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Characterization of reduced-order turbulence models in the L-mode pedestal-forming region in JET

T0 review · 2 major / 6 minor · reviewed 2026-08-07 · deepseek-v4-flash

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Pith's one-line read The paper claims QuaLiKiz is inadequate beyond $\rho_{\mathrm{tor}}=0.85$ in JET's L-mode pedestal-forming region, while TGLF-SAT2 agrees with GENE linear spectra and quasilinear heat fluxes through $\rho_{\mathrm{tor}}=0.9$.

desk verdict Careful, valuable verification of QuaLiKiz and TGLF-SAT2 at the L-mode edge, but the abstract oversells TGLF at rho_tor=0.9. read the letter →

arxiv 2506.03459 v1 pith:HGSQJRVD submitted 2025-06-03 physics.plasm-ph

G. Snoep , C. Bourdelle , J. Citrin , A. Ho , M. J. Pueschel , P. Vincenzi , E. R. Solano , M. Sertoli
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E. Delabie Jet Contributors
This is my paper
classification physics.plasm-ph PACS 52.35.Qz52.55.Fa
keywords gyrokineticsimulationsL-HtransitionL-modepedestalreduced-orderturbulencemodelsQuaLiKizTGLFtrappedelectronmodescollisionality
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper tests whether two fast quasilinear transport models can be trusted in the outermost region of an L-mode tokamak plasma, the zone where the pedestal forms just before the transition to H-mode. Using linear gyrokinetic simulations with the GENE code for seven JET discharges at $\rho_{\mathrm{tor}}=0.85,0.9,0.95$, the authors map which microinstabilities dominate on the low- and high-density branches of the L-H power threshold. They find that QuaLiKiz becomes inadequate beyond $\rho_{\mathrm{tor}}=0.85$, whereas TGLF-SAT2 agrees with the linear spectra and quasilinear heat fluxes up to $\rho_{\mathrm{tor}}=0.9$. The practical stake is that integrated modeling codes need to know how far toward the separatrix they can extend the outer simulation boundary before the reduced turbulence model misrepresents the transport.

What carries the argument

The central object is the local linear gyrokinetic spectrum computed with the GENE code, organized as a scan in normalized electron collisionality $\nu_e^*$ at each radius. The paper identifies the experimental collisionality interval as a minimum-drive gap between collisionless ITG/TEM branches at low $\nu_e^*$ and resistive branches at high $\nu_e^*$, and uses that gap as the yardstick for what a reduced model must reproduce. The fidelity reduction then isolates each reduced model's assumptions: QuaLiKiz's electrostatic $s$-$\alpha$ geometry and Krook collision operator, and TGLF-SAT2's gyrofluid equations, Miller geometry, and pitch-angle-scattering collision model.

What would settle it

A nonlinear GENE simulation at $\rho_{\mathrm{tor}}=0.9$ for a high-density discharge, with the experimental profiles and numerical equilibrium, would settle the inward-particle-flux claim: if the saturated particle flux is outward, the quasilinear transport prediction validated here fails in the regime where TGLF-SAT2 is recommended.

Watch

Extended reading notes

Core claim

On its own terms, the paper establishes a boundary on the applicability of reduced-order quasilinear models in the L-mode pedestal-forming region: QuaLiKiz is reliable only where electron collisionality stays in the banana regime, roughly $\rho_{\mathrm{tor}}\leq0.85$; TGLF-SAT2 remains reliable through $\rho_{\mathrm{tor}}=0.9$, including the high-density $\ell=1$ ion modes with trapped-ion drive, but breaks down at $\rho_{\mathrm{tor}}=0.95$ where hybrid modes and resistive drift-wave branches with non-adiabatic passing electrons dominate. The evidence is a systematic linear gyrokinetic characterization: trapped-electron modes and ITG modes at inner radii, unconventional ballooning ion modes and collisionality-driven resistive branches near the edge, with the experimental collisionality sitting near a minimum of linear drive between branches. The same dataset shows that the experimentally observed dependencies of the L-H power threshold on density, isotope mass, shaping, and impurities are mirrored in the linear stability properties.

