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High-power test results for a cylindrical-shell silicon carbide higher-order-mode damper

2024· article· en· W4392910988 on OpenAlexfundno aff
Wencan Xu, Zachary Conway, E. Daly, J. Guo, KA Hernandez, Douglas Holmes, Robert Rimmer, F. Severino, Kevin Smith, Daniel H. Weiss, A. Zaltsman

Bibliographic record

VenuePhysical Review Accelerators and Beams · 2024
Typearticle
Languageen
FieldEngineering
TopicVibration and Dynamic Analysis
Canadian institutionsnot available
FundersBrookhaven National LaboratoryLaboratory Directed Research and DevelopmentTRIUMFU.S. Department of Energy
KeywordsDamperSilicon carbideShell (structure)Materials sciencePower (physics)Mode (computer interface)Structural engineeringTest (biology)Composite materialPhysicsComputer scienceEngineeringGeology

Abstract

fetched live from OpenAlex

The next high-current Electron-Ion Collider (EIC) is a new accelerator to be built at Brookhaven National Laboratory in collaboration with Thomas Jefferson National Accelerator Facility. In the EIC Electron Storage Ring (ESR), there will be beam currents of up to 2.5 A, which will excite massive higher-order-mode (HOM) power in the 17 single-cell 591 MHz superconducting radio-frequency (SRF) cavities. Damping the HOM power in the ESR SRF cavities is a challenge. A room temperature cylindrical shell shape silicon carbide (SiC) beamline HOM absorber (BLA) was chosen as the baseline design, due to its broadband and high-power capability, and previous demonstrations at other accelerator facilities, albeit at much lower power. Because the EIC BLA HOM power dissipation is significantly greater than the previous applications, it is imperative to carry out high-power testing to determine the maximum device performance levels achievable for thermal transport, rf breakdown, and mechanical stress, prior to finalizing the design. A SiC HOM absorber with a state-of-the-art geometry size was prototyped to verify the shrink-fit technique, test outgassing rate, and high-power handling capability. This paper presents the HOM damper’s prototyping and test results. Published by the American Physical Society 2024

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.545
Threshold uncertainty score0.765

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.012
GPT teacher head0.278
Teacher spread0.266 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations2
Published2024
Admission routes1
Has abstractyes

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