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Record W7103658773 · doi:10.12073/j.hjxb.20240927001

Numerical simulation analysis of the effect of propane nozzle cutting oxygen orifice structure on the flow characteristics of cutting oxygen

2025· article· zh· W7103658773 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2025
Typearticle
Languagezh
FieldEngineering
TopicCombustion and flame dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsBody orificeNozzleConical surfaceSupersonic speedMach numberTurbulatorJet (fluid)Computer simulationCylinder

Abstract

fetched live from OpenAlex

The cutting quality and capacity of an oxygen-propane flame cutting nozzle mainly depend on the characteristics of the cutting oxygen jet. In this paper, the structures of the cutting oxygen orifice of straight cylinder type, conical type, and arc type were investigated. Through theoretical calculations, numerical simulations, and experimental studies, the influence of the cutting oxygen orifice structure on the flow characteristics of the cutting oxygen flow, such as Mach number, velocity distribution, pressure distribution, and density distribution, was revealed. The results show that the straight cylinder type is a subsonic orifice with a maximum Mach number of 1 in jet, and the convergent-divergent (CD) type, namely Laval type, is a transonic orifice that allows the jet to cross from subsonic to supersonic velocities. Compared with a conical type orifice, an arc type orifice has better jet stability, a longer supersonic section, and smaller radial jet fluctuation at the outlet, which is conducive to slag blowing off during the cutting process to obtain better cutting surface quality. Finally, the numerical simulation results are validated through the use of 3D printing techniques and schlieren experiments.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.230
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.058
GPT teacher head0.446
Teacher spread0.387 · 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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