge in the Voltage Sensor Domain of Ion Channels

Voltage-gated ion channels share a common structure typified by peripheral, voltage sensor domains. Their S4 segments respond to alteration in membrane potential with translocation coupled to ion permeation through a central pore domain. The mechanisms of gating in these channels have been intensely studied using pioneering methods such as measurement of charge displacement across a membrane, sequencing of genes coding for voltage-gated ion channels, and the development of all-atom molecular dynamics simulations using structural information from prokaryotic and eukaryotic channel proteins. One aspect of this work has been the description of the role of conserved negative countercharges in S1, S2, and S3 transmembrane segments to promote sequential salt-bridge formation with positively charged residues in S4 segments. These interactions facilitate S4 translocation through the lipid bilayer. In this review, we describe functional and computational work investigating the role of these countercharges in S4 translocation, voltage sensor domain hydration, and in diseases resulting from countercharge mutations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A classical molecular dynamics simulation method for the formation of “dry” gels from boro-aluminosilicate glass structures

In contact with water, glass transforms into amorphous and porous structures called gels. A simulation method based on classical molecular dynamics is proposed here to mimic “dry” gels forming from initial oxide glass structures. Six glass compositions were investigated. Two behaviours were evidenced depending on the initial glass composition, and in particular on the quantity of elements removed. If a large quantity of soluble elements (B, Na) was removed, it induced an increase in the average pore size within the gels, and the time needed to stabilise the gel structure increased because more local atomic rearrangements occurred. The gel network displayed a higher proportion of Si-Q4 at the expense of Si-Q3 and a lower average ring size compared to the glass network, irrespective of the glass composition. Surface effects were also highlighted in the dry gels, such as the presence of 3-coordinated Al and a decrease in the average angle Si-O-Si and Al-O-Al. Our findings will be compared to both wet gels and experimental data in further studies, to help find the best procedure to simulate such structures.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Modeling Structural Colors from Disordered One-Component Colloidal Nanoparticle-Based Supraballs Using Combined Experimental and Simulation Techniques

Bright, saturated structural colors in birds have inspired synthesis of self-assembled, disordered arrays of assembled nanoparticles with varied particle spacings and refractive indices. However, predicting colors of assembled nanoparticles, and thereby guiding their synthesis, remains challenging due to the effects of multiple scattering and strong absorption. In this work, we use a computational approach to first reconstruct the nanoparticles’ assembled structures from small-angle scattering measurements and then input the reconstructed structures to a finite-difference time-domain method to predict their color and reflectance. This computational approach is successfully validated by comparing its predictions against experimentally measured reflectance and provides a pathway for reverse engineering colloidal assemblies with desired optical and photothermal properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Molecular Dynamics Simulation and Theoretical Analysis of Structural Relaxation, Bond Exchange Dynamics, and Glass Transition in Vitrimers

Vitrimers are a class of polymer networks featuring dynamic covalent cross-links that can undergo associative bond exchange. There has been recent interest in these materials due to their promise as recyclable thermosets or self-healing polymers because of the ability of vitrimer networks to rearrange at the molecular level and undergo macroscopic flow. However, the practical use of these materials often occurs in the supercooled regime or glassy state, where the implications of dynamic bonds are complicated by the interplay between slow activated segmental dynamics, cross-link (i.e., bond-exchange) kinetics, and ultimately material properties. Here, in this paper, we combine coarse-grained molecular dynamics simulation and microscopic statistical mechanical theory to understand how cross-linking kinetics affect material dynamics and how this couples to segmental relaxation of the polymeric network strands across a spectrum of length and time scales, especially in the supercooled regime. We characterize the Kuhn segmental alpha relaxation time and bond exchange time for vitrimer systems across various cross-link densities, temperatures, and bond exchange rates. Simulation and theory both exhibit a bending-up behavior for bond exchange time upon cooling, suggesting a coupling between bond exchange dynamics and segmental relaxation that intensifies with faster bond exchange kinetics. We also found bond exchange dynamics have an impact on Kuhn segment alpha relaxation time, which is most significant at higher cross-link densities. Both these effects are most prominent when the bond exchange time is similar to the Kuhn segment alpha relaxation time, and the resulting coupling of these two relaxation processes is tied to both the probability of a free end to find a bonded pair and the time scale of the constraints imposed by the dynamic cross-links. This relationship is reflected by a cross-link dependence of a theoretical parameter which represents the quantitative degree of coupling between bond exchange and segmental dynamics. Overall, the combination of simulation and theory clarifies the intricate interaction between bond kinetics and segmental relaxation and demonstrates the ability to provide molecular-level insights into vitrimer dynamics over a wide temperature range.

