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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 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Feedback control design for non-inductively sustained scenarios in NSTX-U using TRANSP

This paper examines a method for real-time control of non-inductively sustained scenarios in NSTX-U by using TRANSP,a time-dependent integrated modeling code for prediction and interpretive analysis of tokamak experimental data, as asimulator. The actuators considered for control in this work are the six neutral beam sources and the plasma boundaryshape. To understand the response of the plasma current, stored energy, and central safety factor to these actuatorsand to enable systematic design of control algorithms, simulations were run in which the actuators were modulated anda linearized dynamic response model was generated. A multi-variable model-based control scheme that accounts for thecoupling and slow dynamics of the system while mitigating the effect of actuator limitations was designed andsimulated. Simulations show that modest changes in the outer gap and heating power can improve the response time ofthe system, reject perturbations, and track target values of the controlled values.

Predictive simulations↗
DOE OSTI2026

Dynamics of iodine geminate recombination in supercritical xenon solvent: Caging effect

Understanding the dynamics of chemical reactions in solutions is vital, as their rates and kinetics are significantly affected by the solvent environment. Supercritical solvents offer extensive applications in chemical reactions by enabling the manipulation of the solution environment. Here, in this study, we investigate the geminate recombination of iodine in a supercritical xenon solvent by using ReaxFF-based molecular dynamics simulations. Our findings reveal that the highest iodine recombination rate occurs near supercritical conditions, while lower-pressure conditions lead to reduced collision rates and unstable recombination, and higher-pressure conditions hinder iodine diffusion, resulting in a lower recombination rate. Our analysis shows that the xenon local density at the time of recombination is at least 2.5 times higher than the global density, confirming the presence of xenon clusters surrounding the Iodine atoms. This observation is further supported by coordination number analysis, which confirms an elevated xenon local density during recombination. In addition, the correlation between the total energy of xenon atoms within a cluster and recombined iodine atoms underscores the kinetic energy transfer process, validating the occurrence of geminate recombination. The excess kinetic energy from the recombining iodine atoms is transferred to the surrounding xenon atoms. Our examination of geminate recombination demonstrates that iodine atoms confined within xenon clusters—whether through manual insertion of atoms or the fast dissociation of an iodine molecule within xenon clusters—are more likely to recombine as primary geminate recombination. However, extending the iodine molecule dissociation time allows iodine atoms to diffuse out of the cluster, and the recombination to shift toward secondary geminate recombination.

Cage effect↗
DOE OSTI2025

Stage-local partitioned two-step runge-kutta methods for large systems of ordinary differential equations

We introduce stage-local partitioned two-step Runge-Kutta methods are an extension of standard two-step Runge-Kutta methods, which are an alternative to the standard additive two-step Runge-Kutta methods currently existing in the literature. Furthermore, these new schemes are designed with an eye towards truly N-partitioned systems and leverage local stage approximations to make several computationally interesting approximations viable. Specifically, the focus on local stage approximations makes possible the construction of truly asynchronous schemes, in the parallel sense, possible. In addition, we show that an implicit-explicit approach to these schemes can lead to methods that require the inversion of only local nonlinear systems.

Applied Dynamical Systems↗
DOE OSTI2019

Wireless charging and shared autonomous battery electric vehicles (W+SABEV): synergies that accelerate sustainable mobility and greenhouse gas emission reduction