Load-bearing premise

The load-bearing premise is that the fitted local gradients, collisionalities, and reconstructed magnetic equilibria are accurate enough that the seven discharges really sit in the reported instability regimes; the paper acknowledges that reflectometry radial-position uncertainty was not propagated, ECE data were cut below 800 eV, and impurity profiles were extrapolated for two discharges, so a bias in any of these inputs would shift the mode identifications and therefore the reduced-model verdicts.

Editorial extensions

If this is right

  • Integrated modeling of L-mode plasmas can extend the outer simulation boundary to $\rho_{\mathrm{tor}}=0.9$ when using TGLF-SAT2, provided the local collisionality stays below the plateau-Pfirsch-Schlüter boundary.
  • QuaLiKiz should not be used to predict pedestal-forming transport beyond $\rho_{\mathrm{tor}}=0.85$; within the banana regime at that radius it still captures the dominant TEM and ITG branches.
  • At $\rho_{\mathrm{tor}}=0.95$, neither reduced model reproduces the hybrid and resistive modes, so integrated modeling must keep its boundary inside this radius or supplement the reduced model with higher-fidelity physics.
  • The quasilinear particle flux direction is tied to the same collisionality window: inward flux appears only where the linear drive is minimized, which matters for predicting density-profile evolution during pedestal build-up.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • A practical switching rule for integrated modeling could be built from local $\rho_{\mathrm{tor}}$ and $\nu_e^*$, choosing QuaLiKiz below $0.85$, TGLF-SAT2 through $0.9$, and higher-fidelity gyrokinetics beyond; the paper stops short of proposing such a rule.
  • Machine-learning surrogates of QuaLiKiz trained on JET-like edge data would inherit the failure beyond $\rho_{\mathrm{tor}}=0.85$; the GENE dataset assembled here offers a target for retraining on the edge regime.
  • A nonlinear simulation campaign at $\rho_{\mathrm{tor}}=0.9$ comparing saturated particle flux direction with the quasilinear prediction would test whether the inward-flux window survives saturation.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

2 major / 6 minor

Summary. The paper presents a linear gyrokinetic stability analysis of seven JET-ILW L-mode discharges in the pedestal-forming region (rho_tor = 0.85, 0.90, 0.95), just before the L-H transition, using the GENE code. It characterizes the dominant instabilities, including TEMs, ITGs, unconventional l=1 ion-direction modes, and collisionality-dependent resistive/hybrid modes, and performs extensive sensitivity scans in gradients, collisionality, isotope mass, magnetic geometry, and beta. The second half of the paper benchmarks the reduced quasilinear models QuaLiKiz and TGLF-SAT2 against GENE, using staged model reductions to isolate the effect of geometry, collision operators, and electromagnetic effects. The main conclusions are that QuaLiKiz is not reliable beyond rho_tor = 0.85, while TGLF-SAT2 agrees well with linear spectra and quasilinear flux ratios up to and including rho_tor = 0.9.

Significance. If the central claims hold, this is a valuable verification dataset for reduced-order transport models in a region of growing importance for integrated modeling. The paper is carefully structured: convergence checks are reported, model reductions are explicit, and the comparison is performed on a common input-generation pipeline. The identification of unconventional l=1 ion modes and the mapping of collisionality regimes onto neoclassical banana/plateau/Pfirsch-Schlueter boundaries are useful physical results. The authors also provide open-source tools (GyroKit, MEGPy) and state that the simulation database will be made available, which strengthens reproducibility. The main weaknesses are that the abstract overstates the level of TGLF-SAT2 agreement relative to the paper's own quantitative results, and that the flux part of the recommendation is shown in Appendix E to be sensitive to the flux-surface parameterization choice.

