Pith. sign in

REVIEW 3 major objections 5 minor 34 references

Identification and Characterization of a New Disruption Regime in ADITYA-U Tokamak

T0 review · 3 major / 5 minor · reviewed 2026-08-06 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗ Review JSON

Pith's one-line read The paper identifies a new disruption class in the ADITYA-U tokamak, Accelerated Mode Disruption, distinguished by a rising (2,1) drift-tearing-mode frequency followed by a sudden frequency collapse and a faster, more intense current…

desk verdict Plausible new disruption class, but the reported thresholds are built on a classification rule the paper never states; needs major revision before the quantitative claims can be trusted. read the letter →

arxiv 2507.17299 v1 pith:GKTJLSWX submitted 2025-07-23 physics.plasm-ph

Soumitra Banerjee , Harshita Raj , Sk Injamul Hoque , Komal Yadav , Sharvil Patel , Ankit Kumar , Kaushlender Singh , Ashok Kumawat
show 17 more authors
Bharat Hegde Subhojit Bose Priyanka Verma Kumudini Tahiliani Asha Adhiya Manoj Kumar Rohit Kumar Malay Bikash Chowdhuri Nilam Ramaiya Ananya Kundu Suman Aich Suman Dolui K. A. Jadeja K.M. Patel Ankit Patel Rakesh L. Tanna Joydeep Ghosh
This is my paper · ORCID
classification physics.plasm-ph PACS 52.55.Fa
keywords AcceleratedModeDisruptionLockeddrift-tearingtokamakcurrentquenchedgesafetyfactortemperaturehollowingADITYA-U
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 claims that a sizeable fraction of disruptions in ADITYA-U form a distinct class, called Accelerated Mode Disruption (AMD), separate from the familiar Locked Mode Disruption (LMD). In AMD the precursor instability accelerates: the (2,1) drift-tearing mode frequency rises steadily while the amplitude nonlinearly saturates, and only then does the frequency collapse as the island expands and the discharge disrupts. A statistical study of 150 discharges separates the two classes with empirical thresholds: edge safety factor above 4.3, plasma current decay above 16%, current quench time below 1.5 ms, and quench rate above 56 MA/s mark AMD. The proposed mechanism is core radiation and temperature hollowing, which steepens the pressure and current-density gradients near the q=2 surface and destabilizes the drift-tearing mode. If this class is real, disruption prediction and mitigation systems would need a separate trigger for frequency-rising precursors, because AMD quenches faster and is more damaging than LMD.

What carries the argument

The carrying object is the (m/n = 2/1) drift-tearing mode (DTM), the coupled tearing-drift instability that is the sole dominant mode in AMD discharges. Its frequency is decomposed as $f_{\rm MHD} = \frac{m}{2\pi r B_\varphi}\frac{\nabla p_e}{e n_e} + \frac{n v_\varphi}{2\pi R_0} + \frac{m v_\theta}{2\pi r}$ at the rational surface; for shot #37103 the diamagnetic term contributes about 7.8 kHz of a 10 kHz frequency, with toroidal flow about 1.7 kHz and poloidal flow about 0.5 kHz. The mechanism this equation encodes is the paper's central explanation: a rising pressure gradient near the rational surface is what accelerates the mode, and the same core-temperature-hollowing that steepens that gradient also destabilizes the mode and triggers the quench. The empirical separators, $q_{\rm edge} > 4.3$ and greater than 16% current decay, locate the q=2 surface and the current-profile evolution that set AMD apart from LMD.

What would settle it

Take the same 150 discharges, mask the labels, and have two independent analysts classify each shot by a pre-specified rule (for example, the sign of the linear slope of the dominant Mirnov frequency during the 10 ms before the thermal quench, or a threshold on the frequency rise). If the sharp boundaries at $q_{\rm edge}=4.3$, 16% current decay, 1.5 ms quench time, and 56 MA/s do not reappear, the AMD/LMD separation is an artifact of the labelling procedure. A complementary check is to find a single discharge with a clear rising-frequency precursor but a current quench longer than 1.5 ms, which would break the claimed correspondence.

