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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Multi-regime mixing modeling for local extinction and re-ignition in turbulent non-premixed flame by using LES/FDF method

Local extinction and re-ignition occur in turbulent non-premixed combustion when the Damköhler number is not large enough and the combustion is not fully mixing controlled. The occurrence of local extinction introduces locally extinguished flame holes followed by a premixed flame propagation toward the hole center to potentially reignite the flame. The co-existence of the non-premixed and premixed combustion regimes complicates the modeling since traditional combustion models are mostly for a single regime. In this work, we examine the effect of multi-regime mixing modeling in the transported filtered density function (FDF) method on the predictions of local extinction and reignition. Predictions of local extinction and reignition remain a challenge for the FDF method despite the progress made in the past. To account for the multi-regime combustion, two different mixing timescale models for non-premixed and premixed combustion are combined. A flame index based on the gradients of fuel and oxidizer is used to define a weighting factor to blend the two mixing timescale models. A turbulent jet non-premixed flame with substantial local extinction, the Sydney piloted jet flame L, is adopted as a test case to examine the performance of the multi-regime model in large-eddy simulation/FDF modeling. It is found that the traditional non-premixed mixing timescale model when combined with the modified Curl mixing leads to global extinction for the Sydney flame L without the presence of the premixed combustion regime. After accounting for the multi-regime combustion with proper detection of the different combustion regimes, the predictions for the flame statistics and the amount of local extinction are significantly improved. Furthermore, it suggests the need of including multi-regime combustion for the predictions of local extinction and re-ignition in turbulent non-premixed combustion configurations.

42 ENGINEERING↗
DOE OSTI2023

Local Bayesian Dirichlet mixing of imperfect models

Abstract To improve the predictability of complex computational models in the experimentally-unknown domains, we propose a Bayesian statistical machine learning framework utilizing the Dirichlet distribution that combines results of several imperfect models. This framework can be viewed as an extension of Bayesian stacking. To illustrate the method, we study the ability of Bayesian model averaging and mixing techniques to mine nuclear masses. We show that the global and local mixtures of models reach excellent performance on both prediction accuracy and uncertainty quantification and are preferable to classical Bayesian model averaging. Additionally, our statistical analysis indicates that improving model predictions through mixing rather than mixing of corrected models leads to more robust extrapolations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Probing scrambling and operator size distributions using random mixed states and local measurements

The dynamical spreading of quantum information through a many-body system, typically called scrambling, is a complex process that has proven to be essential to describe many properties of out-of-equilibrium quantum systems. Scrambling can, in principle, be fully characterized via the use of out-of-time-ordered correlation functions, which are notoriously hard to access experimentally. In this work, we put forward an alternative toolbox of measurement protocols to experimentally probe scrambling by accessing properties of the operator size probability distribution, which tracks the size of the support of observables in a many-body system over time. Our measurement protocols require the preparation of separable mixed states together with local operations and measurements, and combine the tools of randomized operations, a modern development of near-term quantum algorithms, with the use of mixed states, a standard tool in NMR experiments. We demonstrate how to efficiently probe the probability-generating function of the operator distribution and discuss the challenges associated with obtaining the moments of the operator distribution. We further show that manipulating the initial state of the protocol allows us to directly obtain the individual elements of the distribution for small system sizes. Published by the American Physical Society 2024

Blocher, Philip Daniel (ORCID:0000000163027567)↗
DOE OSTI2023

Probing Ultrafast Electron (De)localization Dynamics in Mixed Valence Complexes Using Femtosecond X-ray Spectroscopy (Final Report)

The central goal of this proposal was to directly visualize and quantify how electronic correlations, vibronic couplings, and local solute-solvent interactions control intramolecular electron motion on the femtosecond time scale. The proposed research program focused on solvated Ruthenium (Ru) based mixed-valence complexes, a prototypical class of transition-metal complexes, which are of significant interest for their potential applications in photochemical energy conversion. Electron movements following photochemical excitation are closely coupled with atomic/vibrational and solvent motion. To disentangle these various components requires tools designed to directly probe electron correlations and vibronic coupling (coherently coupled motions of electronic and vibrational coordinates) on the timescale of electron motion in the solution phase.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Effective rationality for local unitary invariants of mixed states of two qubits

Abstract We calculate the field of rational local unitary invariants for mixed states of two qubits, by employing methods from algebraic geometry. We prove that this field is rational (i.e. purely transcendental), and that it is generated by nine algebraically independent polynomial invariants. We do so by constructing a relative section, in the sense of invariant theory, whose Weyl group is a finite abelian group. From this construction, we are able to give explicit expressions for the generating invariants in terms of the Bloch matrix representation of mixed states of two qubits. We also prove similar rationality results for the local unitary invariants of symmetrically mixed states of two qubits. We also provide a sketch of how to generalize our results to the case of an arbitrary number of qubits. Our results apply to both complex-valued and real-valued invariants.