dynamic relaxation↗
DOE OSTI2021

Deep learning simulations of the microwave sky

Here we present 500 high-resolution, full-sky millimeter-wave deep learning (DL) simulations that include lensed CMB maps and correlated foreground components. We find that these MillimeterDL simulations can reproduce a wide range of non-Gaussian summary statistics matching the input training simulations, while only being optimized to match the power spectra. The procedure we develop in this work enables the capability to mass produce independent full-sky realizations from a single expensive full-sky simulation, when ordinarily the latter would not provide enough training data. We also circumvent a common limitation of high-resolution DL simulations that they be confined to small sky areas, often due to memory or GPU issues; we do this by developing a “stitching” procedure that can recover the large-scale, high-order statistics and avoid discontinuities or repeated features in the maps. In addition, since our network takes as input a full-sky lensing convergence map, it can in principle take a full-sky lensing convergence map from any large-scale structure (LSS) simulation and generate the corresponding lensed CMB and correlated foreground components at millimeter wavelengths; this is especially useful in the current era of combining results from both CMB and LSS surveys, which require a common set of simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Analysis of Cavern and Well Stability at the Bryan Mound SPR Site Using the M–D Salt Creep Model

This report presents computational analyses that simulate the structural response of caverns at the Strategic Petroleum Reserve Bryan Mound site. The cavern field comprises 20 caverns. Five caverns (1, 2, 4, and 5; 3 was later plugged and abandoned) were acquired from industry and have unusual shapes and a history dating back to 1946. The other 16 caverns (101-116) were leached according to SPR standards in the mid-1980s and have tall cylindrical shapes. The history of the caverns and their shapes are simulated in a 3-D geomechanics model of the site that predicts deformations, strains, and stresses. Historical wellhead pressures are used to calculate cavern pressures up through July 2016. Because of the extent of heterogeneous creep behavior observed throughout the Bryan Mound site, a set of cavern-specific creep coefficients was developed to produce better matches with measured cavern closure and surface subsidence. For this new implementation of the model, there are two significant advances: the use of the multimechanism deformation (M-D) salt creep model to evaluate both steady-state and transient salt creep; and the creation of finite element mesh geometries for the caverns that nearly exactly match the geometries obtained through sonar measurements. The results of the finite element model are interpreted to provide information on the current and future status of subsidence, well integrity, cavern stability, and drawdown availability.

58 GEOSCIENCES↗
DOE OSTI2022

LigninGraphs: lignin structure determination with multiscale graph modeling

Lignin is an aromatic biopolymer found in ubiquitous sources of woody biomass. Designing and optimizing lignin valorization processes requires a fundamental understanding of lignin structures. Experimental characterization techniques, such as 2D-heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) spectra, could elucidate the global properties of the polymer molecules. Computer models could extend the resolution of experiments by representing structures at the molecular and atomistic scales. We introduce a graph-based multiscale modeling framework for lignin structure generation and visualization. The framework employs accelerated rejection-free polymerization and hierarchical Metropolis Monte Carlo optimization algorithms. We obtain structure libraries for various lignin feedstocks based on literature and new experimental NMR data for poplar wood, pinewood, and herbaceous lignin. The framework could guide researchers towards feasible lignin structures, efficient space exploration, and future kinetics modeling. Its software implementation in Python, LigninGraphs, is open-source and available on GitHub.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Instabilities and turbulence in low-$β$ guide field reconnection exhausts with kinetic Riemann simulations

The role of turbulence in low-$β$, guide-field reconnection exhausts is explored in 2D reconnection and 2D and 3D Riemann simulations. The structure of the exhaust and associated turbulence is controlled by a pair of rotational discontinuities (RDs) at the exhaust boundary and a pair of slow shocks (SSs) that are generated by counterstreaming ions beams. In 2D, the exhaust develops large-amplitude striations at the ion Larmor radius scale that are produced by electron-beam-driven ion cyclotron waves. The electron beams driving the instability are injected into the exhaust from one of the RDs. However, in 3D Riemann simulations, the additional dimension (in the out-of-plane direction) results in strong Buneman and electron-electron streaming instabilities at the RD which suppress the electron beam formation and therefore the striations in the exhaust. The strength of the streaming instabilities at the RD is controlled by the ratio of the electron thermal speed to Alfvén speed, with the lower thermal speed being more unstable. In the 3D simulations, an ion-ion streaming instability acts to partially thermalize the counterstreaming ion beams at the SSs. This instability is controlled by the ratio of the sound speed to Alfvén speed and is expected to be stable in the low $β$ solar corona. The results suggest that in a guide field reconnection exhaust with 1 $\gg$ $β >$ $m_e/m_i$, the kinetic-scale turbulence that develops will be too weak to play a significant role in energy conversion and particle acceleration. Therefore, the energy conversion will be mostly controlled by laminar physics or multi-x-line reconnection.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Micromechanical Surrogate Machine Learning Model for Creep Deformation Modeling