Emerging technologies play important roles in shaping future mobility systems and impacting sustainability performance of the transportation sector in major economies, such as the United States of America (USA) and China. This study applies a life cycle framework to demonstrate and evaluate the synergies of the following four emerging transportation system technologies both qualitatively and quantitatively: (1) wireless charging; (2) shared mobility services; (3) autonomous driving; and (4) battery electric vehicles (BEV). The new concept of a wireless charging and shared autonomous battery electric vehicle (W+SABEV) system is introduced and modeled. First, an analytical framework is presented to assess the pros and cons of the W+SABEV system vs. a conventional plug-in charging BEV system, adhering to the principles of sustainable mobility and highlighting the impacts and dynamics of the disruptive technologies on the key parameters that define sustainable mobility. Second, a quantitative analysis presents the synergies of the four technologies by modeling a W+SABEV system and demonstrates that the combination of the four technologies can shorten the payback time of greenhouse gas (GHG) emission burdens for infrastructure and vehicles. Finally, compared to a plug-in charging BEV system, a W+SABEV system pays back the additional GHG emission burdens of wireless charging infrastructure deployment within 5 years if the wireless charging utility factor (ratio of en route charging time vs. trip time) is above 19%.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Exploring temporal community evolution: algorithmic approaches and parallel optimization for dynamic community detection

Abstract Dynamic (temporal) graphs are a convenient mathematical abstraction for many practical complex systems including social contacts, business transactions, and computer communications. Community discovery is an extensively used graph analysis kernel with rich literature for static graphs. However, community discovery in a dynamic setting is challenging for two specific reasons. Firstly, the notion of temporal community lacks a widely accepted formalization, and only limited work exists on understanding how communities emerge over time. Secondly, the added temporal dimension along with the sheer size of modern graph data necessitates new scalable algorithms. In this paper, we investigate how communities evolve over time based on several graph metrics under a temporal formalization. We compare six different algorithmic approaches for dynamic community detection for their quality and runtime. We identify that a vertex-centric (local) optimization method works as efficiently as the classical modularity-based methods. To its advantage, such local computation allows for the efficient design of parallel algorithms without incurring a significant parallel overhead. Based on this insight, we design a shared-memory parallel algorithm DyComPar , which demonstrates between 4 and 18 fold speed-up on a multi-core machine with 20 threads, for several real-world and synthetic graphs from different domains.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Theory of Ion-Mediated Segmental Localization, Activated Structural Relaxation, and the Glass Transition in Polymerized Ionic Liquids

Here we combine polymer integral equation theory for structural correlations with a force-level theory for activated segmental relaxation to construct a microscopic theory for how ions modify the onset of segmental localization, the polymer alpha relaxation time, and glass transition temperature, T g , in dry polymerized ionic liquids (PolyILs). Our most important findings concerning the behavior of T g are (i) a weak dependence on anion–cation Coulomb attraction strength due to strong decoupling of ion and segmental dynamics, (ii) strong reduction with increasing mobile ion size due to both plasticization effects and weakening of ion-modified monomer caging, and (iii) increase with backbone rigidity and intrachain dynamic cooperativity. We quantitatively estimate T g variations as ion size and polymer static and dynamic rigidity are widely varied. The experimental data of 19 PolyILs are organized into a specific pattern consistent with the theoretical predictions with glass transition temperatures varying over a very wide range (~250 K) as observed experimentally. Based on the theoretical results, suggestions are made concerning the search for high conductivity Li- or Na-based PolyILs based on further lowering of T g via new polymer synthesis. Calculations of the alpha time as a function of packing fraction reveal the dynamic fragility increases for larger mobile ions, a more flexible backbone, and/or a smaller degree of intrachain dynamic cooperativity, as a consequence of the increasing importance of collective elasticity in determining the activation barrier. An analysis of transient segmental localization and a crossover to activated dynamics reveals similar, but not identical, trends as predicted at the laboratory vitrification timescale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Damping constant estimation in magnetoresistive readers

The damping constant is a key design parameter in magnetic reader design. Its value can be derived from bulk or sheet film ferromagnetic resonance (FMR) line width. However, dynamics of nanodevices is usually defined by presence of non-uniform modes. It triggers new damping mechanisms and produces stronger damping than expected from traditional FMR. This work proposes a device-level technique for damping evaluation, based on time-domain analysis of thermally excited stochastic oscillations. The signal is collected using a high bandwidth oscilloscope, by direct probing of a biased reader. Recorded waveforms may contain different noise signals, but free layer FMR is usually a dominating one. The autocorrelation function is a reflection of the damped oscillation curve, averaging out stochastic contributions. The damped oscillator formula is fitted to autocorrelation data, producing resonance frequency and damping constant values. Restricting lag range allows for mitigation of the impact of other phenomena (e.g., reader instability) on the damping constant. For a micromagnetically modeled reader, the technique proves to be much more accurate than the stochastic FMR line width approach. Application to actual reader waveforms yields a damping constant of ∼0.03.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