major comments (2)
  1. [Abstract; Section IV.D.2] The statement that TGLF-SAT2 'agrees well with linear spectra and the quasilinear heat fluxes from GENE up to and including rho_tor = 0.9' is stronger than the evidence reported in Section IV.D.2. At rho_tor = 0.9 the paper states that for k_y rho_s < 0.15 TGLF-SAT2 predicts different dominant instabilities than GENE for all discharges; for several low-triangularity discharges the dominant modes at k_y rho_s <= 0.3 have the correct growth rate but the wrong propagation direction; for high-density branch discharges TGLF-SAT2 overpredicts growth rates by up to 30% (attributed to the PAS collision model); and the q_i/q_e ratios for the l=1 ion-direction branches are significantly higher in GENE than in TGLF-SAT2. These are not small deviations at unimportant wavenumbers, since k_y rho_s ~ 0.2 is used throughout the paper as transport-relevant. The paper never defines a quantitative criterion for 'agrees well.' The abstract and Section V should either introduce a quantitative error metric and show that it is met, or be reworded to distinguish 'reasonable agreement on the dominant mode at many wavenumbers' from 'agreement in mode identity, propagation direction, and growth-rate magnitude.'
  2. [Appendix E; Section V] The recommendation in Section V that TGLF-SAT2 is suitable for integrated modeling in this region is not supported by the flux sensitivity documented in Appendix E. Figure 34 shows that TGLF-SAT2 saturated heat and particle fluxes change by 40-80% at rho_tor = 0.85 and by 20-60% at rho_tor = 0.95 depending on whether the Miller equilibrium parameterization is generated with FLUSH or MEGPy, while the area under the linear growth-rate spectrum differs by only ~8%. Since rho_tor = 0.85 is within the range for which the abstract recommends TGLF-SAT2, the 'quasilinear heat fluxes' part of the recommendation is not parameterization-independent. The paper should either restrict the agreement claim to the linear spectra and flux ratios, or explicitly address how the flux sensitivity affects the practical recommendation for integrated modeling.
minor comments (6)
  1. [Throughout] The word 'collisonality' is misspelled as 'collisionality' in the abstract and in several places in the main text; please correct globally.
  2. [Section II.A; Section III.B.3; Appendix B] Several unresolved placeholders appear: '5-20% ?', 'Z_eff ~ 1.2-1.4 ?', and 'see Table I?'; these should be completed with references or deleted.
  3. [Appendix B] The sentence 'This is correlated with #94114 having about , as can be seen in Table I.' is incomplete and needs to be finished or removed.
  4. [Abstract; Section IV.A] The phrase 'quasilinear heat fluxes from GENE' is imprecise; the comparison in Section IV is of heat flux ratios q_i/q_e and convective heat flux ratios, not saturated heat fluxes. Please reword to avoid confusion.
  5. [Figure 22 and elsewhere] Notation is inconsistent in places, e.g., 'GENE (s-α eq., β= 0)' is missing a space before 'β' and uses different abbreviation styles; please unify the notation for equilibria and collision operators.
  6. [Data Availability] The data availability statement says data are available 'upon reasonable request'; given the stated intention to share the simulation database, a repository link or DOI would be more suitable for reproducibility.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the central model comparison is anchored to independent GENE simulations and does not reduce to fitted inputs or self-citations.

full rationale

The paper's central claims are comparative: QuaLiKiz and TGLF-SAT2 are checked against linear and quasilinear GENE results. GENE is an independent first-principles gyrokinetic solver, and the reduced models are external to this work, so the verdict is a comparison outcome rather than an input. No parameter is fitted to the target conclusion, and no 'prediction' is constructed from the data it claims to predict. The authors developed and cite auxiliary tools (GyroKit, MEGPy, GPR methodology), but these are used for profile fitting, equilibrium parameterization, and input conversion; they do not determine whether QuaLiKiz or TGLF-SAT2 matches GENE. The paper itself reports limitations that bear on correctness or robustness, not circularity: ECE data were cut below 800 eV due to alignment mismatch, reflectometry radial positioning uncertainty is acknowledged as unaccounted for, impurity profiles were extrapolated for two discharges, Appendix E shows TGLF-SAT2 fluxes vary by 40-80% with the Miller parameterization source, and Section IV.D.2 documents wrong dominant modes at low k_y, wrong propagation directions, and up to 30% growth-rate overprediction at rho_tor=0.9. These weaken the strength of the abstract's 'agrees well' boundary statement, but they are internal evidence about agreement quality, not evidence that the derivation is equivalent to its inputs. The comparison is externally anchored and self-contained; no circular step can be exhibited.