Watch

Extended reading notes

Core claim

The central claim is that ADITYA-U hosts a previously unrecognized disruption regime, Accelerated Mode Disruption, whose precursor differs from locked-mode behavior: instead of the mode slowing toward locking, the (2,1) drift-tearing mode shows a sustained frequency rise while its magnetic island width stays roughly 4–5 cm, followed by an abrupt frequency drop and island expansion immediately before the thermal quench. The paper derives statistical boundaries between AMD and LMD from 150 discharges: 73% of AMDs occur for $q_{\rm edge} > 4.3$ while 80% of LMDs occur below that value, and a plasma current decay greater than 16% from maximum gives a 75% chance of AMD. AMD current quenches are shorter than 1.5 ms and faster than 56 MA/s, making them more hazardous than LMD. Physically, the paper attributes AMD to core radiation and hollowing of the temperature profile, which flattens or hollows the current profile and steepens both the current-density and pressure gradients near the q=2 rational surface, driving the dominant (2,1) drift-tearing mode; roughly 78% of the observed frequency rise is assigned to the diamagnetic pressure-gradient term.

Load-bearing premise

The entire statistical separation rests on the assumption that the 150 discharges were sorted into AMD and LMD by a consistent and unbiased reading of the precursor frequency trend; the paper gives no quantitative, pre-specified sorting rule, so the empirical thresholds could partly be a product of the sorting.

Editorial extensions

If this is right

  • Disruption prediction systems that rely on mode locking as the warning sign will miss AMD until very late; a rising (2,1) mode frequency with saturated amplitude is itself an early precursor.
  • Real-time monitors using $q_{\rm edge}$ and the current decay coefficient can flag high-risk shots: values above 4.3 and above 16% decay point to the faster AMD class.
  • Because AMD current quenches are shorter than 1.5 ms and faster than 56 MA/s, mitigation actuators for ADITYA-U must be able to react on or before the frequency-collapse phase, not after locking.
  • The DTM frequency at the disruption onset correlates with quench duration, so the precursor frequency rise is not just a label but a severity measure.
  • A planned mitigation framework on ADITYA-U would combine software predictions with hardware actuators keyed to $q_{\rm edge}$, current decay, and DTM frequency.

Reading between the lines

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

  • Extension, not the paper's claim: the frequency slope during the precursor could serve as a continuous danger score, with faster rises predicting shorter quench times; the paper's correlation between final frequency and quench time supports this but does not test it directly.
  • Extension, not the paper's claim: if the $q_{\rm edge} > 4.3$ boundary reflects the position of the q=2 surface near the plasma edge, then similar AMD-like events should appear in other small and medium tokamaks operated at high edge safety factor with core radiation; this is testable with existing multi-device disruption records.
  • Extension, not the paper's claim: a practical predictor could classify AMD using only Mirnov frequency slope and soft-X-ray core hollowing, avoiding the need for full equilibrium reconstruction; the paper's diagnostics show both signals change early, but it does not test such a classifier.
Share X Bluesky LinkedIn Reddit HN

Signed reviews

No signed human review yet.

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 5 minor

Summary. The paper reports the identification of a new disruption regime in the ADITYA-U tokamak, termed Accelerated Mode Disruption (AMD), and contrasts it with conventional Locked Mode Disruption (LMD). The distinguishing signature is a precursor phase with a steadily rising mode frequency and nonlinearly saturated amplitude, followed by a sudden frequency collapse and amplitude growth. A statistical analysis of 150 discharges is claimed to yield empirical thresholds in edge safety factor (q_edge > 4.3), normalized current decay coefficient (>16%), current quench time (<1.5 ms), and current quench rate (>56 MA/s) that separate AMD from LMD. The paper further proposes that core temperature hollowing causes steepening of pressure and current density gradients near the 2/1 rational surface, destabilizing the drift-tearing mode and producing the observed frequency behavior.

Significance. If substantiated, the existence of a distinct disruption class with faster and more dangerous current quenches would be valuable for disruption prediction and mitigation, particularly for future devices. The paper leverages a reasonably large dataset (150 discharges) and multiple diagnostics (Mirnov coils, SXR, bolometry, Langmuir probes), and the primary classification signal (rising versus decaying precursor frequency) is in principle independent of the variables used for the reported thresholds. These are notable strengths. However, the quantitative support is currently inadequate: the classification rule is not specified in a reproducible way, the thresholds lack error bars, and the mechanism section contains circular reasoning and a unit inconsistency. The paper's central claim is therefore not yet convincingly established, but it is potentially salvageable with a thorough revision.