Physics↗
DOE OSTI2020

Mixed-State Entanglement from Local Randomized Measurements

In this work, we propose a method for detecting bipartite entanglement in a many-body mixed state based on estimating moments of the partially transposed density matrix. The estimates are obtained by performing local random measurements on the state, followed by postprocessing using the classical shadows framework. Our method can be applied to any quantum system with single-qubit control. We provide a detailed analysis of the required number of experimental runs, and demonstrate the protocol using existing experimental data [Brydges et al., Science 364, 260 (2019)].

1-dimensional spin chains↗
DOE OSTI2021

Local structure and distortions of mixed methane-carbon dioxide hydrates

A vast source of methane is found in gas hydrate deposits, which form naturally dispersed throughout ocean sediments and arctic permafrost. Methane may be obtained from hydrates by exchange with hydrocarbon byproduct carbon dioxide. It is imperative for the development of safe methane extraction and carbon dioxide sequestration to understand how methane and carbon dioxide co-occupy the same hydrate structure. Pair distribution functions (PDFs) provide atomic-scale structural insight into intermolecular interactions in methane and carbon dioxide hydrates. We present experimental neutron PDFs of methane, carbon dioxide and mixed methane-carbon dioxide hydrates at 10 K analyzed with complementing classical molecular dynamics simulations and Reverse Monte Carlo fitting. Mixed hydrate, which forms during the exchange process, is more locally disordered than methane or carbon dioxide hydrates. The behavior of mixed gas species cannot be interpolated from properties of pure compounds, and PDF measurements provide important understanding of how the guest composition impacts overall order in the hydrate structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Local wave-number model for inhomogeneous two-fluid mixing

We analyze the local wave-number (LWN) model, a two-point spectral closure model for turbulence, as applied to the Rayleigh-Taylor (RT) instability, the flow induced by the relaxation of a statically-unstable density stratification. Model outcomes are validated against data from 3D simulations of the RT instability. In the first part of the study we consider the minimal model terms required to capture inhomogeneous mixing and show that this version, with suitable model coefficients, is sufficient to capture the evolution of important mean global quantities including mix-width, turbulent mass flux velocity, and Reynolds stress, if the start time is chosen such that the earliest transitions are avoided. However, this simple model does not permit the expected finite asymptote of the density-specific-volume covariance b. In the second part of the study, we investigate two forms for a source term for the evolution of the spectrum of density-specific-volume covariance for the LWN model. The first includes an empirically motivated calibration of the source to achieve the final asymptotic state of constant b. Here, the second form does not require calibration but, in conjunction with enhanced diffusion and drag captures the full evolution of all the dynamical quantities, namely, the mix-layer growth, turbulent mass-flux velocity, Reynolds stress, as well as the desired behavior of b.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Spatially and Temporally Detailed Water and Carbon Footprints of U.S. Electricity Generation and Use

Electricity generation in the United States entails significant water usage and greenhouse gas emissions. However, accurately estimating these impacts is complex due to the intricate nature of the electric grid and the dynamic electricity mix. Existing methods to estimate the environmental consequences of electricity use often generalize across large regions, neglecting spatial and temporal variations in water usage and emissions. Consequently, electric grid dynamics, such as temporal fluctuations in renewable energy resources, are often overlooked in efforts to mitigate environmental impacts. The U.S. Department of Energy (DOE) has initiated the development of resilient energyshed management systems, requiring detailed information on the local electricity mix and its environmental impacts. This study supports DOE's goal by incorporating geographic and temporal variations in the electricity mix of the local electric grid to better understand the environmental impacts of electricity end users. We offer hourly estimates of the U.S. electricity mix, detailing fuel types, water withdrawal intensity, and water consumption intensity for each grid balancing authority through our publicly accessible tool, the Water Integrated Mapping of Power and Carbon Tracker (Water IMPACT). While our primary focus is on evaluating water intensity factors, our dataset and programming scripts for historical and real-time analysis also include evaluations of carbon dioxide (equivalence) intensity within the same modeling framework. This integrated approach offers a comprehensive understanding of the environmental footprint associated with electricity generation and use, enabling informed decision-making to effectively reduce Scope 2 water usage and emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Scale and Regionality of Nonelectric Markets for U.S. Nuclear Light Water Reactors