The behaviour of PM10 and ozone in Malaysia through non-linear dynamical systems

Prediction of ozone (O3) and PM10 is very important as both these air pollutants affect human health, human activities and more. Short-term forecasting of air quality is needed as preventive measures and effective action can be taken. Therefore, if it is detected that the ozone data is of a chaotic dynamical systems, a model using the nonlinear dynamic from chaos theory data can be made and thus forecasts for the short term would be more accurate. This study uses two methods, namely the 0-1 Test and Lyapunov Exponent. In addition, the effect of noise reduction on the analysis of time series data will be seen by using two smoothing methods: Rectangular methods and Triangle methods. At the end of the study, recommendations were made to get better results in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

THE QUIESCENT X-RAY PROPERTIES OF THE ACCRETING MILLISECOND X-RAY PULSAR AND ECLIPSING BINARY SWIFT J1749.4-2807

Swift J1749.4-2807 is a transient neutron star low-mass X-ray binary that contains an accreting millisecond X-ray pulsar spinning at 518 Hz. It is the first of its kind that displays X-ray eclipses, which holds significant promise to precisely constrain the mass of the neutron star. We report on a {approx_equal} 105 ks long XMM-Newton observation performed when Swift J1749.4-2807 was in quiescence. We detect the source at a 0.5-10 keV luminosity of {approx_equal}1 Multiplication-Sign 10{sup 33}(D/6.7 kpc){sup 2} erg s{sup -1}. The X-ray light curve displays three eclipses that are consistent in orbital phase and duration with the ephemeris derived during outburst. Unlike most quiescent neutron stars, the X-ray spectrum can be adequately described with a simple power law, while a pure-hydrogen atmosphere model does not fit the data. We place an upper limit on the 0.01-100 keV thermal luminosity of the cooling neutron star of {approx}< 2 Multiplication-Sign 10{sup 33} erg s{sup -1} and constrain its temperature to be {approx}< 0.1 keV (for an observer at infinity). Timing analysis does not reveal evidence for X-ray pulsations near the known spin frequency of the neutron star or its first overtone with a fractional rms of {approx}< 34% and {approx}< 28%, respectively. We discuss the implications of our findings for dynamical mass measurements, the thermal state of the neutron star, and the origin of the quiescent X-ray emission.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Strong evidence that the galactic bulge is shining in gamma rays

There is growing evidence that the Galactic Center Excess identified in the Fermi-LAT gamma-ray data arises from a population of faint astrophysical sources. We provide compelling supporting evidence by showing that the morphology of the excess traces the stellar over-density of the Galactic bulge. By adopting a template of the bulge stars obtained from a triaxial 3D fit to the diffuse near-infrared emission, we show that it is detected at high significance. The significance deteriorates when either the position or the orientation of the template is artificially shifted, supporting the correlation of the gamma-ray data with the Galactic bulge. In deriving these results, we have used more sophisticated templates at low-latitudes for the Fermi bubbles compared to previous work and the three-dimensional Inverse Compton (IC) maps recently released by the GALPROP team. Our results provide strong constraints on Millisecond Pulsar (MSP) formation scenarios proposed to explain the excess. We find that an admixture formation scenario, in which some of the relevant binaries are primordial and the rest are formed dynamically, is preferred over a primordial-only formation scenario at 7.6σ confidence level. Our detailed morphological analysis also disfavors models of the disrupted globular clusters scenario that predict a spherically symmetric distribution of MSPs in the Galactic bulge. For the first time, we report evidence of a high energy tail in the nuclear bulge spectrum that could be the result of IC emission from electrons and positrons injected by a population of MSPs and star formation activity from the same site.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Sixfold Way of Traversable Wormholes in the Sachdev-Ye-Kitaev Model