major comments (3)
  1. [Sec. 3.1-3.2] The classification rule used to label the 150 discharges as AMD or LMD is not specified. The text describes AMD as exhibiting 'a steady rise in mode frequency with a nonlinearly saturated amplitude' (Sec. 3.1), but it does not define a quantitative criterion: no time window, frequency slope threshold, amplitude saturation level, or analysis method is given. The inclusion and exclusion criteria for the 150-shot sample, the shot list, and any inter-rater or independent diagnostic checks are also absent. Because the statistical thresholds in Sec. 3.2 (q_edge > 4.3, current decay > 16%) are computed on this manually labeled sample, they may be artifacts of the labeling procedure rather than independent physical boundaries. Please provide an explicit, reproducible classification algorithm or detailed quantitative criteria, and re-derive the thresholds with confidence intervals.
  2. [Sec. 6] The claim that the electron pressure gradient dominates the DTM frequency is circular. The diamagnetic contribution of 7.8 kHz is obtained as the residual after subtracting the flow contributions (1.7 kHz toroidal and 0.5 kHz poloidal) from the measured total frequency of approximately 10 kHz (Sec. 5); it is not an independent measurement of a pressure-gradient-driven term. Using that residual to conclude that 'the pressure gradient near the mode rational surface plays a dominant role' (Sec. 5) is reasoning in a circle. Furthermore, the calculation in the bullet list is dimensionally inconsistent: the text first states that ∇p_e should be 2×10^4 Pa/m, but then writes '∇p_e = ∇(n_e T_e) = 2.6×10^4 / 1.6×10^-19 = 1.625×10^23 Pa/m', which is not a valid pressure-gradient computation. Please correct the unit errors and either provide an independent measurement of the pressure gradient or explicitly frame the 7.8 kHz value as a consistency check rather than as evidence for the mechanism.
  3. [Sec. 5-6] The analysis relies on an assumed current density profile J ~ (1-(r/a)^2)^α with α=3 (Sec. 5), but no justification or sensitivity study is provided. The location of the rational surface r_s ≈ 0.12 m for shot #37103, the computed island width, and the frequency decomposition in Sec. 5 all depend on this assumption. Since the interpretation of the mode as a 2/1 drift-tearing mode and the subsequent mechanism discussion hinge on r_s, please provide a sensitivity analysis over reasonable α values or cite a direct constraint on the current density profile from the ADITYA-U diagnostics.
minor comments (5)
  1. [Sec. 3.3] The text states 'Figure 3 presents the statistical analysis of these parameters across 150 disruptive shots', but the actual figures showing current quench time and rate are Fig. 4(a) and 4(b). Please correct the cross-reference.
  2. [Sec. 6] The text refers to 'Figure 5' and 'Figure 6' for the bolometer radiation profiles and chord-averaged temperature, but these data are displayed in Fig. 10(a) and 10(b). Please correct the figure citations.
  3. [Sec. 7] The summary contains a duplicated phrase: 'Through a comprehensive Through a comprehensive statistical study'. Please fix the typo.
  4. [Sec. 3.1] For shot #37103, the text states that the Mirnov signal shows 'a characteristic 50% increase in frequency', but the described frequency range is 7-15 kHz, which is more than a 100% increase. Please clarify the metric used for the percentage change.
  5. [Sec. 6] The paper refers to 'line-averaged temperature' estimated from SXR signals; SXR diagnostics measure line-integrated emissivity, and the temperature inference is indirect (via foil-filter ratios, as noted in Sec. 2). Please use the correct terminology and explain the inversion method.

Circularity Check

1 steps flagged · score 6.0 of 10

The empirical AMD/LMD separation is not circular, but the mechanistic claim that a pressure-gradient-driven diamagnetic term dominates is constructed from the residual after subtracting flow terms.

  1. self definitional [Section 5 (frequency decomposition) and Section 6 (required pressure gradient)]
    "With this in mind, by incorporating these values into the final equation, the term that contributes the maximum is m/(2πrBφ) ∇p_e/(e n_e)=7.8 kHz. Approximately 22% of the increase in Drift-Tearing Mode (DTM) frequency can be attributed to the combined effects of toroidal and poloidal plasma flows, while the remaining contribution primarily arises from the diamagnetic term. ... For the observed DTM frequency of 7.8 kHz, the relation ... suggests that the required electron pressure gradient ∇p_e should be 2×10^4 Pa/m."