This study assesses existing and potential industries that could conceivably be directly coupled to existing nuclear reactors. The goal is to identify the scale, location, and accessibility of the candidate industrial-product markets, as well as process feedstocks that are available near the plants to establish new industries. For example, CO 2 as a feedstock can be combined with H 2 to produce formic acid (FA), transportation fuels, and lubricants. These new plants can be entirely supported with the heat and electricity provided by a nearby NPP. The potential demand for nonelectric industrial products was assessed by documenting current and possible growth of nonelectricity product markets considered. This assessment used DOE- and industry-supported tools, data, and projections to capture regional industrial market opportunities. Electricity-capacity markets that reward large and reliable generators, such as NPPs, were considered because the electricity market will likely continue to be an important revenue source to NPPs. The key is to balance the needs of energy customers so as to optimize revenue for the affiliated energy customers or partners. In most cases, flexible plant energy delivery and power generation for the grid will require either energy storage or a stock of intermediate products to sustain the industrial customers when the NPP dispatches electricity to the grid. A diverse mix of temperate regions with operating NPPs around the U.S.—representing a variety of operating markets, local generation mix, and seasonal climates—were chosen for this market study. Both current and future market opportunities for candidate industrial-product markets surrounding these NPPs were studied. Figure 2 illustrates the regions chosen for this study. The success of developing nonelectric industrial-product markets as alternative revenue-generating sources for LWRs depends, not only on demand from growing existing markets, such as petroleum refining and NH 3 production, but also on the development of new markets such as light-duty (LD) and heavy-duty (HD) hydrogen FCEVs, synfuels, chemical production, biofuels, metal refining, injection of hydrogen into NG pipelines for gas power-generating units, FA, polymers, and close-coupled industrial heat applications, all of which can significantly increase demand relative to current levels while decarbonizing energy sectors. This study also presents a sample analysis of the economics of hydrogen production in an area of Minnesota, considering the capital and operating costs of a hydrogen plant as well as the local market demand for hydrogen. It includes some assumptions on electricity-grid pricing, showing how hydrogen could be integrated with an NPP and be competitive with the incumbent hydrogen-production process, steam methane reforming (SMR). The objectives of this study include: Provide U.S. NPP operators a robust sampling of the market demand location, scale, and accessibility (including storage and transportation) of the wide variety of industrial-product choices that can be produced using nuclear thermal energy and electricity proximate to a subset of U.S. NPPs to inform the industry of the potential opportunity; show examples and trade-off analyses of how U.S. LWR operators can access these markets, including storage and transportation of industrial products to their intended markets; and present a general analysis example for one industrial product (hydrogen) in one region (Minnesota area), including production, storage, and transportation, to show how nuclear-hybrid integrated energy systems (IESs) could access local markets and improve the profitability of an NPP.

03 NATURAL GAS↗
DOE OSTI2020

Floquet dynamics of disordered bands with isolated critical energies

We investigate localization properties of driven models which exhibit a subextensive number of extended states in the static setting. We consider instances where the extended modes are or are not protected by topological considerations. To this end, we contrast the strongly driven, disordered, lowest Landau level, which we refer to as the random Landau model (RLM), with the random dimer model (RDM); the RDM also has a subextensive set of delocalized modes in the middle of the spectrum whose origin is not topological. We map the driven models on to a higher-dimensional effective model and numerically compute the localization length as a function of disorder strength, drive amplitude, and frequency using the recursive Green's function method. Our numerical results indicate that, in the presence of a strong drive (low frequency and/or large drive amplitude), the topologically protected RLM continues to exhibit a spectrum with both localized and delocalized (or critical) modes, but the spectral range of delocalized modes is enhanced by the driving. This occurs due to an admixture of the localized modes with extended modes arising due to the topologically protected critical energy in the middle of the spectrum. On the other hand, in the RDM, a weak drive immediately localizes the entire spectrum. This occurs in contrast to the naive expectation from perturbation theory that mixing between localized and delocalized modes generically enhances the delocalization of all modes. Our work highlights the importance of the origin of the delocalized modes in the localization properties of the corresponding Floquet model.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Anion-dependent phase behavior of methylimidazolium-based ionic liquids mixed with water: Correlation between local molecular structure and mesoscale behaviors

