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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Angular Correlation Date Measurements with the GeRMAC system

Advanced modeling and simulation efforts have improved at Idaho National Laboratory in recent years with a solid foundation of experimental results. Current computational methods represent significant modeling capabilities but are limited by the accuracy and availability of nuclear data. The creation of pre- and post-processing software tools to address these limitations is fundamental to the improvement of nuclear science modeling capacities. One aspect of predictive modeling tools deals with gamma-rays emitted from radionuclides, including fissile or fissionable material, fission products, or activation products, produced in reactor experiments or other neutron environments. The resulting radionuclides decay in unique ways, providing complications upon measurement as a result of random and cascade, or true, coincidence summing. These effects are not easily quantified during modeling efforts of gamma-ray source terms., The germanium rotational measurements for angular correlation (GeRMAC) system was built to quantify the relative angles for gamma rays emitted by radionuclides of interest to investigate true coincidence, or cascade, summing as well as the nuclear energy levels of decay schemes of interest. Proof of concept studies utilize a series of laboratory check sources to provide validity, and it will soon be used to perform the same measurements for fission products of interest. The resulting data can be used to implement into a Monte Carlo code, such as Geant4, to provide more precise gamma-ray source terms following irradiations of materials.

73 - NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Operando Investigation of the Molecular Origins of Dipole Switching in P(VDF‐TrFE‐CFE) Terpolymer for Large Adiabatic Temperature Change

Abstract Relaxor ferroelectric polymers exhibiting a giant electrocaloric effect (ECE) can potentially be used to create next‐generation solid‐state coolers. Under an electric field, poly(vinylidene fluoride‐trifluoroethylene‐chlorofluoroethylene) terpolymer goes through a large dipolar entropy change producing a high adiabatic temperature change (Δ T ECE ). This work resolves the molecular origins of the large entropy change behind the electric field‐induced dipole switching. A Fourier transform infrared spectroscopy equipped with a high voltage source is used to operandoly observe the characteristic molecular vibrational modes. A short‐range trans (T) conformation of the CF 2 ‐CH 2 dyads interrupted by a gauche (G) conformation, e.g., TTTG in the terpolymer chain, undergoes a dynamic transformation that leads to a corresponding Δ T ECE whenever an electric field is applied. The molecular dynamics simulation also proves that the energy barrier that the transformation from TTTGs into a long T sequence overcomes is smaller than that for all other conformations. A mixed solvent system is used to obtain T3G‐enriched terpolymer films exhibiting a 4.02 K Δ T ECE at 60 MV m −1 and these films are employed to manufacture a 2‐layer‐cascaded cooling device that achieves a 6.7 K temperature lift, the highest reported value for a 2‐layer cascaded device made of fluoropolymers.

Zhu, Yuan↗
DOE OSTI2023

Jet thermalization in QCD kinetic theory

We perform numerical studies in the framework of QCD kinetic theory to investigate the energy and angular profiles of a high energy parton — as a proxy for a jet produced in heavy ion collisions — passing through a Quark-Gluon Plasma (QGP). We find that the fast parton loses energy to the plasma mainly via a radiative turbulent quark and gluon cascade that transports energy locally from the jet down to the temperature scale where dissipation takes place. In this first stage of the system time evolution, the angular structure of the turbulent cascade is found to be relatively collimated. However, when the lost energy reaches the plasma temperature it is rapidly transported to large angles w.r.t. the jet axis and thermalizes. We investigate the contribution of the soft jet constituents to the total jet energy. We show that for jet opening angles of about 0.3 rad or smaller, the effect is negligible. Conversely, larger opening angles become more and more sensitive to the thermal component of the jet and thus to medium response. Our result showcases the importance of the jet cone size in mitigating or enhancing the details of dissipation in jet quenching observables.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Gaussian process hydrodynamics