In the infrared limit, a nearly anti–de Sitter spacetime in two dimensions ( AdS 2 ) perturbed by a weak double trace deformation and a two-site ( q > 2 )-body Sachdev-Ye-Kitaev (SYK) model with N Majoranas and a weak 2 r -body intersite coupling share the same near-conformal dynamics described by a traversable wormhole. We exploit this relation to propose a symmetry classification of traversable wormholes depending on N , q , and r , with q > 2 r , and confirm it by a level statistics analysis using exact diagonalization techniques. Intriguingly, a time-reversed state never results in a new state, so only six universality classes occur—A, AI, BDI, CI, C, and D—and different symmetry sectors of the model may belong to distinct universality classes. Published by the American Physical Society 2024

Physics↗
DOE OSTI2026

Prognostic simulations of mixed-phase clouds with model AC-1D v1.0: the impact of aerosol types and freezing parameterizations on ice crystal budgets

Mixed-phase clouds at high latitudes contribute to the uncertainty in predicting cloud feedbacks and climate sensitivity, mainly due to the complexity of microphysical processes that influence the partitioning between the supercooled liquid and ice phases, and hence, cloud radiative effects on regional scales. Particularly in Arctic mixed-phase clouds, the activation of ice-nucleating particles (INPs) from various aerosol populations remains a leading source of uncertainty. We developed an aerosol-cloud one-dimensional (AC-1D) model, which provides a novel framework to prognostically treat INP and ice crystal budgets while explicitly accounting for polydisperse and multicomponent aerosol that activate INPs following different freezing parameterizations. The AC-1D model is informed by large-eddy simulations to probe the impact of INP representation on predicted ice crystal number concentrations (N i ) and ice crystal budgets in mixed-phase Arctic stratus. We apply three immersion freezing (IMF) parameterizations, two time-independent (singular) and one time-dependent (classical nucleation theory), to predict the evolution of the INP reservoir and resulting ice crystal budget from polydisperse mineral dust, organic (humic-like substances), and sea spray aerosol particle size distributions. Our analysis focuses on how variations in aerosol number concentration and cloud system parameters such as cloud cooling rate, cloud-top entrainment rate, and ice crystal fall speed influence the INP reservoir and ice crystal budgets. Furthermore, this study investigates the competitive ice nucleation dynamics in mixed aerosol environments and provides a process-level quantification of the INP budget terms, which directly controls ice crystal budgets. For all studied case scenarios, the aerosol types and associated particle size distributions significantly impact INP and N i , and the choice between a time-dependent and a singular freezing description yields orders-of-magnitude differences in the predicted INP and N i over the 10 h simulation time, reflecting typical cloud lifetimes. Our results show that the influence of cloud cooling, INP entrainment, and sedimentation varies significantly depending on the chosen freezing parameterization. These findings underscore the critical need for robust IMF parameterizations and precise cloud system observations to enhance the accuracy of models in predicting mixed-phase cloud structure and evolution.

Arctic clouds↗
DOE OSTI2020

Full circle mechanical dynamic characterization including experimental modal analysis and finite element analysis

During operation, it was observed that a specific mechanical system experienced undesirable vibration and it became necessary to understand and mitigate this phenomenon. This document investigates the tools, methodology, and results of the dynamic characterization of the system. The characterization makes use of the experimental modal analysis (EMA) methods of single input multiple output (SIMO) and single input single output (SISO). The validity of the theory of reciprocity is confirmed to minimize measurement error, cost, and time of repeat testing. Finite element analysis (FEA) is used in choosing transducer and modal impact locations to adequately characterize the system. Single degree of freedom (SDOF) and multiple degree of freedom (MDOF) curve fitting is used to fully characterize the system’s mode shapes and natural frequencies. The EMA characterization results are used to modify and validate the FEA model so that FEA can be used to model potential structural modifications to the system to mitigate the undesirable vibration. Structural modifications are chosen, implemented, and their effectiveness is quantified using EMA. Finally, a qualitative evaluation of the methodology of FEA validation by EMA and tuning of the model to match the experimental results is discussed.