The mesoscopic phase behavior of decylmethylimidazolium (C 10 mim) ionic liquids (ILs) bearing three monovalent anions—thiocyanate (SCN − ), nitrate (NO 3 − ), and chloride (Cl − )—mixed with water at relatively high IL contents (50–95 wt%) was investigated. Small-angle and wide-angle X-ray scattering (SAXS/WAXS) were employed to follow the evolution of both local and mesoscale structures across this composition range. In the absence of water, C 10 mimSCN and C 10 mimCl behaved as disordered liquids, whereas C 10 mimNO 3 spontaneously formed a hexagonally ordered cylindrical mesophase and displayed a sticky-solid macroscopic appearance. Upon addition of water, C 10 mimSCN remained a viscous liquid and only weakly ordered lamellar domains were observed. This limited ordering is attributed to the lack of hydrogen bonding and weak interaction energy between SCN − anions and C 10 mim + cations. In contrast, the trigonal-planar NO 3 − and point-like Cl − anions promoted the formation of well-defined hexagonal mesophases up to 35–45 wt% water. The formation of hydrogen bonding of the two anions with imidazolium ring protons likely enabled the creation of compact ion clusters that effectively exclude water molecules from the immediate vicinity of the IL aggregates. These findings demonstrate that the interaction energy between ion pairs dictate IL-water interactions and therefore control the transition from disordered liquids to ordered mesophases in IL/water mixtures with high IL contents. In conclusion, the combined SAXS/WAXS analysis reveals a correlation between local intermolecular structure and the emergence of mesoscopic order, providing a systematic framework for tailoring mesoscale structures in alkylimidazolium-based IL/water systems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Tunable magneto-optical properties in MoS 2 via defect-induced exciton transitions

The presence of chalcogen vacancies in monolayer transition metal dichalcogenides (TMDs) leads to excitons with mixed localized-delocalized character and to reduced valley selectivity. Recent experimental advances in defect design in TMDs allow for a close examination of such mixed exciton states as a function of their degree of circular polarization under external magnetic fields, revealing strongly varying defect-induced magnetic properties. A theoretical understanding of these observations and their physical origins demands a predictive, structure-sensitive theory. In this work, we study the effect of chalcogen vacancies on the exciton magnetic properties in monolayer MoS 2 . Using many-body perturbation theory, we show how the complex excitonic picture associated with the presence of defects—with reduced valley and spin selectivity due to hybridized electron-hole transitions—leads to a structurally controllable exciton magnetic response. We find a variety of $\textit{g}$-factors with changing magnitudes and sign depending on the exciton energy and character. Further, our findings suggest a pathway to tune the nature of the excitons—and by that their magneto-optical properties—through defect architecture.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Mixing across stable density interfaces in forced stratified turbulence

Understanding how turbulence enhances irreversible scalar mixing in density-stratified fluids is a central problem in geophysical fluid dynamics. While isotropic overturning regions are commonly the focus of mixing analyses, we here investigate whether significant mixing may arise in anisotropic statically stable regions of the flow. Focusing on a single forced direct numerical simulation of stratified turbulence, we analyse spatial correlations between the vertical density gradient $\partial \rho /\partial z$ and the dissipation rates of kinetic energy $\epsilon$ and scalar variance $\chi$ , the latter quantifying scalar mixing. The domain is characterized by relatively well-mixed density layers separated by sharp stable interfaces that are correlated with high vertical shear. While static instability is most prevalent within the mixed layers, much of the scalar mixing is localized to the intervening interfaces, a phenomenon not apparent if considering local static instability or $\epsilon$ alone. While the majority of the domain is characterized by the canonical flux coefficient $\varGamma \equiv \chi /\epsilon =0.2$ , often assumed in ocean mixing parametrizations, extreme values of $\chi$ within the statically stable interfaces, associated with elevated $\varGamma$ , strongly skew the bulk statistics. Our findings suggest that current parametrizations of turbulent mixing may be biased by undersampling, such that the most common, but not necessarily the most significant, mixing events are overweighted. Having focused here on a single simulation of stratified turbulence, it is hoped that our results motivate a broader investigation into the role played by stable density interfaces in mixing, across a wider range of parameters and forcing schemes representative of ocean turbulence.

