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Research progress in plasma transport properties, wave interaction, electron density measurements, thermal conductivity of argon and helium, heat transfer and pressure gages
Ionization fraction as independent variable in plasma transport correlation, noting role in pressure effect increase
Predicting the charged particle transport properties of warm dense matter/hot dense plasma mixtures is a challenge for analytical models. High accuracy ab initio methods are more computationally expensive, but can provide critical insight by explicitly simulating mixtures. In this work, we investigate the transport properties and optical response of warm dense carbon–hydrogen mixtures at varying concentrations under either conserved electronic pressure or mass density at a constant temperature. We compare options for mixing the calculated pure species properties to estimate the results of the mixtures. We find that a combination of the Drude model with the Matthiessen's rule works well for DC electron transport and low-frequency optical response. This breaks down at higher frequencies, where a volumetric mix of pure-species AC conductivities works better.
During solar flares a tremendous amount of magnetic energy is released and transported through the Sun’s atmosphere and out into the heliosphere. Despite over a century of study, many unresolved questions surrounding solar flares are still present. Among those are how does the solar plasma respond to flare energy deposition, and what are the important physical processes that transport that energy from the release site in the corona through the transition region and chromosphere? Attacking these questions requires the concert of advanced numerical simulations and high spatial-, temporal-, and spectral-resolution observations. While flares are 3D phenomenon, simulating the NLTE flaring chromosphere in 3D and performing parameter studies of 3D models is largely outwith our current computational capabilities. We instead rely on state-of-the-art 1D field-aligned simulations to study the physical processes that govern flares. Over the last decade, data from the Interface Region Imaging Spectrograph (IRIS) have provided the crucial observations with which we can critically interrogate the predictions of those flare loop models. Here in Paper 2 of a two-part review of IRIS and flare loop models, I discuss how forward modelling flares can help us understand the observations from IRIS, and how IRIS can reveal where our models do well and where we are likely missing important processes, focussing in particular on the plasma properties, energy transport mechanisms, and future directions of flare modelling.
Measured filament velocities in the DIII-D tokamak are compared against theoretical scalings, finding that the latter often represents an upper limit on experimental velocity distributions with most filaments possessing lower velocity. Filament spin from internal E × B drift is experimentally demonstrated to alter filament radial velocity. A critical spin velocity, where filament radial velocity peaks, is observed and corresponds to approximately 5 km/s. This transition is corroborated using a less direct measure of filament spin in the form of a temperature ratio. These techniques are combined to find that the critical spin velocity closely aligns with transport times along and across filaments becoming comparable. The normalized filament size distribution is consistent with the most stable size as dictated by Kelvin–Helmholtz and curvature-driven instabilities. Overall, the findings suggest filament stability and spin alter filamentary transport that may threaten the integrity of first walls in fusion devices.
Understanding plasma self-magnetization is one of the fundamental challenges in both laboratory and astrophysical plasmas. Self-magnetization can modify plasma transport properties, altering the dynamical evolution of plasmas. Multiple high-energy-density (HED) experiments have observed the formation of ion-scale magnetic filaments of megagauss strength, though their origin remains debated. Here, in this study, we conduct 2D collisional particle-in-cell (PIC) simulations with a laser ray-tracing module for a fully self-consistent simulation of the plasma ablation, expansion, and magnetization. The simulations use a planar geometry, effectively suppressing the Biermann magnetic fields, to focus on anisotropy-driven instabilities. The laser intensity is varied between 10 13 and 10 14 W/cm 2 , which is relevant to HED and inertial fusion experiments where collisions must be considered. We find that, above a critical intensity, the plasma rapidly self-magnetizes via an expansion-driven Weibel process, producing a plasma beta of 100 (𝛽 = 8𝜋𝑘 𝐵 𝑛 𝑒 𝑇 𝑒 /𝐵 2 ) and Hall parameter 𝜔 ce 𝜏 𝑒 >1 within the first few hundred picoseconds. The magnetic field is sufficiently strong to modify plasma heat transport, and simulations with an artificially suppressed magnetic field show noticeably different temperature profiles.
A wide variety of plasma flow conditions is found in aeronomy and space plasma physics. Transport equations based on an isotropic Maxwellian vilecity distribution function can be used to describe plasma flows which contain 'small' temperature anisotropies. However, for plasma flows characterized by large temperature anisotropies, transport equations based on an anisotropic bi-Maxwellian (or two-temperature) velocity distribution function are expected to provide a much better description of the plasma transport properties. The present investigation is concerned with the extent to which transport equations based on both Maxwellian and bi-Maxwellian series expansions can describe plasma flows characterized by non-Maxwellian velocity distributions, giving particular attention to a modelling of the anisotropic character of the distribution function. The obtained results should provide clues as to the extent to which a given series expansion can account for the anisotropic character of a plasma.