    The 7.8 kHz diamagnetic contribution is not an independent measured quantity: it is computed as the arithmetic residual from the measured total frequency after subtracting the estimated flow terms (10 kHz − 1.7 kHz − 0.5 kHz) using the decomposition in Eq. (3). The paper then treats this residual as evidence that the pressure gradient dominates and derives the 'required' pressure gradient of 2×10^4 Pa/m from it. Because the diamagnetic term is by construction the leftover after subtracting the flow terms, the conclusion that pressure-gradient effects dominate and drive the frequency increase is guaranteed by the subtraction itself. No independent measurement of ∇p_e is presented to validate the inferred steep gradient.

full rationale

The central regime identification is not circular: AMD and LMD are labeled in Sec. 3.1 by the sign of the precursor-mode frequency trend (rising versus decaying), which is independent of the downstream statistical thresholds (q_edge, current-decay coefficient, CQ time/rate). The reported cluster separation is therefore an empirical summary of an independently labeled sample, even though the labeling rule is qualitative and not pre-registered. That is a reproducibility/validity concern, not a circularity. No load-bearing uniqueness theorem or self-citation chain is invoked: the frequency formula is attributed to an external J-TEXT paper, and the analogous JET observations [9] are an external comparison. The one genuinely circular element is the mechanistic attribution in Secs. 5-6: the diamagnetic term is defined as the measured frequency minus the estimated flow terms, so the statement that it dominates, and the required pressure gradient of 2×10^4 Pa/m, are both constructed from that residual. The paper then uses these as evidence for localized pressure steepening. That sub-claim reduces by construction to the input data. The score of 6 reflects partial circularity in the mechanism, while the empirical AMD/LMD distinction retains independent content.

Assumptions & free parameters 3 free parameters · 4 assumptions · 0 invented entities

The paper's central claims rest on three categories of uncharged inputs: an assumed current density profile (alpha=3) used to locate the rational surface, standard MHD frequency decomposition, and a classification of 150 discharges into AMD/LMD whose labeling rule is not quantitatively specified. The pressure-gradient mechanism further relies on a residual-computed frequency term rather than an independent measurement. No new physical entities are introduced; Accelerated Mode Disruption is an observational category, not a postulated particle, force, or conserved quantity.

free parameters (3)
  • Current density profile exponent alpha = 3
    Assumed in Sec 5 as J ~ (1-(r/a)^2)^alpha; determines q(r), the rational surface radius (0.12 m for shot #37103) and the island width estimate. Not measured or justified for ADITYA-U.
  • Diamagnetic frequency contribution = 7.8 kHz
    Computed in Sec 4 as the measured DTM frequency (10 kHz) minus estimated toroidal flow (1.7 kHz) and poloidal flow (0.5 kHz) terms. This residual is then used in Sec 6 to infer a pressure gradient of 2e4 Pa/m, so it functions as a fitted value rather than an independent measurement.
  • AMD/LMD separation cutoffs = q_edge=4.3, current decay=16%, CQ time=1.5 ms, CQ rate=56 MA/s
    These cutoffs are derived post hoc from the 150-shot sample after classifying shots as AMD or LMD. They are presented as empirical findings, but they also serve as the operational definition of the new regime and lack uncertainty estimates.
assumptions (4)
  • domain assumption Current density profile has the form J ~ (1-(r/a)^2)^3 and the safety factor follows Eq. (1).
    Invoked in Sec 5 to locate the q=2 rational surface and compute island width; the profile is not measured by MSE or polarimetry in this paper.
  • domain assumption The MHD frequency is the sum of diamagnetic, toroidal flow, and poloidal flow terms as in Eq. (3).
    This standard relation from Ref. [35] is used to decompose the observed frequency; it assumes mode rotation follows the electron diamagnetic direction and that flows are separable.
  • domain assumption Temperature hollowing and current flattening destabilize the 2/1 tearing mode via steep gradients near the rational surface.
    The mechanism is borrowed from JET termination studies [9] and classical tearing mode theory; the paper does not derive it from first principles or test it with stability calculations.
  • domain assumption The discharges analyzed in the 150-shot sample are representative and the AMD/LMD labels are assigned correctly.
    The classification rule is described qualitatively in Sec 3.1 (rising vs decaying frequency) but no quantitative, pre-registered criterion, inter-rater check, or exclusion list is given.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Identification and Characterization of a New Disruption Regime in ADITYA-U Tokamak." pith.science (2026). https://pith.science/paper/GKTJLSWX

@misc{pith2026250717299,
  author       = {Pith},
  title        = {Pith review of: Identification and Characterization of a New Disruption Regime in ADITYA-U Tokamak},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/GKTJLSWX}},
  note         = {Machine review of arXiv:2507.17299}
}
read the original abstract

