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ARIEL E-linac Cryogenic System: Commissioning and First Operational Experience

2015· article· en· W2497209555 on OpenAlexaff
Alexey Koveshnikov, Iouri Bylinskii, Geoff Hodgson, David Kishi, Robert Laxdal, Yuxiang Ma, Ruslan Nagimov, Dimo Yosifov

Bibliographic record

VenueIOP Conference Series Materials Science and Engineering · 2015
Typearticle
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsTRIUMF
Fundersnot available
KeywordsLinear particle acceleratorSuperconducting radio frequencyNuclear engineeringLiquid heliumPhysicsNuclear physicsCryogenicsHeliumNational laboratorySeparator (oil production)Environmental scienceParticle acceleratorEngineeringBeam (structure)Engineering physicsAtomic physicsOptics

Abstract

fetched live from OpenAlex

The Advanced Rare IsotopE Laboratory (ARIEL) is a major expansion of the Isotope Separator and Accelerator (ISAC) facility at TRIUMF. A key part of the ARIEL project is a 10 mA 50 MeV continuous-wave superconducting radiofrequency (SRF) electron linear accelerator (e-linac). The 1.3 GHz SRF cavities are operated at 2 K. HELIAL LL helium liquefier by Air Liquide Advanced Technologies (ALAT) with a tuneable liquid helium (LHe) production was installed and commissioned in Q4'2013 [1]. It provides 4 K liquid helium to one injector and one accelerator cryomodules that were installed and tested in 2014. The 4 K to 2 K liquid helium transition is achieved on-board of each cryomodule. The cryoplant, LHe and LN2 distributions, sub-atmospheric (S/A) system and cryomodules were successfully commissioned and integrated into the e-linac cryogenic system. Required pressure regulation for both 4 K cryoplant in the Dewar and 2 K with the S/A system was achieved under simulated load. Final integration tests confirmed overall stable performance of the cryogenic system with two cryomodules installed. The paper presents details of the cryogenic system commissioning tests as well as highlights of the initial operational experience.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.387
Threshold uncertainty score0.663

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 communication0.0010.001
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 head0.024
GPT teacher head0.222
Teacher spread0.198 · 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 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

Citations1
Published2015
Admission routes1
Has abstractyes

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