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Record W2026863702 · doi:10.1115/imece2013-65867

System and Method for Analysis of Involving Factors in the Demisting Cyclone Efficiency

2013· article· en· W2026863702 on OpenAlexaff
Masoud Molaei Najafabadi, Mohammad Ali Ehteram, Mohammad Taghi Ahmadian, Ahmad Barari

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCyclone Separators and Fluid Dynamics
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsCyclonic separationCyclone (programming language)Pressure dropSeparator (oil production)Volumetric flow rateAirflowMechanicsMarine engineeringEnvironmental scienceHydraulic diameterEngineeringRange (aeronautics)Materials scienceElectrostatic precipitatorStructural engineeringMechanical engineeringInletAerospace engineeringPhysicsElectrical engineeringReynolds number

Abstract

fetched live from OpenAlex

In this study a system for real-time analysis of some involving factors in the efficiency of gas-liquid separators is developed based on the weighing method. An ultrasonic atomizer generates water drops in a size range of 1–10 μm with the same frequency during the test. A cyclone separator is selected and effect of the developing flow rate and shape of the mini-riser as a part of connecting assembly to the cyclone separator is investigated. Further an efficient electrostatic precipitator (ESP) with outcome of single-phase airflow is employed in the downstream of the cyclone to separate remaining droplets and produce the same pressure loss during the test. Circular, triangular, rectangular and square cross section areas with the same hydraulic diameter of 14 mm were examined. The highest cyclone efficiency was recorded for the triangular and rectangular risers comparing to the circular riser at the same length and hydraulic diameter, so the connecting risers with corner could improve the separation efficiency.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.404
Threshold uncertainty score0.214

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 head0.012
GPT teacher head0.247
Teacher spread0.236 · 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 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
Published2013
Admission routes1
Has abstractyes

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