Disruptions continue to pose a significant challenge to the stable operation and future design of tokamak reactors. A comprehensive statistical investigation carried out on the ADITYA-U tokamak has led to the observation and characterization of a novel disruption regime. In contrast to the conventional Locked Mode Disruption (LMD), the newly identified disruption exhibits a distinctive two-phase evolution: an initial phase characterized by a steady rise in mode frequency with a nonlinearly saturated amplitude, followed by a sudden frequency collapse accompanied by a pronounced increase in amplitude. This behaviour signifies the onset of the precursor phase on a significantly shorter timescale. Clear empirical thresholds have been identified to distinguish this disruption type from conventional LMD events, including edge safety factor, current decay coefficient, current quench (CQ) time, and CQ rate. The newly identified disruption regime is predominantly governed by the (m/n = 2/1) drift-tearing mode (DTM), which, in contrast to typical disruptions in the ADITYA-U tokamak that involve both m/n = 2/1 and 3/1 modes, consistently manifests as the sole dominant instability. Initiated by core temperature hollowing, the growth of this mode is significantly enhanced by a synergistic interplay between a strongly localized pressure gradient and the pronounced steepening of the current density profile in the vicinity of the mode rational surface.

Figures

Figures reproduced from arXiv: 2507.17299 by the authors.

Figure 1
Figure 1. Temporal evolution of key plasma parameters for representative discharges of two disruption types in Aditya-U : Accelerated Mode Disruption (AMD) discharge #37103, showing plasma current (Ip), loop voltage (V), magnetic activity (MHD), and soft X-ray (SXR) signals(a). Disruption characteristics are inferred from variations in loop-voltage, SXR intensity, Ip decay(b), MHD amplitude(c) and frequency (d); Locked Mode D… view at source ↗
Figure 2
Figure 2. Plasma current characterization for the disruptive discharges analyzed in this study To quantify the current quench (CQ) phase, 𝐼𝑝𝑑90 and 𝐼𝑝𝑑10 are defined as the plasma current levels corresponding to 90% and 10% of the pre-disruptive plasma current (𝐼𝑝𝑑) value. The duration of this CQ interval is influenced by the eddy currents induced in the conductive structures of the vacuum vessel during the current quench pha… view at source ↗
Figure 3
Figure 3. (a) Edge safety factor (𝑞𝑒𝑑𝑔𝑒) evaluated at the disruption onset current (Ipd) for AMD and LMD cases, against shot labels (b) Statistical data of the current decay coefficient(Z) for AMD and LMD discharges with shot label [PITH_FULL_IMAGE:figures/full_fig_p007_3.png] view at source ↗
Figures from the paper (7 more)
Figure 4
Figure 4. Figure 4: (a) Current quench time for AMD & LMD discharges (b) Current quench rate for AMD & LMD discharges [PITH_FULL_IMAGE:figures/full_fig_p008_4.png]
Figure 5
Figure 5. Figure 5: (a) DTM frequency as a function of edge safety factor (𝑞 [PITH_FULL_IMAGE:figures/full_fig_p009_5.png]
Figure 6
Figure 6. Figure 6: CQ time against DTM Frequency A clear correlation between CQ time and DTM frequency at the time corresponding to 𝐼𝑝𝑑, underscoring their mutual dependence, as shown in [PITH_FULL_IMAGE:figures/full_fig_p010_6.png]
Figure 7
Figure 7. Figure 7: (a) Time vector of Mirnov Signal (b) Spatial mode structure extracted using the Singular Value Decomposition (SVD) technique (c) Spectrogram showing the time evolution of mode frequency before and during the disruption phase (d) Estimated magnetic island width associat…
Figure 8
Figure 8. Figure 8: Toroidal flow speed of plasma rotation To further quantify the contribution of toroidal rotation to the total DTM frequency, the second term, representing the toroidal flow component, is calculated. This analysis allows for an assessment of the extent to which the back…
Figure 9
Figure 9. Figure 9: Time evolution of radial E-field during frequency increase (AMD) Subsequently, the third term, corresponding to the contribution of the poloidal flow to the total DTM frequency, is evaluated to quantify its role in the overall mode dynamics. 𝑚𝑣𝜃 2𝜋𝑟 = 𝑚 2𝜋𝑟 ( 𝐸𝑟 𝐵𝜑 ) =…
Figure 10
Figure 10. Figure 10: (a)Bolometer radiation emission profile (b) Temperature evolution with time for AMD and chord average temperature with chord position As previously discussed, disruptions similar to AMD have also been reported in the JET tokamak during the plasma current termination p…