Assumptions & free parameters 0 free parameters · 5 assumptions · 0 invented entities

The central claim rests on the validity of local linear gyrokinetic simulations as a proxy for edge turbulence and on the accuracy of the profile and equilibrium reconstruction. These are domain assumptions rather than fitted parameters. No free parameters or invented physical entities are introduced.

assumptions (5)
  • domain assumption Local flux-tube linear gyrokinetic simulations adequately represent the edge turbulence that determines L-H transition access.
    Section III A and Section V: local GENE simulations at three radii are used to infer regime changes, while global, nonlocal, and nonlinear effects are not assessed.
  • domain assumption E-cross-B flow shear can be neglected without changing the qualitative mode rankings and model assessment.
    Section III A explicitly excludes E-cross-B shear because it leads to Floquet modes in linear simulations; Section V leaves shear stabilization to future work. If shear changes dominant modes, the reduced-model verdicts could change.
  • domain assumption The GPR-fitted profiles and ESCO/JETTO equilibria are accurate enough in the steep-gradient edge.
    Section II A: ECE data were cut below 800 eV due to alignment mismatch, reflectometry radial position uncertainty is noted, and impurity profiles were extrapolated for two discharges; all of these can affect the local gradients that set the mode branches.
  • domain assumption The Sugama collision operator is adequate for the collisionality regime, and collision-operator details do not change the central model ranking.
    Section III A and Figure 14 show that switching to pitch-angle scattering removes the resistive mode branches near the plateau-Pfirsch-Schlueter boundary, so the collision model is a load-bearing choice for the rho_tor=0.95 conclusions.
  • domain assumption Saturated turbulent fluxes are well approximated by quasilinear modeling.
    Section IV A excludes nonlinear validation, and Ref. 25 challenges quasilinear validity in the edge. The heat flux comparisons use linear flux ratios rather than saturated nonlinear transport levels.

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Cite this review

Pith. "Pith review of Characterization of reduced-order turbulence models in the L-mode pedestal-forming region in JET." pith.science (2026). https://pith.science/paper/HGSQJRVD

@misc{pith2026250603459,
  author       = {Pith},
  title        = {Pith review of: Characterization of reduced-order turbulence models in the L-mode pedestal-forming region in JET},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/HGSQJRVD}},
  note         = {Machine review of arXiv:2506.03459}
}
abstract

Linear instability characterization of seven JET discharges just prior to the L-H transition is performed at $\rho_{\text{tor}} \in [0.85,0.9,0.95]$ with the gyrokinetic GENE code. The discharges cover both the low- and high-density branches of the L-H transition at two different triangularities. Sensitivities to driving gradients, normalized electron collisonality $\nu_e^*$, hydrogen isotope mass, magnetic geometry and finite-$\beta$ effects are all characterized. At $\rho_{\text{tor}}=0.85$ and $0.9$, trapped-electron modes (TEMs) propagating in both the electron- or ion-drift direction are observed at the lowest densities. At higher density ion-temperature-gradient (ITG) modes are dominant, some of which exhibit trapped-ion drive and unconventional ballooning structures. At $\rho_{\text{tor}}=0.95$, the low-density cases are similar to inner radii, while at higher densities subdominant modes are destabilized by higher collisionalities. The electron collisonality $\nu_e^*$ is scanned around the experimental values at all three radii and for the seven discharges studied. The experimental collisionality range corresponds to a region of minimum linear drive between ITG-TEM mode branches at lower collisionalities and resistive mode branches at higher collisionalities. Moreover, the quasilinear particle flux is directed inward only in the collisionality domain where the linear drive is minimized at $\rho_{\text{tor}}=0.85$ for all densities and $0.9$ only for the highest densities. Model fidelity reduction is performed on the GENE simulations to evaluate the impact of various assumptions and simplifications made by the state-of-the-art quasilinear models QuaLiKiz and TGLF. QuaLiKiz is found to be inadequate beyond $\rho_{\text{tor}}=0.85$, while TGLF-SAT2 agrees well with linear spectra and the quasilinear heat fluxes from GENE up to and including $\rho_{\text{tor}}=0.9$.

