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Record W2075628133 · doi:10.1002/cjce.21982

Approximate pressure drop and filtration efficiency expressions for semi‐open wall‐flow channels

2014· article· en· W2075628133 on OpenAlexvenueno aff
O. A. Haralampous, Theodore Kontzias

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2014
Typearticle
Languageen
FieldEngineering
TopicAerosol Filtration and Electrostatic Precipitation
Canadian institutionsnot available
Fundersnot available
KeywordsPressure dropMechanicsFiltration (mathematics)Filter (signal processing)UsabilityComputational fluid dynamicsComputer scienceSimulationControl theory (sociology)MathematicsPhysicsStatistics

Abstract

fetched live from OpenAlex

Abstract Semi‐open wall‐flow channels are conventional filter channels with missing plugs either in the frontal or rear side. This configuration has lately become an interesting modelling issue with respect to partial filters designed for the emerging markets and as a special case of wall‐flow filters, that have suffered damage due to regeneration. This paper presents the development of approximate analytical expressions for the estimation of pressure drop and filtration efficiency of semi‐open channels. In order to facilitate the derivation, realistic assumptions are employed and the results are extensively validated using a commercial simulation software, able to solve the differential equations system of the 1D channel model. The validation covers important design parameters and operational conditions, namely filter permeability, length, mass flow rate and soot loading. It is shown that the analytical expressions can predict all trends and moreover offer clear physical explanations. The pressure drop calculation does not exceed 6% of the numerical prediction, while the filtration efficiency absolute error lies within 6% except for specific cases. Finally, a partially failed DPF is simulated using the developed expressions and a commercial CFD package in order to estimate the failure effect on filtration and pressure drop performance. In this way, the usability of the proposed modelling approach is demonstrated.

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: none
Teacher disagreement score0.801
Threshold uncertainty score0.323

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 head0.009
GPT teacher head0.202
Teacher spread0.193 · 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

Citations17
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicAerosol Filtration and Electrostatic PrecipitationFrench-language works237,207