42 ENGINEERING↗
DOE OSTI2019

Dynamic simulation and techno-economic analysis of a concentrated solar power (CSP) plant hybridized with both thermal energy storage and natural gas

The addition of thermal energy storage and natural gas as a complementary energy source improves the flexibility, reliability, and value of concentrated solar power (CSP) plants. Nevertheless, due to the transient nature of solar energy, transitions from solar-only mode and natural-gas mode to hybrid solar-natural gas mode is quite challenging, especially when the plant is equipped with thermal storage. Thus, it is important to develop proper dynamic modeling and control schemes to accurately simulate such transitions. The objective of this study is to address this subject by demonstrating a dynamic model with reliable control schemes for a highly integrated hybrid parabolic trough-natural gas plant equipped with thermal energy storage. The specific goal is to study the dynamics of adding thermal storage to the hybrid plant. It is found that the developed control schemes assist smooth transitions between different operational modes and effective utilization of thermal storage and natural gas to maintain steady power production and steam mass flow rates under different solar conditions. The results demonstrate that the integration of storage regulates power production by solar energy and natural gas during the day time. It also enables an increase in the solar fraction of the hybrid plant while it causes a small decrease in thermodynamic efficiency. The analysis shows that the hybrid plant with the storage has a substantially lower specific CO 2 emission (0.320 tonne/MWh) than single natural gas plant (0.413 tonne/MWh) although it has a higher levelized cost of electricity (86.32/MWh against 74.92/MWh). The hybrid plant with storage demonstrates a promising potential for reliable and clean production of electricity, although research and development should be conducted to lower its cost.

03 NATURAL GAS↗
DOE OSTI2016

Multiscale dynamics of reactive fronts in the subsurface

1. Brief summary of progress to date. Major Goals of the Project. Overreaching goals of the proposed activity are to develop an or- ganizing framework to describe nonlinear reactive transport in geologic systems over many length and time scales, and corresponding physics-based adaptive multi-scale hybrid models. We will also provide computational tools for robust uncertainty quantification in hybrid simulations. Major Activities of the Project. The major activities in this reporting period have focused on developing a time-averaging framework for ADR transport (Task 1) and global diagnosis criteria for spatio-temporal algorithm refinement (Task 2), as well as numerical validation and verification of the analytical approaches developed. The main activities are as follows: (a) We use homogenization theory to perform a spatio-temporal upscaling of pore-scale advection- diffusion equation in a periodic porous medium in the presence of fluctuating boundary conditions on some parts of the boundary and nonlinear chemical reaction on the solid-liquid interface and we investigate the constraints under which the macroscopic equation gives an accurate explanation of the underlying physics at the pore scale. We demonstrate that the dynamics at the continuum scale is strongly influenced by the interplay between signal frequency at the boundary and transport processes at the pore level. Furthermore, we show that by choosing appropriate scaling factors, a homogenized equation along with expressions for the effective coefficients reliably describe the concentration of solute at the length and time scales vastly different from physically robust micro-scale provided that some specific scale separation constraints are met. Our analysis proves that if the reaction rate or advection at the micro-scale are large, the effectiveness of the homogenized model is impeded. (b) We test numerically the conditions derived theoretically for advective-diffusive and reactive trans- port in a fracture with planar walls subject to temporally oscillating Dirichlet boundary conditions. The numerical analysis confirms the theoretical predictions. Significant Results. Two paper are in preparation. 2. Description of work yet to be accomplished The Tasks yet to be accomplished are listed below: (a) Quantify the impact of uncertainty in wall geometry of planar fractures on predictions hybrids of ARD transport (b) Develop coupling conditions for time hybridzation (c) Quantify the impact of uncertainty in pore geometry on predictions of hybrids of ARD transport in porous media, i.e. develop stochastic hybrid models (d) Use the hybrids combined with X-Ray tomographic images of pore scale structure (from Dr. Gouze, see letter of collaboration) to model dynamic changes in porosity/permeability