Abstract We present a Gaussian process (GP) approach, called Gaussian process hydrodynamics (GPH) for approximating the solution to the Euler and Navier-Stokes (NS) equations. Similar to smoothed particle hydrodynamics (SPH), GPH is a Lagrangian particle-based approach that involves the tracking of a finite number of particles transported by a flow. However, these particles do not represent mollified particles of matter but carry discrete/partial information about the continuous flow. Closure is achieved by placing a divergence-free GP prior ξ on the velocity field and conditioning it on the vorticity at the particle locations. Known physics (e.g., the Richardson cascade and velocity increment power laws) is incorporated into the GP prior by using physics-informed additive kernels. This is equivalent to expressing ξ as a sum of independent GPs ξ l , which we call modes, acting at different scales (each mode ξ l self-activates to represent the formation of eddies at the corresponding scales). This approach enables a quantitative analysis of the Richardson cascade through the analysis of the activation of these modes, and enables us to analyze coarse-grain turbulence statistically rather than deterministically. Because GPH is formulated by using the vorticity equations, it does not require solving a pressure equation. By enforcing incompressibility and fluid-structure boundary conditions through the selection of a kernel, GPH requires significantly fewer particles than SPH. Because GPH has a natural probabilistic interpretation, the numerical results come with uncertainty estimates, enabling their incorporation into an uncertainty quantification (UQ) pipeline and adding/removing particles (quanta of information) in an adapted manner. The proposed approach is suitable for analysis because it inherits the complexity of state-of-the-art solvers for dense kernel matrices and results in a natural definition of turbulence as information loss. Numerical experiments support the importance of selecting physics-informed kernels and illustrate the major impact of such kernels on the accuracy and stability. Because the proposed approach uses a Bayesian interpretation, it naturally enables data assimilation and predictions and estimations by mixing simulation data and experimental data.

Mathematics↗
DOE OSTI2024

Pathway to Decarbonization Through Industrial Energy Efficiency: Micro and Macro Perspectives from Compressed Air Usage

Abstract Energy audits directly provided the industrial sector with reduced energy costs and avoided emissions. Still, they also lead to far-reaching indirect and induced local, regional, and national benefits. This paper aims to present the techno-economic-environmental analysis to achieve decarbonization through implementing industrial energy efficiency at micro and macro levels. An integrated techno-economic-environmental methodology is developed. Case studies of micro-level carbon reduction efforts through industrial energy efficiency technologies are presented. The broader macroeconomic and environmental effects of technology on society are analyzed using data from 206 energy audits of industrial compressed air systems conducted over 13 years. The impacts show that energy-efficient improvements lead to direct cost savings for manufacturers, boost economic activity across sectors, and affect carbon dioxide emissions both short-term and long-term in the region. Given their extensive benefits, energy audits significantly influence policymaking. We devised a methodology to link micro-level energy audit data with macroeconomic and environmental analyses to quantify these cascading benefits. The economic scenario analysis shows that $228 M has been saved from direct industrial energy savings from implementing all compressed air recommendations in the studied periods and the region. In addition, the investment made through manufacturers would create 2,025 jobs and $383 M annually, cascading regional economic impacts. The environmental analysis shows that the regional manufacturers have directly avoided about 2.8 M metric tons of carbon dioxide emissions.

Engineering↗
DOE OSTI2022

A general strategy and a consolidated mechanism for low-methane hydrogenolysis of polyethylene over ruthenium

Polyethylene (PE) is one of the most environment-threatening plastic waste. Its Ru-catalyzed hydrogenolysis is rapid but produces too much methane. Here, in this study, low-density PE hydrogenolysis is performed at mild conditions and short times over Ru-doped zirconia catalysts (Ru-XZr, X = Ti, Nb, Ce, W, V, Mo, Fe) to determine low-methane catalysts. Methane is produced via direct terminal C-C scission and surface cascade of consecutive C-C scissions, with the latter sensitive to hydrogen availability and dominant in hydrogen-lean conditions. Reactivity studies, characterization and theory reveal that the most effective dopant oxides (W, V, and Mo) are intermediately reducible, as they store and supply extra hydrogen to Ru via reverse hydrogen spillover. This hydrogen readily hydrogenates and desorbs long alkyl surface intermediates that would otherwise produce cascade methane. Our proposed mechanism reconciles the low methane production achieved by increasing the hydrogen pressure or reducing the particle size and exposes the key selectivity descriptors.

