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Parametric studies of 2K cryogenic system for superconducting e-linac at VECC, Kolkata

2017· article· en· W2750754254 on OpenAlex
J. Pradhan, Manir Ahamed, Manas Mondal, Vaishali Naik, Alok Chakrabarti

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueIndian Journal of Cryogenics · 2017
Typearticle
Languageen
FieldEngineering
TopicSuperconducting Materials and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsLinear particle acceleratorParametric statisticsMathematicsSuperconductivityMedical physicsNuclear engineeringNuclear medicinePhysicsMedicineStatisticsEngineeringOpticsCondensed matter physicsBeam (structure)

Abstract

fetched live from OpenAlex

VECC is developing a 2 mA, 30/50 MeV continuous-wave superconducting electron linear accelerator (e-Linac) for the rare isotope beam facility upgrade. Presently a 10 MeV injector comprising a capture cryomodule (CCM) and an injector cryomodule (ICM) is being developed in collaboration with TRIUMF laboratory in Canada. The CCM and ICM will respectively house two single-cell and one 9-cell niobium superconducting radio-frequency (SRF) cavities operated at 1.3 GHz and 2 K. The 2K temperature is produced by expanding liquid helium from atmospheric pressure to about 30 mbar pressures through a Joule-Thomson (JT) valve. The sub atmospheric pressure is maintained by two roots pumps and a dry backing pump. A 4K-2 K test setup is being developed for testing the cryogenic parameters. A general model is formulated to construct parametric analysis comprising of different components making up the system. The numerical formulation is used for quantitative assessment of the flow requirements under different conditions of operation as well as abnormal scenarios like vacuum failure, rise of thermal shield temperature and so on. The results of the investigation provide a fundamental understanding of the system behaviour and flow requirements during operation. The paper also discusses the intricate relationships among different components of the system along with their desired performance characteristics.

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.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.009
Threshold uncertainty score0.685

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.080
GPT teacher head0.320
Teacher spread0.239 · 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