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Record W979634041 · doi:10.13182/fst10-a10887

Assessment of Collateral Effects of Thermo-Oxidation on DIII-D In-Vessel Components in Preparation for In Situ Oxidation in DIII-D

2010· article· en· W979634041 on OpenAlexafffund
B.W.N. Fitzpatrick, J.W. Davis, A.A. Haasz, A.G. McLean, P.C. Stangeby, S. W. Allen, R. F. Ellis, W. P. West

Bibliographic record

VenueFusion Science & Technology · 2010
Typearticle
Languageen
FieldMaterials Science
TopicFusion materials and technologies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Arizona
KeywordsDIII-DMaterials scienceTorrTritiumCryopumpTorusFusion powerCarbon fibersRadiochemistryNuclear engineeringAnalytical Chemistry (journal)Composite materialChemistryNuclear physicsComposite numberChromatographyPlasmaTokamakPhysicsThermodynamics

Abstract

fetched live from OpenAlex

Carbon-based codeposits formed in carbon-containing fusion devices have the potential to dominate tritium retention in the torus. One of the tritium removal techniques currently being studied is thermo-oxidation, which is unique in its ability to remove tritium from codeposits without mechanical intervention in the torus and in its ability to remove tritium from codeposits in tile gaps and shaded areas. In preparation for an oxidation experiment planned to be performed in DIII-D, we have investigated the potential collateral effects of thermo-oxidation on DIII-D in-vessel components. Laboratory oxidation experiments were performed at 2 Torr ([approximately]270 Pa) and 15 Torr ([approximately]2 kPa) O2 pressure and temperatures in the range 100 to 350°C (373 to 623 K) for 2 to 8 h. After oxidation, components were examined for visual or mechanical change, and when appropriate, mass changes were also obtained. In some cases, optical diagnostics were also performed. The specimens were mostly spare/surplus components and spanned a wide variety of materials and functions, e.g., cryopump components; structural, mechanical, and diagnostic components; and fast-wave antennas. The effect of oxidation was found to be negligible for nearly all DIII-D components and materials tested.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.015
GPT teacher head0.312
Teacher spread0.297 · 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 designObservational
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

Citations3
Published2010
Admission routes2
Has abstractyes

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