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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Spectral treatment of gyrokinetic profile curvature

Using a novel wavenumber-advection algorithm, we show that profile curvature (shear in the profile gradient) can be implemented with spectral accuracy in gyrokinetic turbulence simulations. Here, this approach enables a global simulation capability with the relatively low cost and high accuracy of local simulations. Using this new algorithm, we show that for a well-studied tokamak core test case, the effect of temperature-gradient curvature is below the threshold of detectability for experimentally-relevant values of curvature.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Spatiotemporal predictions of toxic urban plumes using deep learning

Industrial accidents, chemical spills, and structural fires can release large amounts of harmful materials that disperse into urban atmospheres and impact populated areas. Computer models are typically used to predict the transport of toxic plumes by solving fluid dynamical equations. However, these models can be computationally expensive due to the need for many grid cells to simulate turbulent flow and resolve individual buildings and streets. In emergency response situations, alternative methods are needed that can run quickly and adequately capture important spatiotemporal features. Here, we present a novel deep learning model called ST-GasNet inspired by the mathematical equations that govern the behavior of plumes as they disperse through the atmosphere. ST-GasNet learns the spatiotemporal dependencies from a limited set of temporal sequences of ground-level toxic urban plumes generated by a high-resolution large eddy simulation model. On independent sequences, ST-GasNet accurately predicts the late-time spatiotemporal evolution, given the early-time behavior as an input, even when a building splits a large plume into smaller plumes. By incorporating large-scale wind boundary condition information, ST-GasNet achieves a prediction accuracy of at least 90% on test data for the entire prediction period.

Civil and Environmental Engineering↗
DOE OSTI2020

Geometry dependence of the fluctuation intensity in gyrokinetic turbulence

The findings of an investigation into the properties of the three dimensional (3D) saturated fluctuation intensity of the electric potential in gyrokinetic turbulence simulations is presented. Scans in flux surface elongation and Shafranov shift are used to isolate the tokamak geometric dependencies. The potential intensity required in order to compute exact fluxes by a quasilinear method is determined using linear eigenmodes computed with the gyrokinetic code. A model of this non-linear intensity is constructed using the linear eigenmode properties and the geometry shape functions obtained from the 3D intensity spectrum. The model computes the poloidal wavenumber spectrum of the electron and ion energy fluxes with unprecedented accuracy. In conclusion, new insights are gained into the way zonal flow mixing saturates ion-scale turbulence by controlling the radial wavenumber width of the turbulence spectrum.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Electric field and turbulence in global Braginskii simulations across the ASDEX Upgrade edge and scrape-off layer

Turbulence simulations in diverted geometry across the edge and scrape-off layer (SOL) of ASDEX Upgrade are performed with the GRILLIX code (Stegmeir et al 2019 Phys. Plasmas 26 052517). The underlying global (full-f) drift-reduced Braginskii model allows to concurrently study the self-consistent dynamics of the turbulence and the background as well as the evolution of toroidal and zonal flows. Different contributions to the radial electric field are identified. The dominant contribution on closed flux surfaces comes from the ion pressure gradient, due to the diamagnetic drift in the curved magnetic field. Large deviations can be induced, in particular, by the polarization particle flux, leading to zonal flows. The latter are driven by small-scale eddies, but do not exhibit much impact on the overall transport which is driven by ballooning modes at larger scales. Ion viscosity is found to be important in damping poloidal rotation through adjusting of the parallel velocity profile, but not via direct vorticity damping. The zonal flow drive peaks at the separatrix, where a strong shear layer forms due to the sheath-induced counter-propagating SOL flow, allowing for the formation of a transport barrier. The temperature profile across the separatrix is determined by the competition between cross-field transport and outflow in the SOL, the latter being largely controlled by the parallel heat conductivity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Verification of a quasi-linear model for gyrokinetic turbulent transport

