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Record W6982640555

Integrated modelling of the ramp-up phase of the hybrid scenario for the JT-60SA tokamak

2024· article· en· W6982640555 on OpenAlexaboutno aff

Bibliographic record

VenueIRIS Research product catalog (Sapienza University of Rome) · 2024
Typearticle
Languageen
FieldEngineering
TopicEngineering and Materials Science Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTokamakPlasmaRange (aeronautics)SuitePhase (matter)Power (physics)Fusion power
DOInot available

Abstract

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JT-60SA is a large superconducting tokamak built and operated by Europe and Japan under the Broader Approach Satellite Tokamak Program. The machine is designed to support the exploitation of ITER and the investigation of key physics and engineering issues for future demonstration power plants. The main operational parameters of the plasma scenarios, envisaged for the Integrated Research Phase and described in the JT-60SA Research Plan [1], were simulated using the 0.5-dimensional code METIS and the 2-dimensional equilibrium code ACCOME, as reported in [2]. Moreover, the feasibility of the flat-top phase of these scenarios was confirmed by means of 1.5-dimensional transport codes [3, 4]. However, it is of primary importance to simulate the ramp-up in order to assess whether the main plasma parameters foreseen for the scenario are achievable and under which range of assumptions. The goal of this study is to model the ramp-up phase of the scenario 4-2 (hybrid) (3.5 MA/2.28 T, q95=4.4, βN =3.0) with the JINTRAC [5] suite of codes and the Bohm/gyro-Bohm [6] semi-empirical transport model, taking as starting point the modelling performed with the METIS code. We are predicting the current density, ion density, ion temperature and electron temperature, self-consistently with the plasma equilibrium. The speed of the current ramp-up is imposed, while a feedback loop acting on the gas puff rate is controlling the density in order to follow the target volume averaged density. The heating power deposition profiles and current densities of ECRH and NBI are modelled with the GRAY [7] and PENCIL [8] codes respectively, injecting the power of 37 MW (7 MW of ECRH and 30 MW of NBI). The results of the modelling in terms of plasma kinetic profiles evolution, L-H transition, flux consumption and neutral beam shine-through are presented for different levels of ECRH power and different NBI switching on times. JINTRAC results are fairly close to the ones predicted by METIS, however the L-H transition, predicted by Martin scaling, is found earlier in JINTRAC. The electron temperature profiles are also very sensitive to the different shape of the ECRH power deposition computed by GRAY, with respect to the Gaussian-like profiles imposed by METIS. References [1] JT-60SA Research Plan, version 4.0 www.jt60sa.org/pdfs/JT-60SA_Res_Plan.pdf (September 2018) [2] G. Giruzzi et al 2020 Plasma Phys. Control. Fusion 62 014009 [3] L. Garzotti et al 2018 Nucl. Fusion 58 026029 [4] J. Garcia et al 2014 Nucl. Fusion 54 093010 [5] Romanelli M. et al 2014 Plasma and Fusion Research 9 3403023 [6] M Erba et al 1997 Plasma Phys. Control. Fusion 39 261 [7] D. Farina, Fusion Science and Technology 154, 52 (2007) [8] C.D. Challis et al 1989 Nucl. Fusion 29 56

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.066
GPT teacher head0.294
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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