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Dimits transition in three-dimensional ion-temperature-gradient turbulence

Published online by Cambridge University Press:  13 October 2022

Plamen G. Ivanov*
Affiliation:
Rudolf Peierls Centre for Theoretical Physics, University of Oxford, Oxford OX1 3PU, UK EURATOM/UKAEA Fusion Association, Culham Science Centre, Abingdon OX14 3DB, UK
A.A. Schekochihin
Affiliation:
Rudolf Peierls Centre for Theoretical Physics, University of Oxford, Oxford OX1 3PU, UK Merton College, Oxford OX1 4JD, UK
W. Dorland
Affiliation:
Rudolf Peierls Centre for Theoretical Physics, University of Oxford, Oxford OX1 3PU, UK Department of Physics, University of Maryland, College Park, MD 20742, USA
*
Email address for correspondence: plamen.ivanov@physics.ox.ac.uk
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Abstract

We extend our previous work on the two-dimensional (2-D) Dimits transition in ion-scale turbulence (Ivanov et al., J. Plasma Phys., vol. 86, 2020, 855860502) to include variations along the magnetic field. We consider a three-field fluid model for the perturbations of electrostatic potential, ion temperature, and ion parallel flow in a constant-magnetic-curvature geometry without magnetic shear. It is derived in the cold-ion, long-wavelength asymptotic limit of the gyrokinetic theory. Just as in the 2-D model, a low-transport (Dimits) regime exists and is found to be dominated by a quasistatic staircase-like arrangement of strong zonal flows and zonal temperature. This zonal staircase is formed and maintained by a negative turbulent viscosity for the zonal flows. Unlike the 2-D model, the three-dimensional (3-D) one does not suffer from an unphysical blow up beyond the Dimits threshold where the staircase becomes nonlinearly unstable. Instead, a well-defined finite-amplitude saturated state is established. This qualitative difference between the 2-D and 3-D models is due to the appearance of small-scale ‘parasitic’ modes that exist only if we allow perturbations to vary along the magnetic field lines. These modes extract energy from the large-scale perturbations and provide an effective enhancement of large-scale thermal diffusion, thus aiding the energy transfer from large injection scales to small dissipative ones. We show that in our model, the parasitic modes always favour a zonal-flow-dominated state. In fact, a Dimits state with a zonal staircase is achieved regardless of the strength of the linear drive, provided the system is sufficiently extended along the magnetic field and sufficient parallel resolution is provided.

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Type
Research Article
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Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press
Figure 0

Figure 1. Illustration of the 3-D $Z$-pinch magnetic geometry.

Figure 1

Figure 2. A visualisation of the linear growth rate, ${\textrm {Im}{\left (\omega _{\boldsymbol {k}}\right )}}$, given by (3.1), for $\kappa _T = 1$ and $\chi = 0.1$. (a) The linear growth rate in the $k_\parallel = 0$ plane. This is the 2-D cITG instability that we dealt with in Ivanov et al. (2020). (b) The linear growth rate in the $k_x = 0$ plane (where it is largest). The solid black lines denote the marginal modes with ${\textrm {Im}{\left (\omega _{\boldsymbol {k}}\right )}} = 0$. The dotted lines outline the region of unstable collisionless ($\chi = 0$), pure-slab ($L_B^{-1} = 0$) modes, given by (3.14).

Figure 2

Figure 3. Linear growth rates for the sITG instability (without the magnetic drift) as a function of parallel ($k_\parallel$) and poloidal ($k_y$) wavenumbers for $k_x = 0$, $\kappa _T = 1$, $\chi = 0$. The growth rate along the $k_\parallel = \kappa _T k_{\perp } k_y$ line converges to $\kappa _T / \sqrt {2} \approx 0.7$ for large $k_\parallel$. The solid black lines are the instability boundary given by (3.14).

Figure 3

Figure 4. Example of instantaneous radial profiles of perturbations in the 3-D Dimits state for $L_x = L_y = 80$: (a) ZF; (b) zonal shear; (c) zonal temperature gradient. Example of instantaneous radial profiles in strong turbulence: (d) ZF; (e) zonal shear; (f) zonal temperature gradient. The dotted green lines in (b,e) are the largest linear growth rates for the respective simulations. The dotted orange lines in (c,f) show the value of $\kappa _T$, which is equal to minus the normalised equilibrium temperature gradient. Just as in the 2-D case, the zonal shear in the Dimits state is determined by the largest linear growth rate. Strongly turbulent ZFs do not have regions of coherent shear.

