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Thermal Design of a 100 kW Electron to Gamma Converter at TRIUMF

2018· article· en· W4234445346 on OpenAlexaff
B. Cade, Luca Egoriti, A. Gottberg, Dayton Priessl

Bibliographic record

VenueJournal of Physics Conference Series · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear Physics and Applications
Canadian institutionsUniversity of VictoriaTRIUMF
Fundersnot available
KeywordsBremsstrahlungPhysicsElectronNuclear physicsPhotonGamma rayCathode rayNuclear engineeringOpticsEngineering

Abstract

fetched live from OpenAlex

The electron target station of the TRIUMF-ARIEL Facility will employ an electron "driver" beam to irradiate Isotope Separator On-Line (ISOL) targets for the production of radioactive isotopes via photofission [1]. 35 MeV electrons will be converted to gamma spectrum Bremsstrahlung photons via an electron to gamma (e- γ ) converter located upstream of the ISOL target. The e- γ concept uses a composite metal with two layers: One high-Z material to stop and convert electrons to photons, and one low-Z material to provide structural support, thermal dissipation, and maximal transparency to the produced gamma photons as well as to provide attenuation of remaining primary electrons.. Several material combinations and bonding processes are currently being evaluated and tested using TRIUMF's e-linac. Water-cooling and thermal design are being optimized for 100 kW electron beam power operation and have thus far been experimentally validated up to 10 kW driver beam power equivalent. The latest test results and future prospects are summarized.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.024
GPT teacher head0.261
Teacher spread0.237 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

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