Figures

Figures reproduced from arXiv: 2506.03459 by the authors.

Figure 2
Figure 2. , but instead exhibits a minimum that separates the so-called low- and high-density branches of the L-H transition. For these discharges PL−H varied by about a factor 2, between 3.4 MW and 6.6 MW. More experi￾mental points around the minima are reported in Ref.53 . Furthermore, modification of the plasma shape also ap￾pears to impact PL−H, with larger δu resulting in a higher power threshold, consistent with previou… view at source ↗
Figure 3
Figure 3. Gaussian process regression fits of time-averaged experimental measurements (grey markers) of the (a) electron density ne (blue), (b) electron temperature Te (red) and (c) ion temperature Ti (green) of the low-density branch, low￾triangularity JET-ILW discharge #94123 (10.6-10.8s) for ρtor ∈ [0.8, 1]. High-resolution Thomson scattering (HRTS) and reflectometry data were used for ne, HRTS for Te, and impurity charge … view at source ↗
Figure 4
Figure 4. Nominal Gaussian process regression fits of time￾averaged measurements of (a) the electron density ne and (b) the electron temperature Te as functions of ρtor for both the high- (shades of blue) and low-triangularity (shades of red) JET-ILW discharges. Radial locations of interest in the pedestal-forming region ρtor ∈ [0.85, 0.90, 0.95] are indicated (vertical dashed). For the electron temperature profiles in [PITH… view at source ↗
Figures from the paper (29 more)
Figure 5
Figure 5. Figure 5: Linear GENE ion-scale spectra as function of binormal wavenumber ky at ρtor = 0.85. The linear (a, e) growth rate γ, (b, f) frequency ω, (c, g) heat flux ratio qi/qe and (d, h) convective heat flux ratio 3 2TeΓe/qe are shown for both the low- and high-density branches …
Figure 6
Figure 6. Figure 6: Linear GENE ion-scale spectra as a function of bi￾normal wavenumber ky at ρtor = 0.9. The linear (a, e) growth rate γ, (b, f) frequency ω, (c, g) heat flux ratio qi/qe and (d, h) convective heat flux ratio 3 2TeΓe/qe are shown for both the low- and high-density branche…
Figure 8
Figure 8. Figure 8: Sine of the mean cross-phase angles α between fluctuations in the electrostatic potential ϕ˜ and (a) the elec￾tron density ˜ne and (b) perpendicular electron temperature T˜e,⊥ as function of ky for #95473 at ρtor = 0.85 (crosses), ρtor = 0.9 (open symbols) and 0.95 (so…
Figure 7
Figure 7. Figure 7: Linear GENE ion-scale spectra as a function of binormal wavenumber ky at ρtor = 0.95. The linear (a, e) growth rate γ, (b, f) frequency ω, (c, g) heat flux ratio qi/qe and (d, h) convective heat flux ratio 3 2TeΓe/qe are shown for both the low- and high-density branche…
Figure 9
Figure 9. Figure 9: Linear GENE (num. eq.) ballooning representation of the normalized electrostatic potential ϕ as a function of ballooning angle θp. Mode structures for kyρs = 0.1, 0.2, 0.3 and 0.5 are shown for #95473 (a, b, c, d on top row) and #83160 (e, f, g, h on bottom row) at ρto…
Figure 10
Figure 10. Figure 10: Linear (a) growth rate γ and (b) frequency ω spectra from GENE eigenvalue simulations for #83160 at ρtor = 0.95. Insets show a truncated view (two poloidal turns centered on the outboard midplane) of multiple eigenmodes at kyρs = 0.15. 0.4 0.3 0.2 0.1 0.0 0.1 0.2 0.3 …
Figure 12
Figure 12. Figure 12: From top to bottom: the linear (a, b, c) growth rate γ, (d, e, f) mode frequency ω, (g, h, i) heat flux ratio qi/qe and (j, k, l) convective heat flux ratio 3 2TeΓe/qe as functions of normalized electron collision frequency ν ∗ e for kyρs = 0.2 at three radial positio…
