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Record W4413422435 · doi:10.1016/j.csite.2025.106912

Quantitative mapping mechanism between thermo-flow coupled characteristics and cutting performance of oxygen-propane cutting nozzles

2025· article· en· W4413422435 on OpenAlexaboutno aff
Haonan Yu, Bin Xiong, Y M Han, Zhijun Hu, Xin Liu, Zhixin Wang

Bibliographic record

VenueCase Studies in Thermal Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsnot available
FundersNational Major Science and Technology Projects of ChinaNational Science and Technology Major ProjectNational Natural Science Foundation of China
KeywordsPropaneNozzleMaterials scienceMechanism (biology)Flow (mathematics)MechanicsOxygenNuclear engineeringMechanical engineeringThermodynamicsChemistryPhysics

Abstract

fetched live from OpenAlex

ABSTRACT The present study is founded upon the theoretical framework of isentropic flow, and it puts forward a structural enhancement, of the Laval type, for the oxygen channel of a commercial straight-tube oxygen-propane cutting nozzle. Initially, numerical simulation methods were utilised to examine the preheating flame characteristics of the designed nozzle and the thermal-fluid coupling mechanism between the preheating flame and the cutting oxygen jet. The validation of the simulation results was achieved through the execution of in-situ testing experiments. The study indicates that the characteristics of the cutting oxygen jet are the key factors determining the cutting performance of the flame nozzles. The protective effect of the preheating flame has been shown to significantly improve the flow field characteristics of the oxygen jet (e.g., extending the length of the unmixed high-purity oxygen jet and the length of the velocity core zone). The improved nozzle was finally prototyped and tested on a 332 mm-thick ship engine crankshaft forging (S34MnV steel) under design conditions. This process was successful in revealing and establishing a quantitative mapping relationship between the coupled flow field characteristics and the cutting performance of the nozzle.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.757
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
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 head0.029
GPT teacher head0.260
Teacher spread0.231 · 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.

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
Published2025
Admission routes1
Has abstractyes

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