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

34 extracted references · 29 canonical work pages

  1. [1]

    Effects of an electrically conducting first wall on the blanket loading during a Tokamak plasma disruption,

    T. Jordan and D. Schneider, “Effects of an electrically conducting first wall on the blanket loading during a Tokamak plasma disruption,” Fusion Engineering and Design, vol. 31, no. 4, pp. 313–321, Aug. 1996, doi: 10.1016/0920-3796(96)00526-1

    work page doi:10.1016/0920-3796(96)00526-1 1996

  2. [2]

    Parsimonious statistical techniques for the detection of drifts toward dangerous operational conditions in tokamaks,

    T. Craciunescu, A. Murari, on behalf of JET Contributors, and the EUROfusion Tokamak Exploitation Team, “Parsimonious statistical techniques for the detection of drifts toward dangerous operational conditions in tokamaks,” Plasma Phys. Control. Fusion, vol. 66, no. 9, p. 095008, Sep. 2024, doi: 10.1088/1361-6587/ad670a

    work page doi:10.1088/1361-6587/ad670a 2024

  3. [3]

    Disruptions in tokamaks,

    F. C. Schuller, “Disruptions in tokamaks,” Plasma Phys. Control. Fusion, vol. 37, no. 11A, pp. A135–A162, Nov. 1995, doi: 10.1088/0741-3335/37/11A/009

    work page doi:10.1088/0741-3335/37/11a/009 1995

  4. [4]

    Disruptions and Plasma Current Asymmetries in Tokamak Plasmas

    E. Matveeva, J. Havlıˇcek, O. Hronova, V . Weinzettl, and A. Havranek, “Disruptions and Plasma Current Asymmetries in Tokamak Plasmas”

    work page

  5. [5]

    Vertical displacement events: A serious concern in future ITER operation,

    A. Hassanein, T. Sizyuk, and M. Ulrickson, “Vertical displacement events: A serious concern in future ITER operation,” Fusion Engineering and Design, vol. 83, no. 7–9, pp. 1020–1024, Dec. 2008, doi: 10.1016/j.fusengdes.2008.05.032

    work page doi:10.1016/j.fusengdes.2008.05.032 2008

  6. [6]

    A new look at density limits in tokamaks,

    M. Greenwald et al., “A new look at density limits in tokamaks,” Nucl. Fusion, vol. 28, no. 12, pp. 2199–2207, Dec. 1988, doi: 10.1088/0029-5515/28/12/009

    doi:10.1088/0029-5515/28/12/009 1988

  7. [8]

    Characterization of the plasma current quench during disruptions in ADITYA tokamak,

    S. Purohit et al., “Characterization of the plasma current quench during disruptions in ADITYA tokamak,” Nucl. Fusion, vol. 60, no. 12, p. 126042, Dec. 2020, doi: 10.1088/1741-4326/abb79c. 19

    work page doi:10.1088/1741-4326/abb79c 2020

  8. [9]

    Onset of tearing modes in plasma termination on JET: the role of temperature hollowing and edge cooling,

    G. Pucella et al., “Onset of tearing modes in plasma termination on JET: the role of temperature hollowing and edge cooling,” Nucl. Fusion, vol. 61, no. 4, p. 046020, Apr. 2021, doi: 10.1088/1741-4326/abe3c7

    work page doi:10.1088/1741-4326/abe3c7 2021

Show all 34 references
  1. [10]

    The study of heat flux for disruption on experimental advanced superconducting tokamak,

    Z. Yang et al., “The study of heat flux for disruption on experimental advanced superconducting tokamak,” Physics of Plasmas, vol. 23, no. 5, p. 052502, May 2016, doi: 10.1063/1.4948494

    2016 doi

  2. [11]

    Characteristics of current quenches during disruptions in the J-TEXT tokamak,

    Y . Zhang et al., “Characteristics of current quenches during disruptions in the J-TEXT tokamak,” Phys. Scr., vol. 86, no. 2, p. 025501, Aug. 2012, doi: 10.1088/0031- 8949/86/02/025501

    2012 doi

  3. [12]

    MHD spectrogram contribution to disruption prediction using Convolutional Neural Networks,

    E. Aymerich, G. Sias, S. Atzeni, F. Pisano, B. Cannas, and A. Fanni, “MHD spectrogram contribution to disruption prediction using Convolutional Neural Networks,” Fusion Engineering and Design, vol. 204, p. 114472, Jul. 2024, doi: 10.1016/j.fusengdes.2024.114472