Figure 13
Figure 13. Figure 13: Linear growth rates γ as function of normal￾ized electron collisionality ν ∗ e for kyρs = 0.2 in #83160 at ρtor = 0.9. The growth rate is split into contributions by terms in the linear gyrokinetic equation to the electrostatic￾potential part of the free-energy balanc…
Figure 14
Figure 14. Figure 14: The effect of the collision operator on the linear (a) growth rate γ, (b) frequency ω and weighted cross-phase angles between (c) ϕ˜ and ˜ne and (d) ϕ˜ and T˜e,⊥ of the domi￾nant mode at kyρs = 0.2 as a function of normalized electron collisionality ν ∗ e for #83160 a…
Figure 15
Figure 15. Figure 15: The derivative of the linear growth rate γ with respect to the normalized electron collisionality ν ∗ e , from GENE simulations with numerical equilibria and Sugama collision operator for all seven discharges, as a function of ky at (a) ρtor = 0.85, (b) ρtor = 0.9 and…
Figure 16
Figure 16. Figure 16: The linear (a) growth rate γ and (b) frequency ω of the dominant mode at kyρs = 0.2 as functions of both normalized electron collisionality ν ∗ e and a/Lne for #83157 at ρtor = 0.95. The nominal experimental values of both ν ∗ e and a/Lne are indicated as dashed lines…
Figure 17
Figure 17. Figure 17: The effect of isotope mass on the linear spectra from GENE simulations with numerical equilibrium, where hydrogen (red) and tritium (purple) are compared to deuterium. The ratio of the linear growth rates for isotopes and deuterium γisotope/γD as a function of ky for …
Figure 18
Figure 18. Figure 18: The effect of the effective charge Zeff on the lin￾ear growth rate γ of the dominant mode at kyρs = 0.2 as a function of normalized electron collisionality ν ∗ e for #83160 at ρtor = 0.95 in GENE simulations with numerical equilibrium. Results at the nominal Zeff and …
Figure 19
Figure 19. Figure 19: Comparison between the growth rates γ times the sign of the corresponding mode frequencies ω from lin￾ear, electrostatic GENE simulations using s-α equilibria and numerical equilibria for all seven JET discharges at three ra￾dial positions (symbols) and (kyρs)num. eq.…
Figure 20
Figure 20. Figure 20: Comparison of the linear (a, b, c) growth rates γ times sign of the mode frequencies ω, (d, e, f) heat flux ratio qi/qe and (g, h, i) convective heat flux ratio 3 2TeΓe/qe from QuaLiKiz (QLK) and linear, electrostatic GENE simulations using s-α equilibria and a Sugama…
Figure 21
Figure 21. Figure 21: Comparison between the growth rates γ times the sign of the corresponding mode frequencies ω from QuaLiKiz (QLK) and linear, electrostatic GENE simulations using numerical equilibria and a Sugama collision operator for all seven JET discharges (symbols) at three radia…
Figure 22
Figure 22. Figure 22: QuaLiKiz linear (a) growth rates γ and (b) mode frequencies ω for #95473 at ρtor = 0.95. Various settings for the Krook collision operator in QuaLiKiz (QLK) are com￾pared against the linear spectra from GENE (s-α eq., β = 0). C.3 Effect of collisionality in QuaLiKiz I…
Figure 23
Figure 23. Figure 23: Comparison of the linear (a, b, c) growth rates γ times sign of the mode frequencies ω, (d, e, f) heat flux ratio qi/qe and (g, h, i) convective heat flux ratio 3 2TeΓe/qe from TGLF-SAT2 against local linear, electromagnetic GENE simulations using Miller geometry for …