The verification and calibration of a new quasi-linear transport model with a large database of gyrokinetic turbulence simulations is presented in this paper. In a previous paper (Staebler et al 2020 Plasma Phys. Control. Fusion 63 015013), a model for the saturated spectrum of electric potential fluctuations was developed based on the properties of the non-linear 3D spectrum. In this paper, a modification to the overall multiplicative factor in this model is found to be necessary to improve the fit to scans of the temperature and density gradients. The error in the fit of the quasi-linear fluxes of electron and ion energy fluxes is significantly better than for previous saturation models. The spectral shift model for the impact of equilibrium E × B velocity shear (Staebler et al 2013 Phys. Rev. Lett. 110 055003) and the zonal flow mixing model for electron-scale turbulence (Staebler et al 2016 Phys. Plasmas 23 062518) are both revised to be compatible with this new model. Furthermore, the models for the loss of bounce averaging and electron collisions in the TGLF reduced linear equations (Staebler et al 2005 Phys. Plasmas 12 102508) are also changed to improve the linear eigenmodes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Anisotropic Energy Transfer and Conversion in Magnetized Compressible Turbulence

We present a spatial filtering (or coarse-graining) analysis on 3D magnetized magnetohydrodynamic (MHD) turbulence simulations. The filtered compressible MHD formulae show transfer of kinetic and magnetic energies from large to small scales, as well as energy conversion between kinetic, magnetic, and thermal energies. The anisotropic filtering enables separate analyses of the energy flows perpendicular and parallel to the global mean magnetic field. Anisotropy in energy cascade is demonstrated by the larger perpendicular energy cascade rate and also the larger perpendicular wavenumbers associated with the peak energy transfer rate. We also find that the “inertial range” along the parallel (perpendicular) direction in the anisotropic energy cascade formulation is no longer strictly dissipation-free, because it includes the dissipation in the perpendicular (parallel) direction. A change in the driving force (kinetic only versus kinetic and magnetic) affects the energy conversion between kinetic and magnetic energies. While the compressibility of the driving force changes the partition of different channels of energy transfer and conversion, and also increases the total energy transfer rate, the global energy flow remains unaffected by compressibility qualitatively. Our analysis can be applied to multispacecraft observations of turbulence in the solar wind or a planetary magnetosphere.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

An uncertainty visualization framework for large-scale cardiovascular flow simulations: A case study on aortic stenosis

We present a generalizable uncertainty quantification (UQ) and visualization framework for lattice Boltzmann method simulations of high Reynolds number vascular flows, demonstrated on a patient-specific stenosed aorta. The framework combines EasyVVUQ for parameter sampling with large-eddy simulation turbulence modeling in HemeLB, and executes ensembles on the Frontier exascale supercomputer. Spatially resolved metrics, including entropy and isosurface-crossing probability, are used to map uncertainty in pressure and wall shear stress fields directly onto vascular geometries. Two sources of model variability are examined: inlet peak velocity and the Smagorinsky constant. Inlet velocity variation produces high uncertainty downstream of the stenosis where turbulence develops, while upstream regions remain stable. Smagorinsky constant variation has little effect on the large-scale pressure field but increases WSS uncertainty in localized high-shear regions. In both cases, the stenotic throat manifests low entropy, indicative of robust identification of elevated WSS. By linking quantitative UQ measures to three-dimensional anatomy, the framework improves interpretability over conventional 1D UQ plots and supports clinically relevant decision-making, with broad applicability to vascular flow problems requiring both accuracy and spatial insight.

Hemodynamics↗
DOE OSTI2024

Application of passive vortex generators to enhance vertical mixing in an open raceway pond

A novel use of vortex generators in a raceway pond is described here, with the flow field quantitatively simulated using computational fluid dynamics using the large eddy simulation turbulence model. Persistence lengths of the swirling motion generated by the vortex generators indicate that significant vertical mixing can be achieved by placing vortex generators in the straight section opposite the paddle wheel, downstream of the first hairpin bend. Relatively simple vortex generators are capable of creating stronger swirling motions that persist for a longer distance than those created by the paddle wheel. For optimal performance, vortex generators are positioned side by side but in opposite directions, and their diameters should be equal to or slightly less than the desired liquid depth. The optimal length of a 0.18 m diameter vortex generator in a 0.2 m deep pond was determined to be 0.3 m. As a result, it has been demonstrated that a longer persistence length is achieved by inducing a swirling motion with its rotational axis parallel to the primary flow direction.