Figure 4

Figure 5. Snapshots of the perturbed nonzonal (a) temperature $T'$, (b) potential $\varphi '$, (c) pressure $p' = \varphi ' + T'$, and (d) parallel velocity ${u}'$ in the 3-D Dimits state. The colour scale is relative to the maximum absolute amplitude in each panel (given in the panels’ titles). We see that ferdinons carry a ${u}$ perturbation, as well as $T$ and $\varphi$ perturbations. A more detailed view of one of the ferdinons is shown in figure 7. These snapshots are from the same simulation as figure 4(ac).

Figure 5

Figure 6. (a) Dependence of the time-averaged heat flux $Q$ on the parallel size of the box $L_{\parallel }$ for $\chi = 0.1$, $L_x = L_y = 80$, and $\kappa _T=0.36$. The orange dotted line shows the time-averaged heat flux for the 2-D state ($L_{\parallel } = 0$). (b) Same as (a), but with $\kappa _T = 0.8$. (cf) Time evolution of the heat flux $Q$ for $\kappa _T = 0.8$, $\chi = 0.1$, $L_x = 80$, $L_y = 80$, and four different values of $L_{\parallel }$ (notated on each panel). As $L_{\parallel }$ increases, the turbulent bursts become more frequent and less violent, and the time-averaged $Q$ drops.

Figure 6

Figure 7. Snapshots of the 3-D temperature perturbations associated with a ferdinon. The plots in each row are cross-sections in different planes at the same $t$ taken from simulations that have the same $\kappa _T = 0.36$, $\chi =0.1$, $L_x = L_y = 80$, but (a) $L_{\parallel } = 32$, (b) $L_{\parallel } = 64$, and (c) $L_{\parallel } = 256$. The black dashed lines visualise the intersections of the cross-sectional planes. As we increase $L_{\parallel }$, turbulence loses the ability to stay coherent along the parallel extent of the box and the bursts become localised in $z$.

Figure 7

Figure 8. Snapshots of perturbed nonzonal (a) temperature, (b) potential, (c) pressure, and (d) parallel velocity at fixed $z$ in the Dimits state with parameters $\kappa _T = 0.8$, $\chi = 0.1$, $L_x = L_y = 80$, $L_{\parallel } = 1$, parallel hyperviscosity $\nu = 2.4\times 10^{-8}$, and Fourier-space resolution $(n_x, n_y, n_z) = (171, 171, 21)$. The colour scale is relative to the maximum absolute amplitude in each panel (given in the panel's title). Small-scale sITG modes driven by the gradients of the ferdinon are evident in panel (d).

Figure 8

Figure 9. Snapshots of perturbed nonzonal (a) temperature, (b) potential, (c) pressure and (d) parallel velocity at fixed $z$ in the strongly turbulent state with parameters $\kappa _T = 3$, $\chi = 0.05$, $L_x = L_y = 80$, $L_{\parallel } = 1$, parallel hyperviscosity $\nu = 1.5\times 10^{-10}$, and Fourier-space resolution $(n_x, n_y, n_z) = (285, 285, 83)$. The colour scale is relative to the maximum absolute amplitude in each panel (given in the panel's title). Time-averaged spectra from the same simulation are shown in figure 10.

Figure 9

Figure 10. Time-averaged spectra (a) $W_{\boldsymbol {k}}$ and (b) $I_{\boldsymbol {k}}$, defined by (2.17) and (2.18), respectively, in the strongly turbulent state with parameters $\kappa _T = 3$, $\chi = 0.05$, $L_x = 80$, $L_y = 80$, and $L_{\parallel } = 1$. The solid black lines demarcate the region of linear instability for $k_x = 0$, and the red dashed line is $k_\parallel = \kappa _T k_{\perp }^2$, where the collisionless modes with largest growth rate reside (see § 3.3.2). We can see that the largest contributions to the two conserved quantities are offset from the region of linear instability. The dotted black line denotes the peak $k_{\perp, I}(k_\parallel )$ of $I_{\boldsymbol {k}}$ at fixed $k_\parallel$. Zonal profiles and cross-sectional snapshots from the same simulation are shown in figures 4 and 9, respectively. The spectra of the saturated state with the same parameters, but with $\kappa _T$ set to $0$ for all $k_\parallel \neq 0$ modes, are given in (c,d). Turning off the equilibrium gradient for the 3-D modes does not alter the spectra noticeably. Snapshots from this modified simulation are shown in figure 11.