Figure 24
Figure 24. Figure 24: TGLF-SAT2 (Miller eq., electromagnetic) ballooning representation of the normalized electrostatic potential ϕ as a function of ballooning angle θp, centered at the outboard midplane. Mode structures for (kyρs)num. eq. = 0.1, 0.2, 0.3 and 0.5 are shown for #95473 (a, b…
Figure 25
Figure 25. Figure 25: Comparison of the growth rate γ times sign of the mode frequency ω from TGLF-SAT2 against the values from linear, electromagnetic GENE simulations using Miller geometry for all seven JET discharges at ρtor = 0.95 and (kyρs)num. eq. ∈ [0.05, 1] with the pitch-angle sca…
Figure 26
Figure 26. Figure 26: Comparison of the linear growth rate and frequency as a function of a/Lne and a/LTe between GENE (num. eq., Sugama) in the left two columns and TGLF-SAT2 (Miller, PAS) in the right two columns. Separate color scales are used for the GENE and TGLF-SAT2 growth rates for…
Figure 27
Figure 27. Figure 27: A comparison between TGLF-SAT2 (vertical) and GENE (horizontal) of the derivative of the linear growth rate with respect to the dimensionless electron collisionality ∂γ/∂ν∗ e for (kyρs)num. eq. ∈ [0.1, 0.2, 0.3, 0.5, 0.7, 0.9] at (a) ρtor = 0.85, (b) ρtor = 0.9 and (c…
Figure 28
Figure 28. Figure 28: Linear (a) growth rates and (b) mode frequencies from TGLF-SAT2 as a function of ν ∗ e , for all seven discharges, for (kyρs)num. eq. = 0.2 at ρtor = 0.95. not lead to better matches for the mode branches dom￾inant in the GENE simulations. The divergence is also not r…
Figure 29
Figure 29. Figure 29: A comparison of the ratio of the linear growth rates for hydrogen (shades of red) and tritium (shades of purple) with deuterium γisotope/γD between GENE (num. eq., Sugama) and TGLF-SAT2 for kyρs ∈ [0.05, 1] at three different radii (from left to right). sitivity of th…
Figure 30
Figure 30. Figure 30: Gaussian process regression fits of time-averaged experimental measurements (grey markers) of the (a) electron density ne (blue), (b) electron temperature Te (red) and (c) ion temperature Ti (green) near the edge of the plasma, ρtor ∈ [0.8, 1], for #83164, #83157, #83…
Figure 31
Figure 31. Figure 31: Linear gene electron-scale spectra as a function of binormal wavenumber kyρs at ρtor = 0.85, 0.9, 0.95. From top to bottom the linear (a) growth rate γ, (b) frequency ω, (c) heat flux ratio qi/qe and (d) convective heat flux ratio 3 2TeΓe/qe are shown for both high (c…
Figure 32
Figure 32. Figure 32: For a few cases a change in mode propagation direction is shifted to slightly higher kyρs. Additionally for the weakly resistive, ℓ=1 ion-direction instabilities, dominant at low kyρs on the high ¯ne branch, both the heat flux and convective heat flux ratios increase …
Figure 33
Figure 33. Figure 33: The linear (a) growth rate γ and (b) frequency ω for the instabilities found at kyρs = 0.2 for #83164 at ρtor = 0.95 as a function of β in percent. The nominal values based on the fit of the experimental data (blue circle) are indicated on the left. Around the expecte…
Figure 34
Figure 34. Figure 34: The relative difference in the TGLF-SAT2 heat and particle fluxes in percent when changing the shape pa￾rameters from FLUSH to MEGPy for ρtor ∈ [0.85, 0.9, 0.95]. (Turnbull-)Miller parameterizations of the local equilib￾rium were generated for #83164 and #95473 with t…

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Reviewed August 7, 2026 · model on record in the stance chip above.