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Record W2960401979 · doi:10.1016/j.nme.2019.100696

Physics basis for the first ITER tungsten divertor

2019· article· en· W2960401979 on OpenAlexaff
R.A. Pitts, X. Bonnin, F. Escourbiac, H. Frerichs, J.P. Gunn, T. Hirai, A.S. Kukushkin, E. Kaveeva, M.A. Miller, D. Moulton, V. Rozhansky, I. Senichenkov, E. Sytova, O. Schmitz, P.C. Stangeby, G. De Temmerman, I. Veselova, S. Wiesen

Bibliographic record

VenueNuclear Materials and Energy · 2019
Typearticle
Languageen
FieldMaterials Science
TopicFusion materials and technologies
Canadian institutionsUniversity of Toronto
FundersRussian Science FoundationUniversity of Wisconsin-MadisonU.S. Department of Energy
KeywordsDivertorTungstenNuclear engineeringPhysicsNuclear physicsBasis (linear algebra)TokamakMaterials sciencePlasmaEngineeringMetallurgyGeometry

Abstract

fetched live from OpenAlex

• Reviews the fundamental physics aspects of the first ITER W divertor and defines the required operational lifetime within the Staged Approach. • Uses the ITER divertor SOLPS simulation database to establish the target peak heat flux and neutral pressure burning plasma operating domain. • Assesses consequences of narrow SOL heat flux channels, fluid drifts, component shaping and 3D magnetic fields for ELM control. • Uses W recrystallization to define an operational budget and shows that heat fluxes ∼50% higher than previously assumed may be acceptable. • Shows that Ne and N should be equally good as seed impurities and suggests that very strong ELM mitigation will be required at high performance. • Provides a list of key outstanding R&D areas to consolidate the divertor physics basis in the period up to ITER operation. On the eve of component procurement, this paper discusses the present physics basis for the first ITER tungsten (W) divertor, beginning with a reminder of the key elements defining the overall design, and outlining relevant aspects of the Research Plan accompanying the new “staged approach” to ITER nuclear operations which fixes the overall divertor lifetime constraint. The principal focus is on the main design driver, steady state power fluxes in the DT phases, obtained from simulations using the 2-D SOLPS-4.3 and SOLPS-ITER plasma boundary codes, assuming the use of the low Z seeding impurities nitrogen (N) and neon (Ne). A new perspective on the simulation database is adopted, concentrating purely on the divertor physics aspects rather than on the core-edge integration, which has been studied extensively in the course of the divertor design evolution and is published elsewhere. Emphasis is placed on factors which may increase the peak steady state loads: divertor target shaping for component misalignment protection, the influence of fluid drifts, and the consequences of narrow scrape-off layer heat flux channels. All tend to push the divertor into an operating space at higher sub-divertor neutral pressure in order to remain at power flux densities acceptable for the target material. However, a revised criterion for the maximum tolerable loads based on avoidance of W recrystallization, sets an upper limit potentially ∼50% higher than the previously accepted value of ∼10 MW m −2 , a consequence both of the choice of material and the finalized component design. Although the simulation database is currently restricted to the 2-D toroidally symmetric situation, considerable progress is now also being made using the EMC3-Eirene 3-D code suite for the assessment of power loading in the presence of magnetic perturbations for ELM control. Some new results for low input power corresponding to the early H-mode operation phases are reported, showing that even if realistic plasma screening is taken into account, significant asymmetric divertor heat fluxes may arise far from the unperturbed strike point. The issue of tolerable limits for transient heat pulses is an open and key question. A new scaling for ELM power deposition has shown that whilst there may be more latitude for operation at higher current without ELM control, the ultimate limit is likely to be set more by material fatigue under large numbers of sub-threshold melting events.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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)0.0040.001

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 head0.011
GPT teacher head0.190
Teacher spread0.180 · 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 designBench or experimental
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

Citations653
Published2019
Admission routes1
Has abstractyes

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