Figure 10

Figure 11. Same as figure 9, but for a modified simulation, i.e., with $\kappa _T$ set to zero for the $k_\parallel \neq 0$ modes. Visually, the saturated state is identical to that shown in figure 9.

Figure 11

Figure 12. (a) Comparison of the location of the spectral peak $k_{\perp, I} (k_\parallel )$ of $I_{\boldsymbol {k}}$ (blue line) and the location of the peak of the growth rate of the collisionless linear instability driven by the equilibrium gradient (orange dashed line), given by $k_\parallel = \kappa _T k_{\perp }^2$. The black curve circumscribes the region of linear instability, i.e., all ${\textrm {Im}{\left (\omega _{\boldsymbol {k}}\right )}} \geq 0$ solutions to (3.1) are inside it and outside of it, all solutions satisfy ${\textrm {Im}{\left (\omega _{\boldsymbol {k}}\right )}} \leq 0$. (b) Comparison of the equilibrium temperature gradient $\kappa _T$ and the ‘effective’ temperature gradient $\kappa _T^\textrm {eff}(k_\parallel ) \equiv k_\parallel / k_{\perp, I}^2$. The data is from the same simulation as shown in figure 9. The spectra of this simulation are given in figure 10. This rough estimate of $\kappa _T^\textrm {eff}$ being approximately 5–10 times larger than $\kappa _T$ is consistent with the calculated growth rate of the parasitic small-scale instability (see figure 13).

Figure 12

Figure 13. (a) Snapshot of the 2-D temperature perturbation $\left \langle T \right \rangle _\parallel$ in the $(x, y)$ plane. The data is taken from the same $\kappa _T = 3$, $\chi = 0.05$ simulation that we showed in figure 9. The 2-D temperature perturbations lack the small-scale structure that was seen in figure 9(a), confirming that the parallel average (4.5) removes small-scale perpendicular structure. (b) Small-scale growth rate in the $(x, y)$ plane. This plot is obtained by finding the maximum growth rate of the full (including collisionality and magnetic curvature) dispersion relation (3.1) with the addition of the local temperature and density gradients of the large-scale fields at every point. For this simulation, $\kappa _T = 3$, and so the largest collisionless growth rate, given by (3.25), is $\kappa _T / \sqrt {2} \approx 2.1$. It is thus evident that the influence of the gradients of the large-scale fields dominates over that of the equilibrium gradient $\kappa _T$ by a factor of $5$. The ‘effective’ $\kappa _T^\textrm {eff}$ that we estimated for the same simulation in figure 12(b) is, indeed, a factor of 5–10 larger that the equilibrium gradient $\kappa _T$.

Figure 13

Figure 14. This plot shows the direction in which the heat flux (4.22) of the most unstable small-scale mode ($\hat {\boldsymbol {q}} = \hat {\boldsymbol {q}}_{\textrm {max}}$) pushes the temperature gradient $\boldsymbol {\kappa }_T = -\hat {\boldsymbol {z}}\times \boldsymbol {\nabla }_\perp \left \langle T \right \rangle _\parallel$. We have chosen a coordinate system in which the large-scale density gradient is $\boldsymbol {\kappa }_n = (0, 1)$, denoted by the green arrow. The red line shows the values of $\boldsymbol {\kappa }_T$ for which the sITG instability has zero growth rate, according to (4.20). The black arrows represent the direction of $-\hat {\boldsymbol {z}}\times \langle \widetilde {\boldsymbol {Q}}\rangle _\parallel$. We see that $\langle \widetilde {\boldsymbol {Q}}\rangle _\parallel$ pushes the large-scale temperature gradient $\boldsymbol {\kappa }_T$ towards the linearly stable region.

