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Record W4367317856 · doi:10.18280/mmep.100221

Hybrid Flame Combustion Burner

2023· article· en· W4367317856 on OpenAlexvenueno aff
Ali Samir, Karrar A. Hammoodi, Ihab Omar, Ali Basem, Mujtaba A. Flayyih

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2023
Typearticle
Languageen
FieldEngineering
TopicCombustion and flame dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsCombustorCombustionEnvironmental sciencePremixed flameWaste managementMaterials scienceEngineeringChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The hybrid combustor is represented by combined between premixed and diffusion flame.The premixed flame implemented by cylindrical burner which it gives swirling flow by two nozzles in opposite direction.The diffusion flame investigated by co-axial jet of fuel and annulled by air.The hybrid flame was experimentally and numerically investigated to get high level of flame stability and low emissions level of pollutant.This research used working fuel of liquid petroleum gas which it has 40% propane and 60% butane.Two types of flame were examined, diffusion flame combustion DFC and hybrid flame combustion HFC.In HFC, the influences of fuel nozzle geometry on air/fuel mixing were achieved in terms of stability of flame and level of pollutant emissions.An extremely stability of flame can be given in HFC by the swirling premixed which utilized it as a flame holder because it created over all inner surface of burner.The results showed that the burner design gave high vortex flow by evaluating swirl number for hybrid flame in term of heat input and overall equivalent ratio.The results of flame temperature for three types of combustion premixed flame combustion PFC, DFC and HFC with lean, rich and stoichiometric of equivalence ratio.Numerically studded temperature distribution of diffusion flame combustion by simulate cyclone burner which using in experimental work.Fluent Ansys 16.1 used for 2D simulate turbulent modeling (Standard k-ε model).Three cases of mixture investigated numerically lean, rich and stoichiometric and compared it with experimental rustles.The temperature observed numerically is more than which observed experimentally because the enhancement in heat transfer through test rig burner and low mixing efficiency between air and fuel.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.013
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.002

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 head0.018
GPT teacher head0.193
Teacher spread0.175 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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