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

Role of electronic energy loss on defect production and interface stability: Comparison between ceramic materials and high-entropy alloys

High-entropy alloys (HEAs) and some complex alloys exhibit desirable properties and significant structural stability in harsh environments, including possible applications in advanced reactors. Energetic ion irradiation is often used as a surrogate for neutron irradiation; however, the impact of ion electronic energy deposition and dissipation is often neglected. Moreover, differences in recoil energy spectrum and density of cascade events on damage evolution must also be considered. In many chemically complex alloys, the mean free path of electrons is reduced significantly, thus their decreased thermal conductivity and slow dissipation of localized radiation energy can have noticeable effects on displacement cascade evolution that is greatly different from metals with high thermal conductivity. In this work, nanocrystalline HEAs of Ni 20 Fe 20 Co 20 Cr 20 Cu 20 and nonequiatomic (NiFeCoCr) 97 Cu 3 , both having much lower room-temperature thermal conductivity than pure Ni or Fe, are chosen as model HEAs to reveal the role that electronic energy loss during ion irradiation has in complex alloys. The response of nanocrystalline HEAs is investigated under irradiation at room temperature using MeV Ni and Au ions that have different ratios of electronic energy to damage energy, which is the energy dissipated in displacing atoms. Different from previously reported amorphization of nanocrystalline SiC, experimental results on these HEAs show that, similar to the process in nanocrystalline oxide materials, both inelastic thermal spikes via electron–phonon coupling and elastic thermal spikes via collisions among atomic nuclei contribute to the overall grain growth. The growth follows a power law dependence with the total deposited ion energy, and the derived value of the power-exponent suggests that the irradiation-induced instability at and near grain boundaries leads to local rapid atomic rearrangements and consequently grain growth. The high power-exponent value can be attributed to the sluggish diffusion and delayed defect evolution arising from the chemical complexity intrinsic to HEAs. Here, this work calls attention to quantified fundamental understanding of radiation damage processes beyond that of simplified displacement events, especially in simulating neutron environments.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Cooperative Brønsted-Lewis acid sites created by phosphotungstic acid encapsulated metal–organic frameworks for selective glucose conversion to 5-hydroxymethylfurfural

Production of 5-hydroxymethylfurfural (HMF) from biomass-derived glucose has great potential for synthesis of renewable fuels and chemicals. Selective glucose conversion to 5-hydroxymethylfurfural requires a balance between Lewis and Brønsted acids for the cascade of glucose isomerization followed by fructose dehydration. A dual Brønsted-Lewis acid, phosphotungstic acid encapsulated MIL-101(Al)–NH 2 metal–organic frameworks (MOFs) was developed to catalyze the glucose dehydration reaction. The encapsulated catalysts had a high HMF selectivity of 58% at 44% glucose conversion at 120°C in [C 4 C 1 im]Cl. Phosphotungstic acid was uniformly dispersed in the MOF pores, which provided both Brønsted and Lewis acid sites for this cascade reaction. The Brønsted acidic phosphotungstic acid-encapsulated MOF catalyst was stable and recyclable at least four times. Here, these findings explain the effect of phosphotungstic acid location for maximizing the HMF selectivity and suggest a new approach for the design of bifunctional solid acid catalysts for selective HMF production from glucose. Moreover, the tunability of the acid properties of the encapsulated MOF catalysts provides opportunities for other biomass transformations.

