MétaCan
Menu
Back to cohort
Record W4404711333 · doi:10.3390/ma17235796

Analysis of the Influence of Different Diameters of De Laval Supersonic Nozzles on the Key Splashing Parameters of Remaining Slag

2024· article· en· W4404711333 on OpenAlexaboutno aff
V. Sinelnikov, D. Kalisz, Jan Novosád, Piotr Czarnywojtek, C. Rapiejko, P. Niedzielski, R. Kaczorowski, Pavel Srb, Breno Totti Maia, Michal Petrů, Katarzyna Ewa Buczkowska

Bibliographic record

VenueMaterials · 2024
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsnot available
FundersTechnická Univerzita v Liberci
KeywordsNozzleSupersonic speedSlag (welding)Materials scienceMetallurgyComposite materialMechanical engineeringEngineeringAerospace engineering

Abstract

fetched live from OpenAlex

The paper is devoted to the analysis of a supersonic nozzle system effect in gas-cooled lances on the technological parameters of slag splashing in an oxygen converter. Simulation calculations were carried out, taking into account the parameters of nozzles used in the technological lines of converter steel plants in Ukraine and Brazil. The problems were solved in several stages. The simulation results of the first stage revealed the influence of different nozzle diameters dcr, dex and the inlet pressure before nozzle P0 on the nitrogen consumption of one nozzle Vн. Calculations also showed the influence of the critical dcr and output dex of the nozzle diameter and nitrogen flow through one nozzle Vн on the power of injected nitrogen N1 and the depth of penetration of the stream hx into the liquid slag. The second stage was dedicated to numerical simulation of the slag splashing process, including an array of results from the first stage. The thermodynamic and physical parameters were calculated using our own computer program, while 3D simulations were conducted using the ANSYS Fluent 2023 R2 program.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.224

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.011
GPT teacher head0.209
Teacher spread0.198 · 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 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

Explore more

Same venueMaterialsSame topicMetallurgical Processes and ThermodynamicsFrench-language works237,207