09 BIOMASS FUELS↗
DOE OSTI2022

Thermal fluctuations in the dissipation range of homogeneous isotropic turbulence

In this work, using fluctuating hydrodynamics we investigate the effect of thermal fluctuations in the dissipation range of homogeneous isotropic turbulence. Simulations confirm theoretical predictions that the energy spectrum is dominated by these fluctuations at length scales comparable to the Kolmogorov length. We also find that the extreme intermittency in the far-dissipation range predicted by Kraichnan is replaced by Gaussian thermal equipartition.

42 ENGINEERING↗
DOE OSTI2023

On the evolution of scalar iso-surface area density in a turbulent mixing layer

In this paper, the transport equation for scalar iso-surface area density (Σ) in a turbulent, temporally developing mixing layer is examined. Exploring the spatial and temporal evolution of the terms in the Σ transport equation is vital to improving our understanding of turbulent flows characterized by distinct interfaces, e.g. the flame surface or the turbulent/non-turbulent interface. Previous work reported by the authors identified that Σ exhibits self-similar behaviour consistent with the development of the temporal mixing layer. Accordingly, each of the terms in the Σ transport equation is found to behave in a self-similar manner, though there are notable differences in the self-similar behaviours for each term. Based on the results presented herein, it is suggested that the rate of change of Σ (∂Σ/∂t) and the advection term scale with hλ Φ /ΔU, where h is the width of the mixing layer, λ Φ is the scalar Taylor length scale and ΔU is the velocity difference. The production and destruction terms are found to scale with an additional factor (ReSc) 1/2 . In contrast, the molecular diffusion term is found to scale with a factor (ReSc) –1/2 compared to ∂Σ/∂t. Importantly, it is found that the difference between the production and destruction terms, or net surface ‘stretch’, scales with the same factor as ∂Σ/∂t and the advection term, which may have a significant impact on how the evolution of Σ is understood and modelled in turbulent flows.

42 ENGINEERING↗
DOE OSTI2022

Impact of the electron density and temperature gradient on drift-wave turbulence in the Large Plasma Device

In this paper we present an experimental study of edge turbulence in the Large Plasma Device at UCLA. We utilize a scan of discharge power and prefill pressure (neutral density) to show experimentally that turbulent density fluctuations decrease with decreasing density gradient, as predicted for resistive drift-wave turbulence (RDWT). As expected for RDWT, we observe that the cross-phase between the density and potential fluctuations is close to 0. Moreover, the addition of an electron temperature gradient leads to a reduction in the amplitude of the density fluctuations, as expected for RDWT. However, counter to theoretical expectations, we find that the potential fluctuations do not follow the same trends as the density fluctuations for changes either in density gradients or the addition of a temperature gradient. The disconnect between the density and potential fluctuations is connected to changes in the parallel flows as a result of differences in the prefill pressure, i.e. neutral density. Further analysis of the density and potential fluctuation spectra show that the electron temperature gradient reduces the low frequency fluctuations up to $10 \,{\rm kHz}$ and the introduction of a temperature gradient leads to an unexpected ${\sim }{\rm \pi}$ shift of the density–potential cross-phase at ${\sim }10\,{\rm kHz}$ , while maintaining the typical resistive drift-wave cross-phase at lower frequencies. These experiments partly confirm existing knowledge on resistive drift-wave turbulence, but also introduce new observations that indicate a need for dedicated nonlinear three-dimensional turbulence simulations that include neutrals.