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

The cold high-pressure approach to hydrogen delivery

In view of the very expensive and wasteful nature of today's approaches to H 2 delivery, in this work we explore the possibility of transporting cold (200 K) high pressure (875 bar) H 2 in thermally insulated trailers and dispensing H 2 directly from the trailer, with the potential to eliminate station compressor, cascade, and refrigerator, leading to major reductions in station complexity, maintenance, electricity consumption, and cost, while improving functionality by enabling essentially unlimited back to back refuels, and improving safety due to reduced H 2 expansion energy at low temperature. Detailed techno-economic analysis shows promise for substantial delivery cost reductions through cold high pressure H 2 dispensed directly from the trailer. Results indicate that: (1) Terminal operations for cold high pressure H 2 delivery are $\$$0.32/kg H 2 more expensive than for 350 bar compressed gas delivery (today's lowest cost H 2 delivery technology) due to higher level of pressurization (to 1000 bar) and chilling needs (to 165 K). (2) Trailer cost drops slightly ($\$$0.73 vs. $\$$0.81/kg H 2 for a 350 bar trailer) due to increased capacity (1035 kg H 2 delivered vs. 700 kg) compensating for increased capital cost ($\$$906,900 for cold high pressure H 2 vs. $\$$634,000 for 350 bar trailer). (3) Cold hydrogen delivery presents major advantages in fueling station cost, reduced from $\$$1.27 to $\$$0.46/kg H 2 due to elimination of major system components: compressor, cascade, and chiller. (4) Total compression cost (terminal + station) drops from $\$$0.92/kg H 2 ($\$$0.32 terminal and $\$$0.60 station) for 350 bar trailers to $\$$0.55/kg H 2 (all at the terminal) for cold high pressure H 2 . (5) Elimination of small-scale station compressors is the main contributor to reduced delivery cost due to their inefficiency, capital expense, and maintenance needs. In summary, total delivery cost reduction vs. 350 bar trailer equals $\$$0.58/kg H 2 (from $\$$2.96 to 2.38/kg H 2 ), equivalent to 24% of the total delivery cost. This large cost advantage will improve the economics of H 2 vehicles facilitating the transition to a future of zero emission transportation.

08 HYDROGEN↗
DOE OSTI2026

Cross-sectoral impact of emerging technologies on U.S. manufacturing resilience and competitiveness

Introducing new technologies in one energy-intensive industry can affect how other industries operate and stay resilient, yet these cross-sector interactions are often underappreciated in conventional technology roadmaps. In practice, industrial systems do not evolve in isolation. They are linked through shared upstream and downstream dependencies, such as electricity and fuel supply, critical materials, transportation networks, and enabling infrastructure. As a result, large-scale technology deployment in one sector can reshape resource availability, infrastructure demand, and operational risk in others. These interdependencies mean that technology deployment decisions in one sector can create unintended bottlenecks or cascading benefits in others. Here, this article argues that a cross-sector, system-of-systems perspective is essential for evaluating and scaling emerging technologies in energy-intensive industries. By framing industrial transformation as an interconnected systems challenge rather than a set of isolated sectoral decisions, the study highlights how interdependence shapes technology feasibility, adoption pathways, and resilience outcomes. The article illustrates how cross-sector linkages can amplify both risks and benefits, and it emphasizes the importance of integrated planning approaches that account for shared dependencies, cascading impacts, and co-optimization opportunities. Adopting this broader perspective can support more robust technology roadmaps, improve strategic coordination across industries, and strengthen the long-term resilience of the industrial sector as a whole.