Figure 14

Figure 15. (a) Linear growth rate and (b) the ratio ${\textrm {Re}{\left (T_{\boldsymbol {k}}/\varphi _{\boldsymbol {k}}\right )}}$ of the most unstable ($k_x=0$) modes versus $k_\parallel$ and $k_y$ for $\kappa _T = 1$ and $\chi = 0.1$. The green dashed line is ${\textrm {Re}{\left (T_{\boldsymbol {k}}/\varphi _{\boldsymbol {k}}\right )}} = -1$. The black dashed line is the location of the largest collisionless growth rate $k_\parallel = \kappa _T k_y^2$. While the green and black lines would coincide to $O(k_{\perp }^{-2})$ for the collisionless modes, we see that the addition of collisions shifts the linearly unstable modes towards the Dimits-favourable ${\textrm {Re}{\left (T_{\boldsymbol {k}}/\varphi _{\boldsymbol {k}}\right )}} > -1$ ratio.

Figure 15

Figure 16. Dependence of the turbulent viscosity (4.4) on the temperature gradient for $\chi = 0.1$ and $L_{\parallel } = 1$. The 2-D Dimits regime ends at $\kappa _T^{c, \textrm {2D}} \approx 1$. In 3-D simulations, the 2-D modes eventually reverse their turbulent viscosity (red), but the 3-D sITG modes continue to feed the ZFs through a negative turbulent viscosity (blue). The data is taken from simulations with fixed ZF profiles.

Figure 16

Figure 17. Schematic of the flow of energy in (a) the Dimits regime, characterised by strong, turbulence-shearing, staircase ZFs and (b) strong turbulence, where no such ZFs can be generated or sustained. In the Dimits regime, the equilibrium gradients (EG) inject energy into large-scale modes via the 2-D cITG instability. These can then drive ZFs via the secondary instability (see § 2.8 of Ivanov et al.2020) and small-scale perturbations via the parasitic sITG instability (see § 4.2). In the 2-D Dimits regime ($\kappa _T < \kappa _T^{c, \textrm {2D}}$), the curvature-driven large-scale modes generate a negative turbulent viscosity on the ZFs and hence reinforce the Dimits state. For $\kappa _T > \kappa _T^{c, \textrm {2D}}$, the 2-D modes erode the ZFs, but the ZF drive of the parasitic modes sustains the ZFs (see § 4.2.5). On the other hand, if a Dimits state cannot be achieved, the energy injected into the large-scale modes is transferred to small scales via the parasitic sITG instability, whence it cascades to even smaller, linearly stable scales where it is taken out of the system.

Figure 17

Figure 18. Dependence of the saturated turbulent heat flux $Q$ on (a) the parallel size of the box $L_{\parallel }$ and (b) the largest parallel Fourier mode $k_{\parallel, \textrm {max}}$ that is included in the simulation.

Figure 18

Figure 19. The left-hand (red) and right-hand (blue) sides of the sITG dispersion relation (3.12) for $\hat {k}_{\parallel } = 2$, $k_{\perp }^2 = 0.2$. There is only one real solution, so there exists a complex one with positive imaginary part. Thus, there are linearly unstable modes for $\hat {k}_{\parallel } = 2$, $k_{\perp }^2 = 0.2$.

Figure 19

Figure 20. (a) Largest growth rate ${\textrm {Im}{(\hat {\omega }_{\boldsymbol {k}})}}$ obtained by solving (C1). (b) The ratio ${\textrm {Re}{(T_{\boldsymbol {k}}/\varphi _{\boldsymbol {k}})}}$ for the most unstable mode. The solid black line is the stability boundary ${\textrm {Im}{(\hat {\omega }_{\boldsymbol {k}})}} = 0$. The dotted lines in (a) show the analytic approximations to the $\alpha _{\boldsymbol {k}}$ and $\beta _{\boldsymbol {k}}$ instability boundaries, given by (C4) (for $\beta _{\boldsymbol {k}} \ll 1$) and (C10) (for $\beta _{\boldsymbol {k}} \sim \lambda \ll 1$). We see perfect agreement with (C4), but a slight discrepancy with (C10), whose derivation is accurate only under the assumption that $1 -a -b = \lambda \approx 0.36$ is small. All unstable modes lie within ${\textrm {Re}{(T_{\boldsymbol {k}}/\varphi _{\boldsymbol {k}})}} > -1$.