Physics↗
DOE OSTI2026

From Weibel seeds to dynamo beyond pair-plasmas

Bridging the spatiotemporal scales of magnetic seed field generation and subsequent dynamo amplification in the weakly collisional intracluster medium presents an extreme numerical challenge. We perform collisionless turbulence simulations with initially unmagnetised electrons that capture both magnetic seed generation via the electron Weibel instability and the ensuing dynamo amplification. Going beyond existing pair-plasma studies, we use an ion-to-electron mass ratio of 100 for which we find electron and ion dynamics are sufficiently decoupled. These simulations are enabled by the 10-moment collisionless fluid solver of Gkeyll, which evolves the full pressure tensor for all species. The electron heat-flux closure regulates pressure isotropisation and effectively sets the magnetic Reynolds number. We investigate how the strength of the closure influences the transition between a regime reminiscent of previous kinetic pair-plasma simulations and a regime exhibiting dynamo behaviour qualitatively similar to magnetohydrodynamics.

astrophysical plasmas↗
DOE OSTI2021

Potential vorticity transport in weakly and strongly magnetized plasmas

Tangled magnetic fields, often coexisting with an ordered mean field, have a major impact on turbulence and momentum transport in many plasmas, including those found in the solar tachocline and magnetic confinement devices. We present a novel mean field theory of potential vorticity mixing in β-plane magnetohydrodynamic (MHD) and drift wave turbulence. Our results show that mean square stochastic fields strongly reduce Reynolds stress coherence. This decoherence of potential vorticity flux due to stochastic field scattering leads to suppression of momentum transport and zonal flow formation. A simple calculation suggests that the breaking of the shear-eddy tilting feedback loop by stochastic fields is the key underlying physics mechanism. Furthermore, a dimensionless parameter that quantifies the increment in power threshold is identified and used to assess the impact of stochastic field on the L-H transition. We discuss a model of stochastic fields as a resisto-elastic network.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Learning the structure of wind: A data-driven nonlocal turbulence model for the atmospheric boundary layer

In this work, we develop a novel data-driven approach to modeling the atmospheric boundary layer. This approach leads to a nonlocal, anisotropic synthetic turbulence model which we refer to as the deep rapid distortion (DRD) model. Our approach relies on an operator regression problem that characterizes the best fitting candidate in a general family of nonlocal covariance kernels parameterized in part by a neural network. This family of covariance kernels is expressed in Fourier space and is obtained from approximate solutions to the Navier–Stokes equations at very high Reynolds numbers. Each member of the family incorporates important physical properties such as mass conservation and a realistic energy cascade. The DRD model can be calibrated with noisy data from field experiments. After calibration, the model can be used to generate synthetic turbulent velocity fields. To this end, we provide a new numerical method based on domain decomposition which delivers scalable, memory-efficient turbulence generation with the DRD model as well as others. We demonstrate the robustness of our approach with both filtered and noisy data coming from the 1968 Air Force Cambridge Research Laboratory Kansas experiments. Using these data, we witness exceptional accuracy with the DRD model, especially when compared to the International Electrotechnical Commission standard.

17 WIND ENERGY↗
DOE OSTI2021

Data-driven learning of Mori–Zwanzig operators for isotropic turbulence

Developing reduced-order models for turbulent flows, which contain dynamics over a wide range of scales, is an extremely challenging problem. In statistical mechanics, the Mori–Zwanzig (MZ) formalism provides a mathematically exact procedure for constructing reduced-order representations of high-dimensional dynamical systems, where the effects due to the unresolved dynamics are captured in the memory kernel and orthogonal dynamics. Turbulence models based on MZ formalism have been scarce due to the limited knowledge of the MZ operators, which originates from the difficulty in deriving MZ kernels for complex nonlinear dynamical systems. In this work, we apply a recently developed data-driven learning algorithm, which is based on Koopman's description of dynamical systems and Mori's linear projection operator, on a set of fully resolved isotropic turbulence datasets to extract the Mori–Zwanzig operators. With data augmentation using known turbulence symmetries, the extracted Markov term, memory kernel, and orthogonal dynamics are statistically converged and the generalized fluctuation–dissipation relation can be verified. The properties of the memory kernel and orthogonal dynamics, and their dependence on the choices of observables are investigated to address the modeling assumptions that are commonly used in MZ-based models. A series of numerical experiments are then constructed using the extracted kernels to evaluate the memory effects on prediction. The results show that the prediction errors are strongly affected by the choice of observables and can be further reduced by including the past history of the observables in the memory kernel.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