A model for pulsed inductive plasma acceleration containing an energy equation to account for the various sources and sinks in such devices is presented. The model consists of a set of circuit equations coupled to an equation of motion and energy equation for the plasma. The latter two equations are obtained for the plasma current sheet by treating it as a one-element finite volume, integrating the equations over that volume, and then matching known terms or quantities already calculated in the model to the resulting current sheet-averaged terms in the equations. Calculations showing the time-evolution of the various sources and sinks in the system are presented to demonstrate the efficacy of the model, with two separate resistivity models employed to show an example of how the plasma transport properties can affect the calculation. While neither resistivity model is fully accurate, the demonstration shows that it is possible within this modeling framework to time-accurately update various plasma parameters.
Many plasmas of interest in laboratory experiments and space consist of multiple ion species. In tokamak edge plasmas, for instance, ionized impurities expelled from the vessel wall influence plasma transport. When describing multi-species plasmas using fluid equations, we need accurate closure relations to close the set of fluid equations. In this study, we introduce the development of fitting formulas for parallel closures using supervised machine learning, in conjunction with the recent closure theory, considering multi-ion collisions and arbitrary ion temperatures. We apply this approach to a high-collisionality deuterium-carbon plasma and demonstrate its effectiveness. As a result, the machine learning-based method for developing practical and accurate closures can be extended to a wider range of plasmas.
Anomalous transport of multi-species plasma is considered with the generalized Hasegawa–Wakatani model [A. R. Knyazev and S. I. Krasheninnikov, Phys. Plasmas 31, 012502 (2024)] further extended to incorporate the Finite Larmor Radius (FLR) effects. By introducing the “associated” enstrophy, it is shown that with no FLR effects (where anomalous transport of all ion species is described as a transport of passive scalars in the turbulent fields of the electrostatic potential and electron density fluctuations) the fluctuating densities of ion species converge to the state where they are linearly proportional to electron density and vorticity fluctuations, which confirm previous numerical findings of [A. R. Knyazev and S. I. Krasheninnikov, Phys. Plasmas 31, 012502 (2024)]. However, in contrast to the “cold” ion approximation, with the FLR effects included, both the plasma turbulence and the dynamics of all ion species become interconnected. Therefore, for simplicity, the FLR effects in this work were considered only for a small “trace” impurity fraction. It is found that for light (neon) “trace” impurity, the FLR effects reduce both anomalous flux and density fluctuations. However, for heavy (tungsten) “trace” impurity, the FLR effects exhibit non-monotonic impact on anomalous transport.
Anomalous transport of mixed deuterium–tritium plasma in the edge of magnetic fusion reactors is investigated using numerical solutions of resistive drift wave turbulence model equations, including finite Larmor radius effects, that are derived within the generalized Hasegawa–Wakatani framework. The anomalous cross field diffusivities of deuterium and tritium are compared in turbulence regimes with different values of the electron adiabaticity parameter controlling the existence of zonal flow. The dependence of the tritium-to-deuterium diffusivity ratio on the deuterium and tritium densities and the logarithmic density gradients is analyzed, and a scaling relation is obtained.
Current delivery in pulsed power inertial confinement fusion is influenced by collisionless current-carrying microturbulent plasmas, which are sourced from electrode surfaces. In this setting, the lower hybrid drift instability—triggered by plasma acceleration—is a leading candidate driver of difficult-to-predict momentum and energy transport. To characterize the nonlinear state of the microturbulent plasma, a parameterized anomalous transport model is developed for the instability, with analytic formulas for anomalous collision frequency, resistivity, and species heating rates. The formulas are expressed in terms of linear-theory variables and four dimensionless parameters that characterize the macroscopic plasma state. The model is built on linear theory analysis, power law analysis, and quasilinear theory analysis, and is validated using a series of nonlinear continuum kinetic Vlasov–Poisson simulations. The theoretical and computational investigation demonstrates that the anomalous collision frequency associated with the instability can be reliably approximated, within about a factor of five or better, by the unscaled linear theory growth rate of the fastest-growing wavenumber mode. This finding enables efficient calculation of anomalous resistivity and species heating rates over a wide range of plasma conditions, resulting in improved predictive capabilities.