Figure 20

Figure 21. Plot of the time-averaged 2-D heat flux $Q_\textrm {2D}$ given by (F8) (solid blue), the 3-D heat flux $Q_\textrm {3D} \equiv Q - Q_\textrm {2D}$ (dash–dotted black), the collisional dissipation in (F6)$D_{\left \langle \varphi \right \rangle _\parallel }$ given by (F9) (dashed green), and the collisional dissipation in (F7), $D_{\left \langle T \right \rangle _\parallel }/\kappa _T$ given by (F10) (dashed orange) versus $\kappa _T$ for $\chi = 0.05$, $L_x = L_y = 60$ and $L_{\parallel } = 0.5$. We see that $Q_\textrm {2D}$ is more than twice $Q_\textrm {3D}$, and is balanced nearly perfectly by $D_{\left \langle \varphi \right \rangle _\parallel }$, i.e., the nonlinear transfer in (4.6) is small. On the other hand, $D_{\left \langle T \right \rangle _\parallel }/\kappa _T Q_\textrm {2D} \ll 1$, so the majority of energy injected into $\left \langle T \right \rangle _\parallel$ is nonlinearly transferred to 3-D modes.

Figure 21

Figure 22. The linear growth rate ${\textrm {Im}{(\omega _{\boldsymbol {k}})}}$ of the kinetic dispersion relation (G4) for $\tau = 0.01$, normalised as $\hat {\omega }_{\boldsymbol {k}} = L_T\omega _{\boldsymbol {k}}/c_s\tau$, which is equivalent to normalisation of time in (2.10) for $\kappa _T = 1$. The wavenumbers $k_y$ and $k_\parallel$ are also normalised according to (2.10) with $\kappa _T=1$. The largest kinetic growth rate is ${\textrm {Im}{(\hat {\omega }_{\boldsymbol {k}}^\textrm {kin})}} \approx 1.07$, while the largest cold-ion growth rate, given by (3.25), is ${\textrm {Im}{(\hat {\omega }_{\boldsymbol {k}}^\textrm {cold})}} \approx 0.71$. The vertical dotted line is the critical parallel wavenumber $k_\parallel ^{({c})}$ for $k_{\perp } \gg 1$ kinetic modes (G11). The dashed black lines are the cold-ion stability boundary (3.14). The solid black line is the kinetic stability boundary (G10). The kinetic sITG instability has a finite growth rate at $k_{\perp } \to \infty$.

Figure 22

Figure 23. (a) Growth rate ${\textrm {Im}{(\hat {\omega }_{\boldsymbol {q}})}}$, normalised as $\hat {\omega }_{\boldsymbol {q}} = L_T\omega _{\boldsymbol {q}}/c_s\tau$, which is equivalent to normalisation of time in (2.10) for $\kappa _T = 1$. (b) The ratio ${\textrm {Re}{(\mathcal {P}_{\boldsymbol {q}}/\varphi _{\boldsymbol {q}})}}$, given by (H17). For both panels, $\tau = 0.01$ and $q_x = 0$. The wavenumbers $q_y$ and $q_\parallel$ are also normalised according to (2.10) with $\kappa _T=1$. The solid black lines show the kinetic stability boundary (G10). It is evident that the vast majority of sITG modes, including the dominant ones, support the ZFs, i.e., satisfy ${\textrm {Re}{(\mathcal {P}_{\boldsymbol {q}}/\varphi _{\boldsymbol {q}})}} > 0$.

Figure 23

Figure 24. Same as figure 23, but for $\tau = 1$. Evidently, the small-scale sITG modes at $q_y \gg 1$ have ${\textrm {Re}{(\mathcal {P}_{\boldsymbol {q}}/\varphi _{\boldsymbol {q}})}} > 0$, i.e., they support the ZFs. However, it is no longer obvious whether the dominant sITG modes support or destroy the ZFs.