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RESEARCH OF ADJUSTABLE LAVAL NOZZLE

2024· article· en· W4393850446 on OpenAlexaboutno aff
Mykhailiuk Vasyl, Liakh Mykhailo, Protsiuk Vasyl, Deineha Rruslan, Vytrykhovskyi Yevstakhii, Stetsiuk Roman

Bibliographic record

VenueInternational scientific and technical conference Information technologies in metallurgy and machine building · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicAerospace, Electronics, Mathematical Modeling
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Heat exchangers are the most common and simplest equipment for cooling gas streams, but heat must be removed for their operation. However, by using a Laval nozzle, it is possible to achieve cooling of the gas flow due to a physical phenomenon in which the gas flow velocity is reduced to the speed of sound. The efficiency of such a nozzle depends on the change in the gas flow rate in it. Therefore, to regulate the mode of operation of the Laval nozzle, its design is proposed, which is simpler than the existing ones, cheaper to manufacture and operate. The nozzle is made of an elastic material - silicone, and is located in a special housing, into which a compression nut is inserted, which compresses the nozzle in the axial direction. Due to this achievement, the inner opening of the nozzle is reduced. Conducted simulation studies of the proposed design of the nozzle made it possible to apply its deformed state, developed and printed on a 3D printer of a mold - to make a silicone nozzle and conduct its research. After conducting a study of the silicone nozzle, it was established that the diameter of the hole at the critical section without deformation in the axial direction is 11.8 mm, and at a deformation of 10 mm - 8.6 mm.

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: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.035
GPT teacher head0.321
Teacher spread0.286 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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