    2024

  4. [13]

    Deep sequence to sequence learning-based prediction of major disruptions in ADITYA tokamak,

    A. Agarwal et al., “Deep sequence to sequence learning-based prediction of major disruptions in ADITYA tokamak,” Plasma Phys. Control. Fusion, vol. 63, no. 11, p. 115004, Nov. 2021, doi: 10.1088/1361-6587/ac234c

    2021 doi

  5. [14]

    Disruption prediction using a full convolutional neural network on EAST,

    B. H. Guo et al., “Disruption prediction using a full convolutional neural network on EAST,” Plasma Phys. Control. Fusion, vol. 63, no. 2, p. 025008, Feb. 2021, doi: 10.1088/1361-6587/abcbab

    2021 doi

  6. [15]

    CNN disruption predictor at JET: Early versus late data fusion approach,

    E. Aymerich, G. Sias, F. Pisano, B. Cannas, A. Fanni, and the-JET-Contributors, “CNN disruption predictor at JET: Early versus late data fusion approach,” Fusion Engineering and Design, vol. 193, p. 113668, Aug. 2023, doi: 10.1016/j.fusengdes.2023.113668

    2023

  7. [16]

    In-depth research on the interpretable disruption predictor in HL-2A,

    Z. Yang, F. Xia, X. Song, Z. Gao, S. Wang, and Y . Dong, “In-depth research on the interpretable disruption predictor in HL-2A,” Nucl. Fusion, vol. 61, no. 12, p. 126042, Dec. 2021, doi: 10.1088/1741-4326/ac31d8

    2021 doi

  8. [17]

    The ITPA disruption database,

    N. W. Eidietis et al., “The ITPA disruption database,” Nucl. Fusion, vol. 55, no. 6, p. 063030, Jun. 2015, doi: 10.1088/0029-5515/55/6/063030

    2015 doi

  9. [18]

    Drift-tearing modes in a tokamak plasma,

    D. Biskamp, “Drift-tearing modes in a tokamak plasma,” Nucl. Fusion, vol. 18, no. 8, pp. 1059–1068, Aug. 1978, doi: 10.1088/0029-5515/18/8/003

    1978 doi

  10. [19]

    Effect of periodic gas-puffs on drift-tearing modes in ADITYA/ADITYA- U tokamak discharges,

    H. Raj et al., “Effect of periodic gas-puffs on drift-tearing modes in ADITYA/ADITYA- U tokamak discharges,” Nucl. Fusion, vol. 60, no. 3, p. 036012, Mar. 2020, doi: 10.1088/1741-4326/ab6810

    2020 doi

  11. [20]

    Drift-tearing magnetic islands in tokamak plasmas,

    R. Fitzpatrick and F. L. Waelbroeck, “Drift-tearing magnetic islands in tokamak plasmas,” Physics of Plasmas, vol. 15, no. 1, p. 012502, Jan. 2008, doi: 10.1063/1.2829757

    2008 doi

  12. [21]

    Controlling the rotation of drift tearing modes by biased electrode in ADITYA-U tokamak,

    T. Macwan et al., “Controlling the rotation of drift tearing modes by biased electrode in ADITYA-U tokamak,” Physics of Plasmas, vol. 28, no. 11, p. 112501, Nov. 2021, doi: 10.1063/5.0059410

    2021 doi

  13. [22]

    Mode rotation control in a tokamak with a feedback-driven biased electrode,

    J. W. Brooks, I. G. Stewart, M. D. Boyer, J. P. Levesque, M. E. Mauel, and G. A. Navratil, “Mode rotation control in a tokamak with a feedback-driven biased electrode,” Review of Scientific Instruments, vol. 90, no. 2, p. 023503, Feb. 2019, doi: 10.1063/1.5062271

    2019 doi

  14. [23]

    Effect of electrode biasing on m/n = 2/1 tearing modes in J-TEXT experiments,

    H. Liu et al., “Effect of electrode biasing on m/n = 2/1 tearing modes in J-TEXT experiments,” Nucl. Fusion, vol. 57, no. 1, p. 016003, Jan. 2017, doi: 10.1088/0029- 5515/57/1/016003

    2017 doi

  15. [24]

    In-vessel saddle coils for MHD control in ASDEX Upgrade,

    W. Suttrop et al., “In-vessel saddle coils for MHD control in ASDEX Upgrade,” Fusion Engineering and Design, vol. 84, no. 2–6, pp. 290–294, Jun. 2009, doi: 10.1016/j.fusengdes.2008.12.044

