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Record W4283264056 · doi:10.47893/gret.2022.1132

A Study on Concepts De-Laval Nozzle using CFD Tool

2022· article· en· W4283264056 on OpenAlexaboutno aff
Krishna Kumar Yadav, Digambar Daware, Vedant Akolkar, Pallavi Padalwar

Bibliographic record

VenueGraduate Research in Engineering and Technology · 2022
Typearticle
Languageen
FieldEngineering
TopicFlow Measurement and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsNozzleComputational fluid dynamicsMechanicsMechanical engineeringFlow (mathematics)Fluid dynamicsEngineeringPhysics

Abstract

fetched live from OpenAlex

A device that is used to control the characteristics of fluid is known as a nozzle. Its primary function is to increase the fluid's rate of motion. A traditional De-Laval nozzle will have three distinct parts: a throat, a converging section, and a diverging part. This paper will attempt to detail the bulk of the nozzle concepts developed by De Laval. This paper provides a comprehensive analysis of the nozzle's operational philosophy. In addition, theoretical flow analysis is carried out at a number of locations along the length of the nozzle. The dynamic changes in flow parameters such as pressure, temperature, velocity, and density may be seen with the use of computational fluid dynamics (CFD). The use of CFD is also employed in the simulation of shockwaves.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score0.570

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.131
GPT teacher head0.349
Teacher spread0.218 · 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 designSimulation or modeling
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
Published2022
Admission routes1
Has abstractyes

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