Nain, Preeti [Oak Ridge National Laboratory (ORNL)↗
DOE OSTI2024

Hydrologic connectivity and dynamics of solute transport in a mountain stream: Insights from a long-term tracer test and multiscale transport modeling informed by machine learning

The movement of solutes in a watershed is a complex process with multiple interactions and feedbacks across spatial and temporal scales. Modeling the dynamics of solute transport along diverse hydrologic pathways within watersheds – from hillslopes to stream channels and in and out of the hyporheic zones – is challenging but critically important, as these processes integrate and contribute to the biogeochemical functioning of the river corridor up to the river network scale. Here we use results from a long-term network-scale tracer test at the H.J. Andrews experimental forest in western Cascade Mountains, Oregon, USA to inform a multiscale framework for transport in stream corridors. The framework uses a Lagrangian-based subgrid model to represent the effects of hyporheic exchange flow and advective transport at stream network scales. The spatially and temporally resolved stream discharge needed for the transport model is imputed across the river system by an entity-aware long short-term memory network. Modeled concentrations show good agreements with the observations and exhibit power scaling laws indicative of a very wide range of timescales over which hyporheic exchange flow occurs. Our results demonstrate a data-informed modeling framework that links dynamical processes occurring at small scales to a network context to help understand how changes at reach scale cascade into network-scale effects, providing a useful tool for sustainable river basin management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Identifying the nature of the QCD transition in heavy-ion collisions with deep learning

In this proceeding, we review our recent work using deep convolutional neural network (CNN) to identify the nature of the QCD transition in a hybrid modeling of heavy-ion collisions. Within this hybrid model, a viscous hydrodynamic model is coupled with a hadronic cascade “after-burner”. As a binary classification setup, we employ two different types of equations of state (EoS) of the hot medium in the hydrodynamic evolution. The resulting final-state pion spectra in the transverse momentum and azimuthal angle plane are fed to the neural network as the input data in order to distinguish different EoS. To probe the effects of the fluctuations in the event-by-event spectra, we explore different scenarios for the input data and make a comparison in a systematic way. We observe a clear hierarchy in the predictive power when the network is fed with the event-by-event, cascade-coarse-grained and event-fine-averaged spectra. The carefully-trained neural network can extract high-level features from pion spectra to identify the nature of the QCD transition in a realistic simulation scenario.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Turbulence theories and statistical closure approaches

When discussing research in physics and in science more generally, it is common to ascribe equal importance to the three components of the scientific trinity: theoretical, experimental, and computational studies. This review will explore the future of modern turbulence theory by tracing its history, which began in earnest with Kolmogorov’s 1941 analysis of turbulence cascade and inertial range [A.N. Kolmogorov, Dokl. Akad. Nauk SSSR, 30, 299, (1941); 32, 19, (1941)]. The 80th Anniversary of Kolmogorov’s landmark study is a welcome opportunity to survey the achievements and evaluate the future of the theoretical approach of turbulence research. Over the years, turbulence theories have been critically important in laying the foundation of our understanding of the nature of turbulent flows. In particular, the Direct Interaction Approximation (DIA) [R.H. Kraichnan, J. Fluid Mech., 5, 497 (1959)] and its subsequent development, known as the statistical closure approach, can be identified as perhaps the most profound single advancement. The remarkable success of the statistical closure has furnished a platform to study such essential concepts as the energy transfer process and interacting scales, and the roles of the straining and sweeping motions. More recently, the quasi-Lagrangian formulation of V. L’vov & I. Procaccia and Kraichnan’s solvable passive scalar model provided powerful ways to explore another fundamental aspect of turbulent flows, the phenomena of intermittency, and the associated anomalous scaling exponents. In the meantime, the theory of fluid equilibria has been developed to describe the large-scale structures that can emerge from turbulent cascades of two-dimensional and geophysical flows at a later time. And yet, despite all these successes, analytical treatments suffer from mathematical complexities. As a result, the utility of theoretical approaches has been limited to relatively idealized flows. On the other hand, in recent decades, computational abilities and experimental facilities have reached an unprecedented scale. Looking beyond the horizon, the imminent deployment of exascale supercomputers will generate complete datasets of the entire flow field of key benchmark flows, allowing researchers to extract additional measurements concerning fully developed, complex turbulent flow fields far beyond those available from the statistical closure theories. Some other developments that could potentially influence the future course of turbulence theories include the advancement of machine learning, artificial intelligence, and data science; likely disruptions arising from the advent of quantum computation; and the increasingly prominent role of turbulence research in providing more accurate climate scientific data. Finally, turbulence theorists can leverage these developments by asking the right questions and developing advanced, sophisticated frameworks that will be able to predict and correlate vast amounts of data from the other two components of the trinity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Detection of the keto-enol tautomerization in acetaldehyde, acetone, cyclohexanone, and methyl vinyl ketone with a novel VUV light source

