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Record W4242509513 · doi:10.3990/1.9789036539937

Development of a sorption-based Joule-Thomson cooler for the METIS instrument of E-ELT

2015· dissertation· en· W4242509513 on OpenAlexaboutno aff
Yingzhe Wu

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicAdvanced Thermodynamic Systems and Engines
Canadian institutionsnot available
Fundersnot available
KeywordsMetisJoule–Thomson effectSpectrographBellowsMechanical engineeringNuclear engineeringMaterials sciencePhysicsEngineeringComputer scienceThermodynamicsAstronomy

Abstract

fetched live from OpenAlex

METIS, the Mid-infrared E-ELT Imager and Spectrograph, is one of instruments in the European Extremely Large Telescope. Its detectors require cryogenic cooling at three temperature levels below that of liquid nitrogen, 8 K, 25 K, and 40 K. Vibration-free cooling is one of the technologies that were identified as the most needed in the development of the METIS instruments. Therefore, a useful cooling technology based on sorption Joule-Thomson (JT) coolers was proposed for the METIS by University of Twente. The scope of this thesis is to provide vibration-free cooling at multiple cryogenic temperatures for the optics and infrared detectors in large ground telescopes. The thesis focuses on developing a vibration-free sorption-based JT cooler for the METIS instrument in the E-ELT. The research is characterized by challenges such as multiple cooling levels, large cooling capacity with considerable efficiency and size, manufacturability and costs, etc.. The development initialized by gathering basic inputs, such as adsorption isotherms and optimization of the working fluids according to the cooling requirement. A conceptual baseline design of the METIS cooler chain was first defined to present a first impression, particularly in terms of the input power and size. Based on this baseline design, three demonstration setups were built and tested to validate the cooler design: 1. Full-scale 8 K helium JT cold stage; 2. Scaled helium sorption compressor; 3. Scaled 40 K neon sorption JT cooler.

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)0.001
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: Bench or experimental
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.021
GPT teacher head0.259
Teacher spread0.238 · 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
GenreOther

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
Published2015
Admission routes1
Has abstractyes

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