    2009 doi

  16. [25]

    Mode locking in tokamaks,

    M. F. F. Nave and J. A. Wesson, “Mode locking in tokamaks,” Nucl. Fusion, vol. 30, no. 12, pp. 2575–2583, Dec. 1990, doi: 10.1088/0029-5515/30/12/011. 20

    1990 doi

  17. [26]

    Nonlinear saturation of resistive tearing modes in a cylindrical tokamak with and without solving the dynamics,

    J. Loizu and D. Bonfiglio, “Nonlinear saturation of resistive tearing modes in a cylindrical tokamak with and without solving the dynamics,” J. Plasma Phys., vol. 89, no. 5, p. 905890507, Oct. 2023, doi: 10.1017/S0022377823000934

    2023 doi

  18. [27]

    Overview of recent experimental results from the ADITYA-U tokamak,

    R. L. Tanna et al., “Overview of recent experimental results from the ADITYA-U tokamak,” Nucl. Fusion, vol. 62, no. 4, p. 042017, Feb. 2022, doi: 10.1088/1741- 4326/ac31db

    2022 doi

  19. [28]

    Improved Horizontal Plasma Position Control Using c-RIO-Based Real Time System in Aditya-U,

    P. Gautam et al., “Improved Horizontal Plasma Position Control Using c-RIO-Based Real Time System in Aditya-U,” IEEE Trans. Plasma Sci., vol. 52, no. 9, pp. 3809– 3813, Sep. 2024, doi: 10.1109/TPS.2024.3474713

    2024

  20. [29]

    DEVELOPMENT OF MULTIPURPOSE SOFT X-RAY TOMOGRAPHY SYSTEM FOR ADITYA-U

    J. Raval, “DEVELOPMENT OF MULTIPURPOSE SOFT X-RAY TOMOGRAPHY SYSTEM FOR ADITYA-U.”

  21. [30]

    Mirnov coil data analysis for tokamak ADITYA,

    D. Raju, R. Jha, P. K. Kaw, S. K. Mattoo, Y . C. Saxena, and A. Team, “Mirnov coil data analysis for tokamak ADITYA,” Pramana - J Phys, vol. 55, no. 5–6, pp. 727–732, Nov. 2000, doi: 10.1007/s12043-000-0039-8

    doi

  22. [31]

    Design and measurements of the diamagnetic loop in Aditya-U tokamak,

    S. Aich et al., “Design and measurements of the diamagnetic loop in Aditya-U tokamak,” Radiation Effects and Defects in Solids, pp. 1–12, Aug. 2024, doi: 10.1080/10420150.2024.2378424

    2024

  23. [32]

    The effect of impurity seeding on edge toroidal rotation in the ADITYA-U tokamak,

    A. Kumar et al., “The effect of impurity seeding on edge toroidal rotation in the ADITYA-U tokamak,” Nucl. Fusion, vol. 64, no. 8, p. 086019, Aug. 2024, doi: 10.1088/1741-4326/ad4c5a

    2024 doi

  24. [33]

    MHD mode evolutions prior to minor and major disruptions in SST-1 plasma,

    J. Dhongde, S. Pradhan, and M. Bhandarkar, “MHD mode evolutions prior to minor and major disruptions in SST-1 plasma,” Fusion Engineering and Design, vol. 114, pp. 6– 12, Jan. 2017, doi: 10.1016/j.fusengdes.2016.10.015

    2017 doi

  25. [34]

    Pre- disruption MHD activity in the LT-4 tokamak,

    A. D. Cheetham, S. M. Hamberger, H. Kuwahara, A. H. Morton, and D. Vender, “Pre- disruption MHD activity in the LT-4 tokamak,” Nucl. Fusion, vol. 27, no. 5, pp. 843– 847, May 1987, doi: 10.1088/0029-5515/27/5/013

    1987 doi

  26. [35]

    Observation of the bifurcation of tearing modes due to supersonic gas injected into the J-TEXT plasmas,

    X. D. Feng, G. Zhuang, Z. J. Yang, J. S. Xiao, J. Chen, and X. W. Hu, “Observation of the bifurcation of tearing modes due to supersonic gas injected into the J-TEXT plasmas,” Physics Letters A, vol. 378, no. 16–17, pp. 1147–1152, Mar. 2014, doi: 10.1016/j.physleta.2014.02.017

    2014 doi

Pith tools

Reviewed August 6, 2026 · model on record in the stance chip above.