The discovery of enols in combustion environments and our atmosphere has garnered increasing attention to the many unanswered questions surrounding enol chemistry. The scarcity of experimental data concerning these enols renders combustion and atmospheric models with a lack of constraining parameters, leading to varying computational predictions. Experimental detection is difficult because mass spectrometry, a powerful tool for probing a wide variety of species, cannot distinguish between enols and their thermodynamically favorable ketone isomers. A solution to this ambiguity is to use tunable vacuum ultraviolet (VUV) light from a synchrotron to identify the presence of the enol by its lower ionization energy compared to the isomer. We present a tabletop-scale VUV light source that implements highly cascaded harmonic generation, a new regime of cascaded nonlinear optics, to provide a set of spectral lines spaced by 1.2 eV. We demonstrate that the variety of photon energies available allows us to detect the keto-enol tautomerization of four aldehydes and ketones. By combining this novel VUV light source with an established microreactor, we first revisit the formation of vinyl alcohol from acetaldehyde and confirm that the observed isomerization is indeed unimolecular. Secondly, we observe the thermal tautomerization of acetone to propen-2-ol for the first time. Finally, we observe the thermal tautomerization of cyclohexanone to 1-cyclohexenol and methyl vinyl ketone to 2-hydroxybutadiene, where the results are in good agreement with those reported at a synchrotron. Furthermore, our measurements can be used to constrain models, inform future experimental studies of enol reactivity, and potentially enhance current understanding of combustion and environmental chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Wildfire-Power Grid Interactions: Feedback, Impacts, Monitoring, Modeling, and Mitigation Strategies

Wildfires are increasingly interacting with electric power systems through a two-way hazard chain: fires damage grid assets and trigger cascading outages, while grid faults can ignite new fires under hot, dry, and windy conditions. This review synthesizes the state of knowledge across five domains: (i) physical impacts of flames, heat, and smoke on lines, towers, insulators, and substations; (ii) power-infrastructure-initiated ignitions via conductor clash, high-impedance faults, and corona discharge; (iii) widespread blackouts and disproportionate societal impacts; (iv) multi-scale monitoring spanning laboratory tests, in-situ and grid-integrated sensors, and Earth observation; (v) coupled modeling that links fire behavior with grid operations; and (vi) technological and strategic mitigation pathways spanning prevention, response, and recovery. We integrate these domains into a novel 'feedback-aware' socio-technical framework. Through a longitudinal analysis (2005-2025) of global incidents, we identify that while vegetation contact remains the most frequent ignition source, aging infrastructure failure has emerged as a critical driver of catastrophic 'mega-fires'. We further identify persistent gaps, including limited interoperability of high-frequency grid and environmental data, scarce real-time data assimilation, and under-developed equity metrics for outage management. We conclude by outlining a research agenda to (1) deploy interoperable sensing architectures, (2) advance feedback-coupled fire-grid simulations, and (3) evaluate mitigation portfolios through techno-economic and fairness lenses. Recognizing wildfire-grid interactions as coupled socio-technical systems is essential for protecting infrastructure and communities and for ensuring reliable, sustainable electricity in a changing world.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Towards critical and supercritical electromagnetic fields