Process variability during the manufacture of gas turbine engine hot section components can significantly affect the material’s resulting microstructure. In casting, for instance, geometric variation within a component (thin sections versus thick sections, radial location) influences cooling rates and the resulting grain size. The high temperature creep response is known to be sensitive to grain size owing to a diffusional creep mechanism which occurs more readily along grain boundaries. Microstructural variation correspondingly drives mechanical behavior which propagates into component scale performance uncertainty. These factors are essential when planning inspection, maintenance, and repair strategies within a reliability framework. These benefits provide opportunities to increase overall energy efficiency through refined margins. Critically, there is an opportunity to bolster existing data-driven reliability models using physics-driven process-structure-property relations. Here we present recent work establishing a framework for evaluating the probabilistic creep performance of high-temperature materials. A novel microstructure-sensitive crystal plasticity finite element model is established that captures both grain boundary and crystallographic deformation effects. The computationally expensive physics model is calibrated using a statistical approach and this high-fidelity model is subsequently used to train a computationally efficient machine learning surrogate model. The surrogate model is essential for sampling a large ensemble of simulated structure-property pair results. The ensemble data are then mined to extract salient trends to be incorporated into a microstructure-sensitive reliability model. The proposed approach represents a novel way to capture microstructure-sensitive trends from physics-based models within a modern reliability framework.

Fernandez-Zelaia, Patxi [ORNL]↗
DOE OSTI2024

Predicting thermophysical properties of molten salts in the MgCl 2 -NaCl-KCl-LiCl system with a shell-model potential

Ternary eutectic salts composed of MgCl 2 , NaCl, and KCl, referred to as MNK salts, have recently emerged as promising candidates as high-temperature heat transfer fluids and thermal energy storage media. Here we performed classical molecular dynamics (MD) simulations to predict the densities, specific heat capacities, viscosities, and ionic self-diffusivities for MNK salts over a wide temperature range. The impact of LiCl additive on their thermophysical properties was also investigated. To capture the electronic polarization of Cl anions by neighboring cations, we developed a novel shell-model potential using the force-matching method and a dataset of ab initio calculated interatomic forces. Our extensive MD simulations predict structure and properties for pure salts and binary/ternary salt mixtures in the MgCl 2 -NaCl-KCl-LiCl system in overall good agreement with available experimental and theoretical data, which corroborates the accuracy and reliability of our developed potential.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Predictive multiscale modeling for Unidirectional Carbon Fiber Reinforced Polymers

This paper presents a predictive multiscale modeling scheme for Unidirectional (UD) Carbon Fiber Reinforced Polymers (CFRP). A bottom-up modeling procedure is discussed for predicting the performance of UD structures. UD material responses are computed from high fidelity Representative Volume Elements (RVEs). A data-driven Reduced Order Modeling approach compresses RVEs into Reduced Order Models so material responses can be computed in a concurrent fashion along with the structural level simulation. The approach presented in this paper is validated against experimental data and is believed to provide design guidance for future fiber reinforced polymers development.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The Contribution of Subtropical Moisture Within an Atmospheric River on Moisture Flux, Cloud Structure, and Precipitation Over the Salmon River Mountains of Idaho Using Moisture Tracers

The impact of an atmospheric river (AR) on the flux of subtropical moisture across Idaho's Salmon River Mountains and precipitation over the mountains is evaluated using the Weather, Research, and Forecasting model with water vapor tracers (WRF-WVT). The AR impacted Idaho between 17 and 19 January 2017 during the Seeded and Natural Orographic Wintertime Clouds: The Idaho Experiment (SNOWIE) campaign. WRF-WVT is configured to isolate the subtropical moisture contribution to the AR, the moisture flux, and precipitation. Subtropical water vapor advected by the AR into Idaho is tagged and tracked in three-dimensional space throughout the run. This allows the contribution of the subtropical moisture to the vertical distribution of water vapor and the precipitation to be directly calculated. The simulated cloud structure is compared with airborne radar data collected during two SNOWIE intensive operation periods. This study found that more than 70% of the moisture flux and more than 80% of the precipitation across the Idaho Mountains during SNOWIE IOP 4 could be attributed to subtropical moisture within the AR. Nearly all of the moisture flux in the upper cloud and 50% of the moisture in the lower cloud was attributable to the subtropical moisture. The subtropical moisture contribution within the AR to precipitation ranged from 35% in northern Idaho to more than 90% in southern Idaho. Across the entire period of impact of the AR, more than 60% of precipitation in Idaho was attributable to the subtropical moisture within the AR, with this percentage increasing toward the south across the state.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Molecular determinants of pH sensing in the proton-activated chloride channel