An approximate inertial manifold (AIM) based closure for turbulent flows

A closure model for turbulent flows is developed based on a dynamical system theory. An appropriately discretized formulation of the governing equations is considered for this process. The key ingredient is an approximation of the system’s attractor, where all the trajectories in phase space are confined. This approximate inertial manifold based approach provides a path to track trajectories of the system in a lower-dimensional subspace. Unlike conventional coarse-graining approaches, the turbulent field is decomposed into resolved and unresolved dynamics using the properties of the governing equations. The novelty of the approach relies on the reconstruction of the unresolved field constrained by the governing equations. A posteriori tests for homogeneous isotropic turbulence and the Kuramoto–Sivashinsky equation show promising results for considerable dimension reduction with strong convergence properties. The proposed model outperforms the dynamic Smagorinsky model, and the computational overhead is competitive with similar approaches.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Theory-based scaling laws of near and far scrape-off layer widths in single-null L-mode discharges

Abstract Theory-based scaling laws of the near and far scrape-off layer (SOL) widths are analytically derived for L-mode diverted tokamak discharges by using a two-fluid model. The near SOL pressure and density decay lengths are obtained by leveraging a balance among the power source, perpendicular turbulent transport across the separatrix, and parallel losses at the vessel wall, while the far SOL pressure and density decay lengths are derived by using a model of intermittent transport mediated by filaments. The analytical estimates of the pressure decay length in the near SOL is then compared to the results of three-dimensional, flux-driven, global, two-fluid turbulence simulations of L-mode diverted tokamak plasmas, and validated against experimental measurements taken from an experimental multi-machine database of divertor heat flux profiles, showing in both cases a very good agreement. Analogously, the theoretical scaling law for the pressure decay length in the far SOL is compared to simulation results and to experimental measurements in TCV L-mode discharges, pointing out the need of a large multi-machine database for the far SOL decay lengths.

Physics↗
DOE OSTI2024

Prediction of transport in the JET DTE2 discharges with TGLF and NEO models using the TGYRO transport code

Abstract The JET Deuterium-Tritium-Experiment Campaign 2 (DTE2) has demonstrated the highest-ever fusion energy production. To forecast the transport dynamics within these discharges, the TGLF and NEO models within the TGYRO transport code were employed. A critical development in this study is the new quasilinear transport model, TGLF-SAT2, specifically designed to resolve discrepancies identified in JET deuterium discharges. This model accurately describes the saturated three-dimensional (3D) fluctuation spectrum, aligning closely with a database of nonlinear CGYRO turbulence simulations, thereby enhancing the predictive accuracy of TGYRO simulations. In validating against the JET DTE2 discharges across two primary operating scenarios, TGYRO effectively predicted the temperature profiles within a broad radial window ( ρ ∼ 0.2–0.85), though with minor ion temperature discrepancies near the core. However, a consistent underprediction of electron density profiles by 20% across the simulation domain was noted, indicating areas for future refinement. To achieve a self-consistent steady-state solution based on the JET DTE2 discharges, an integrated modeling workflow TGYRO-STEP within the OMFIT framework was introduced. This workflow iterates among the core transport, the pedestal pressure and the MHD equilibrium, ultimately yielding a converged solution that significantly reduces dependence on experimental boundary conditions for temperature and density profiles. The integrated simulation results show negligible differences in electron density and temperature profiles compared to standalone TGYRO modeling, while the ion temperature profile is lower due to the updated boundary condition in TGYRO-STEP. The application of the TGYRO-STEP workflow to JET DTE2 discharges serves as a crucial test to validate its robustness and highlights its limitations, providing valuable insights for its potential future application in ITER and Fusion Power Plant deuterium and tritium prediction modeling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