Abstract The availability of ever stronger, laser-generated electromagnetic fields underpins continuing progress in the study and application of nonlinear phenomena in basic physical systems, ranging from molecules and atoms to relativistic plasmas and quantum electrodynamics. This raises the question: how far will we be able to go with future lasers? One exciting prospect is the attainment of field strengths approaching the Schwinger critical field ${E}_{\mathrm{cr}}$ in the laboratory frame, such that the field invariant ${E}^2-{c}^2{B}^2>{E}_{\mathrm{cr}}^2$ is reached. The feasibility of doing so has been questioned, on the basis that cascade generation of dense electron–positron plasma would inevitably lead to absorption or screening of the incident light. Here we discuss the potential for future lasers to overcome such obstacles, by combining the concept of multiple colliding laser pulses with that of frequency upshifting via a tailored laser–plasma interaction. This compresses the electromagnetic field energy into a region of nanometre size and attosecond duration, which increases the field magnitude at fixed power but also suppresses pair cascades. Our results indicate that laser facilities with peak power of tens of PW could be capable of reaching ${E}_{\mathrm{cr}}$ . Such a scenario opens up prospects for the experimental investigation of phenomena previously considered to occur only in the most extreme environments in the universe.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Scale interactions and anisotropy in Rayleigh–Taylor turbulence

We study energy scale transfer in Rayleigh–Taylor (RT) flows by coarse graining in physical space without Fourier transforms, allowing scale analysis along the vertical direction. Two processes are responsible for kinetic energy flux across scales: baropycnal work Λ, due to large-scale pressure gradients acting on small scales of density and velocity; and deformation work Π, due to multiscale velocity. Our coarse-graining analysis shows how these fluxes exhibit self-similar evolution that is quadratic-in-time, similar to the RT mixing layer. We find that Λ is a conduit for potential energy, transferring energy non-locally from the largest scales to smaller scales in the inertial range where Π takes over. In three dimensions, Π continues a persistent cascade to smaller scales, whereas in two dimensions Π rechannels the energy back to larger scales despite the lack of vorticity conservation in two-dimensional (2-D) variable density flows. This gives rise to a positive feedback loop in 2-D RT (absent in three dimensions) in which mixing layer growth and the associated potential energy release are enhanced relative to 3-D RT, explaining the oft-observed larger α values in 2-D simulations. Despite higher bulk kinetic energy levels in two dimensions, small inertial scales are weaker than in three dimensions. Moreover, the net upscale cascade in two dimensions tends to isotropize the large-scale flow, in stark contrast to three dimensions. Furthermore, our findings indicate the absence of net upscale energy transfer in three-dimensional RT as is often claimed; growth of large-scale bubbles and spikes is not due to ‘mergers’ but solely due to baropycnal work Λ.

42 ENGINEERING↗
DOE OSTI2025

Molecular fluctuations inhibit intermittency in compressible turbulence

In the standard picture of fully developed turbulence, highly intermittent hydrodynamic fields are nonlinearly coupled across scales, where local energy cascades from large scales into dissipative vortices and large density gradients. Microscopically, however, constituent fluid molecules are in constant thermal (Brownian) motion, but the role of molecular fluctuations in large-scale turbulence is largely unknown, and with rare exceptions, it has historically been considered irrelevant at scales larger than the molecular mean free path. Recent theoretical and computational investigations have shown that molecular fluctuations can impact energy cascade at Kolmogorov length scales. Here, we show that molecular fluctuations not only modify energy spectrum at wavelengths larger than the Kolmogorov length in compressible turbulence, but also significantly inhibit spatio-temporal intermittency across the entire dissipation range. Using large-scale direct numerical simulations of computational fluctuating hydrodynamics, we demonstrate that the extreme intermittency characteristic of turbulence models is replaced by nearly Gaussian statistics in the dissipation range. These results demonstrate that the compressible Navier–Stokes equations should be augmented with molecular fluctuations to accurately predict turbulence statistics across the dissipation range. Our findings have significant consequences for turbulence modelling in applications such as astrophysics, reactive flows and hypersonic aerodynamics, where dissipation-range turbulence is approximated by closure models.

compressible turbulence↗