42 ENGINEERING↗
DOE OSTI2022

Optimal Electric Grid Black Start Restoration Subject to Intentional Threats

Efficient restoration of the electric grid from significant disruptions – both natural and manmade – that lead to the grid entering a failed state is essential to maintaining resilience under a wide range of threats. Restoration follows a set of black start plans, allowing operators to select among these plans to meet the constraints imposed on the system by the disruption. Restoration objectives aim to restore power to a maximum number of customers in the shortest time. Current state-of-the-art for restoration modeling breaks the problem into multiple parts, assuming a known network state and full observability and control by grid operators. These assumptions are not guaranteed under some threats. This paper focuses on a novel integration of modeling and analysis capabilities to aid operators during restoration activities. A power flow-informed restoration framework, comprised of a restoration mixed-integer program informed by power flow models to identify restoration alternatives, interacts with a dynamic representation of the grid through a cognitive model of operator decision-making, to identify and prove an optimal restoration path. Application of this integrated approach is illustrated on exemplar systems. Validation of the restoration is performed for one of these exemplars using commercial solvers, and comparison is made between the steps and time involved in the commercial solver, and that required by the restoration optimization in and of itself, and by the operator model in acting on the restoration optimization output. Publications and proposals developed under this work, along with a path forward for additional expansion of the work, and summary of what was achieved, are also documented.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Testing thermal conductivity models with equilibrium molecular dynamics simulations of the one-component plasma

Equilibrium molecular dynamics simulations are used to calculate the thermal conductivity of the onecomponent plasma via the Green-Kubo formalism over a broad range of Coulomb coupling strength, 0.1 ≤ Γ ≤180. These simulations address previous discrepancies between computations using equilibrium versus nonequilibrium methods. Analysis of heat flux autocorrelation functions show that very long (6×10 5 $ω^{-1}_{p}$) time series are needed to reduce the noise level to allow ≲2% accuracy. The simulations provide accurate data for Γ ≲ 1. Furthermore, this enables a test of the traditional Landau-Spitzer theory, which is found to agree with the simulations for Γ ≲ 0.3. It also enables tests of theories to address moderate and strong Coulomb coupling. Two are found to provide accurate extensions to the moderate coupling regime of Γ ≲ 10, but none are accurate in the Γ ≳ 10 regime where potential energy transport and coupling between mass flow and stress dominate thermal conduction.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Exploring Transport Behavior in Hybrid Perovskites Solar Cells via Machine Learning Analysis of Environmental-Dependent Impedance Spectroscopy

Hybrid organic–inorganic perovskites are one of the promising candidates for the next-generation semiconductors due to their superlative optoelectronic properties. However, one of the limiting factors for potential applications is their chemical and structural instability in different environments. Herein, the stability of (FAPbI3)0.85(MAPbBr3)0.15 perovskite solar cell is explored in different atmospheres using impedance spectroscopy. An equivalent circuit model and distribution of relaxation times (DRTs) are used to effectively analyze impedance spectra. DRT is further analyzed via machine learning workflow based on the non-negative matrix factorization of reconstructed relaxation time spectra. This exploration provides the interplay of charge transport dynamics and recombination processes under environment stimuli and illumination. The results reveal that in the dark, oxygen atmosphere induces an increased hole concentration with less ionic character while ionic motion is dominant under ambient air. Under 1 Sun illumination, the environment-dependent impedance responses show a more striking effect compared with dark conditions. In this case, the increased transport resistance observed under oxygen atmosphere in equivalent circuit analysis arises due to interruption of photogenerated hole carriers. The results not only shed light on elucidating transport mechanisms of perovskite solar cells in different environments but also offer an effective interpretation of impedance responses.

36 MATERIALS SCIENCE↗