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Record W4412700036 · doi:10.11159/ffhmt25.236

Experimental Study of Axial Fan Performances Operating In Constrained Environment: Application of Axial and Combined Axial–Radial Blockage

2025· article· en· W4412700036 on OpenAlexvenueno aff
A. Larabi, Tarik Azzam, Amrid Mammeri, Michael P. Pereira, Florent Ravelet, M. Mekadem, H. Oualli, Farid Bakir

Bibliographic record

VenueProceedings of the ... International Conference on Fluid Flow, Heat and Mass Transfer · 2025
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Fluid Dynamics Research
Canadian institutionsnot available
Fundersnot available
KeywordsMechanical fanAxial compressorPhysicsMaterials scienceComputer scienceEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

This paper aimed to develop an experimental procedure for axial fans characterisation operating in constrained fields.The influence of an obstacle located downstream of a fan is studied experimentally on standardised test bench of the suction box type under different specific angular speeds.The axial fan of forward sweep category operates in free field referred as baseline configuration and in fields constrained by two blocking configurations axial and combined axial-radial.The blockages are produced by a flat plate, perpendicular to the axis of rotation of the fan for axial blockage case and two other plates placed radially for combined axial-radial blockage case, modelling, for example, the obstruction of a car internal combustion engine block.The four sets of global performances (pressure rise, flow rate, mechanical power and static efficiency) evolving with the different obstacles are compared to highlight their similarities.Variations in pressure rise as a function of flow rate were observed as the obstacle was changed depending upon the operating regime of the fan weather is working on axial or radial pattern discharge.The characteristic curves seem to evolve with substantial gain compared to the free field case especially when the blockage matched the flow configuration in the fans' wake.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.863
Threshold uncertainty score0.501

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 head0.239
Teacher spread0.228 · 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
Published2025
Admission routes1
Has abstractyes

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