In response to acidic pH, the widely expressed proton-activated chloride (PAC) channel opens and conducts anions across cellular membranes. By doing so, PAC plays an important role in both cellular physiology (endosome acidification) and diseases associated with tissue acidosis (acid-induced cell death). Despite the available structural information, how proton binding in the extracellular domain (ECD) leads to PAC channel opening remains largely unknown. Here, through comprehensive mutagenesis and electrophysiological studies, we identified several critical titratable residues, including two histidine residues (H130 and H131) and an aspartic acid residue (D269) at the distal end of the ECD, together with the previously characterized H98 at the transmembrane domain–ECD interface, as potential pH sensors for human PAC. Mutations of these residues resulted in significant changes in pH sensitivity. Some combined mutants also exhibited large basal PAC channel activities at neutral pH. By combining molecular dynamics simulations with structural and functional analysis, we further found that the β12 strand at the intersubunit interface and the associated “joint region” connecting the upper and lower ECDs allosterically regulate the proton-dependent PAC activation. Our studies suggest a distinct pH-sensing and gating mechanism of this new family of ion channels sensitive to acidic environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Evaluation of Thermal Neutron Scattering Cross Section of Uranium Silicide with Ab Initio Lattice Dynamics

Uranium silicide (U 3 Si 2 ) is a candidate material for the high-density nuclear fuel in commercial light water reactors [1], [2]. Its higher uranium density, 11.3 g-U/cm3, compared to that of uranium dioxide (UO 2 ), 9.7 g-U/cm3, can improve the performance of a nuclear reactor while using low enriched uranium (LEU) and diversify the choice of cladding materials [1]–[3]. It also has a higher thermal conductivity than UO 2 , which can reduce the thermal stress on the material caused by a temperature gradient across the fuel pellet and provide a larger margin for some postulated accidents [1], [2], [4]. Furthermore, compared to U3Si, another high-density fuel candidate, it has better resistance to in-pile swelling due to less irradiation-induced rapid amorphization [1], [3]. Corresponding to its importance in nuclear engineering, many previous studies have reported the properties of U3Si2. Experiments showed that U 3 Si 2 is a paramagnetic (PM) metal, where a slight linear increase in magnetic susceptibility was measured with increasing temperature [5], [6]. In addition, thermodynamic quantities such as thermal expansion coefficient, heat capacity, and thermal conductivity were experimentally determined over a wide temperature range [1], [7], [8]. In several computational studies, ab initio atomistic simulations based on density functional theory (DFT) were performed to calculate various properties including elastic constants, electronic density of states (DOS), and phonon dispersion curves [9]–[12]. Nevertheless, thermal neutron scattering cross sections, which are critical to the prediction of the parameters in reactor physics that are ultimately related to reactor criticality, have not yet been evaluated for U3Si2. The scattering cross section can be calculated from the phonon DOS, or the energy spectrum of lattice vibrations, of the crystalline system [13], [14]. However, there is also no experimental data available for the phonon DOS of U 3 Si 2 . While some computational studies reported the phonon DOS and/or dispersion curves from ab initio simulations [9]–[12], the accuracy cannot be guaranteed because it is unclear whether the spin-polarization behavior of PM U 3 Si 2 was properly described. In the present study, the thermal neutron scattering cross section for U 3 Si 2 is evaluated for the first time by calculating the phonon DOS for U3Si2 from ab initio lattice dynamics (AILD) simulations based on DFT. First, U 3 Si 2 is modeled based on the experimental structure, and AILD simulations are performed on the modeled U3Si2 to optimize the structure. Next, AILD simulations are performed for supercells with atomic displacement to calculate Hellmann-Feynman forces. Based on the calculated forces, partial phonon DOSs for U and Si are obtained, and the thermal neutron scattering law (TSL) for U 3 Si 2 is finally evaluated. To verify the accuracy of the calculations in the present study, the calculation results are compared with experimental data on the structure and heat capacity of U3Si2 [1], [7], [8], [15].

Geometry Optimization↗
DOE OSTI2023

Constructing the Mechanism of Dinoflagellate Luciferin Bioluminescence Using Computation

Dinoflagellate luciferin bioluminescence is unique since it does not rely on decarboxylation but is poorly understood compared to that of firefly, bacteria, and coelenterata luciferins. Here, in this work, we computationally investigate possible protonation states, stereoisomers, a chemical mechanism, and the dynamics of the bioluminescence intermediate that is responsible for chemiexcitation. Using semiempirical dynamics, time-dependent density functional theory static calculations, and a correlation diagram, we find that the intermediate’s functional group that is likely responsible for chemiexcitation is a 4-member ring, a dioxetanol, that undergoes [2π + 2π] cycloreversion and the biolumiphore is the cleaved structure. The simulated emission spectra and luciferase-dependent absorbance spectra agree with the experimental data, giving support to our proposed mechanism and biolumiphore. We also compute circular dichroism spectra of the intermediate’s four stereoisomers to guide future experiments in differentiating them.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