This study presents a systematic investigation of the transverse-momentum differential radial flow fluctuations observable 𝑣 0 (𝑝 𝑇 ) in relativistic heavy-ion collisions at top Relativistic Heavy Ion Collider ($\sqrt{s_{NN}}$ = 200 GeV) and Large Hadron Collider ($\sqrt{s_{NN}}$ = 2.76 and 5.02 TeV) energies. Using a multistage hydrodynamic model, this study assesses the sensitivity of 𝑣 0 (𝑝 𝑇 ) to a wide range of physical effects, including bulk and shear viscosities, off-equilibrium corrections at particlization, the presence of a hadronic afterburner, and the nucleon size in the initial conditions. By employing complementary rescaling strategies, this study demonstrates how different physical effects leave distinct imprints on the shape of 𝑣 0 (𝑝 𝑇 ). A combined double-rescaling of 𝑣 0 (𝑝 𝑇 )/𝑣 0 versus 𝑝 𝑇 /⟨𝑝 𝑇 ⟩ reveals a universality across a wide range of energies and model assumptions in the low-𝑝 𝑇 regime, a robust signature of collective behavior. This allows us to disentangle the universal dynamics of the bulk medium from model-specific features that emerge at higher 𝑝 𝑇 . These results establish 𝑣 0 (𝑝 𝑇 ) as a powerful and complementary observable for constraining quark-gluon plasma transport properties and initial-state granularity, offering a unique probe of the created QCD medium.
Transport properties and distribution function dynamics in one dimensional plasma models
We report the results of the second charged-particle transport coefficient code comparison workshop, which was held in Livermore, California on 24–27 July 2023. This workshop gathered theoretical, computational, and experimental scientists to assess the state of computational and experimental techniques for understanding charged-particle transport coefficients relevant to high-energy-density plasma science. Data for electronic and ionic transport coefficients, namely, the direct current electrical conductivity, electron thermal conductivity, ion shear viscosity, and ion thermal conductivity were computed and compared for multiple plasma conditions. Additional comparisons were carried out for electron–ion properties such as the electron–ion equilibration time and alpha particle stopping power. Overall, 39 participants submitted calculated results from 18 independent approaches, spanning methods from parameterized semi-empirical models to time-dependent density functional theory. In the cases studied here, we find significant differences—several orders of magnitude—between approaches, particularly at lower temperatures, and smaller differences—roughly a factor of five—among first-principles models. We investigate the origins of these differences through comparisons of underlying predictions of ionic and electronic structure. The results of this workshop help to identify plasma conditions where computationally inexpensive approaches are accurate, where computationally expensive models are required, and where experimental measurements will have high impact.
Gyro-fluid equations are velocity space moments of the gyrokinetic equations. Special gyro-Landau-fluid closures have been developed that include the damping due to kinetic resonances by fitting to the collisionless local plasma response functions. This damping allows for accurate linear eigenmodes to be computed with a relatively low number of velocity space moments compared to the number of velocity quadrature points in gyrokinetic codes. However, none of the published gyro-Landau-fluid closure schemes considers the Onsager symmetries of the resulting quasi-linear fluxes as a constraint. Onsager symmetry guarantees that the matrix of diffusivities is positive definite, an important property for the numerical stability of a transport solver. A two-parameter real closure for improving the accuracy of low-resolution gyro-fluid equations, which preserves the Onsager symmetry and allows higher velocity space moments, is presented in this paper. The new linear gyro-fluid system (GFS) is used to extend the TGLF quasi-linear transport model so that it can compute the energy and momentum fluxes due to parallel magnetic fluctuations, completing the transport matrix. The GFS equations do not use a bounce average approximation. The GFS equations are fully electromagnetic with general flux surface magnetic geometry, pitch angle scattering for electron collisions, and subsonic equilibrium toroidal rotation. Using GFS eigenmodes in the quasi-linear TGLF model will be shown to yield a more accurate match to fluxes computed by CGYRO turbulence simulations. In conclusion, prospects for future applications of a quasi-linear theory to new plasma transport regimes and magnetic confinement devices in addition to tokamaks are opened by the flexibility of the GFS eigensolver.
This work presents a Bayesian inference study for relativistic heavy-ion collisions in the beam energy scan program at the BNL Relativistic Heavy-Ion Collider. The theoretical model simulates event-by-event (3+1)-dimensional [(3+1)D] collision dynamics using hydrodynamics and hadronic transport theory. We analyze the model's 20-dimensional posterior distributions obtained using three model emulators with different accuracy and demonstrate the essential role of training an accurate model emulator in the Bayesian analysis. Our analysis provides robust constraints on the quark-gluon plasma's transport properties and various aspects of (3+1)D relativistic nuclear dynamics. By running full model simulations with 100 parameter sets sampled from the posterior distribution, we make predictions for p T -differential observables and estimate their systematic theory uncertainty. Here, a sensitivity analysis is performed to elucidate how individual experimental observables respond to different model parameters, providing useful physics insights into the phenomenological model for heavy-ion collisions.