Couchman, Miles M. P. (ORCID:0000000246676829)↗
DOE OSTI2023

Integrated control of edge localized modes and divertor flux using mixed toroidal harmonic resonant magnetic perturbations in EAST

Mixed harmonic resonant magnetic perturbations (RMPs) for integrated edge localized modes (ELMs) and divertor flux control are demonstrated in EAST target plasmas of low input torque and normalized beta β N ~1.7–1.9, which are close to the equivalent value in ITER high Q operation. The applied RMPs are designed to combine a static harmonic of the toroidal mode number n = 3 with a static or rotating harmonic of n = 2. ELM suppression is achieved without a drop of plasma energy confinement, and tungsten concentration is effectively reduced during the application of RMPs. With mixed harmonics, the toroidal varying steady state heat and particle fluxes on the divertor target can be modified with the rotating n = 2 harmonic, which agrees with the numerical modeling of three-dimensional magnetic topology, with plasma responses being taken into account. ELM suppression correlates with the times of larger n = 3 response with mixed n = 2 and n = 3 RMPs. The mixture of harmonics and the rotating n = 2 harmonic does not require additional coil current because the variation is only in the upper-lower coil current phase space. Furthermore, these results further affirm the effectiveness of integrated ELM and divertor flux control using RMPs with mixed harmonics and improve the understanding of the role of plasma responses in ELM suppression.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Mixing by internal gravity waves in stars: assessing numerical simulations against theory

ABSTRACT Here we present a study of radial chemical mixing in non-rotating massive main-sequence stars driven by internal gravity waves (IGWs), based on multidimensional hydrodynamical simulations with the fully compressible code MUSIC. We examine two proposed mechanisms of material mixing in stars by IGWs that are commonly quoted, relating to thermal diffusion and sub-wavelength shearing. Thermal diffusion provides a non-restorative effect to the waves, leaving material displaced from its previous equilibrium, while shearing arising within the waves drives weak localized flows, mixing the fluid there. Using IGW spectra from the simulations, we evaluate theoretical predictions of mixing rates due to these mechanisms. We show, for $20\, \mathrm{M}_\odot$ main-sequence stars, that neither of these mechanisms are likely to create mixing sufficient to correct inaccuracies in current stellar evolution models. Furthermore, we compare these predictions to results obtained from Lagrangian tracer particles, following a method recently used for global simulations of stellar interiors to measure mixing by IGWs in their radiative zones. We demonstrate that tracer particle methods face significant numerical challenges in measuring the small diffusion coefficients predicted by the aforementioned theories, for which they are prone to yielding artificially enhanced coefficients. Diffusion coefficients based on such methods are currently used with stellar evolution codes for asteroseismic studies, but should be viewed with caution. Finally, in a case where tracer particles do not suffer from numerical artefacts, we suggest that a diffusion model is not suitable for time-scales typically considered by 2D numerical simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

A Deep Learning Modeling Framework to Capture Mixing Patterns in Reactive-Transport Systems

Prediction and control of chemical mixing are vital for many scientific areas such as subsurface reactive transport, climate modeling, combustion, epidemiology, and pharmacology. Due to the complex nature of mixing in heterogeneous and anisotropic media, the mathematical models related to this phenomenon are not analytically tractable. Numerical simulations often provide a viable route to predict chemical mixing accurately. However, contemporary modeling approaches for mixing cannot utilize available spatial-temporal data to improve the accuracy of the future prediction and can be compute-intensive, especially when the spatial domain is large and for long-term temporal predictions. To address this knowledge gap, in this work we will present in this paper a deep learning (DL) modeling framework applied to predict the progress of chemical mixing under fast bimolecular reactions. This framework uses convolutional neural networks (CNN) for capturing spatial patterns and long short-term memory (LSTM) networks for forecasting temporal variations in mixing. By careful design of the framework—placement of non-negative constraint on the weights of the CNN and the selection of activation function, the framework ensures non-negativity of the chemical species at all spatial points and for all times. Our DL-based framework is fast, accurate, and requires minimal data for training. The time needed to obtain a forecast using the model is a fraction (≈ O(-6)) of the time needed to obtain the result using a high-fidelity simulation. To achieve an error of 10% (measured using the infinity norm) for capturing local-scale mixing features such as interfacial mixing, only 24% to 32% of the sequence data for model training is required. To achieve the same level of accuracy for capturing global-scale mixing features, the sequence data required for model training is 64% to 70% of the total spatial-temporal data. Hence, the proposed approach—a fast and accurate way to forecast long-time spatial-temporal mixing patterns in heterogeneous and anisotropic media—will be a valuable tool for modeling reactive-transport in a wide range of applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