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Record W2070220351 · doi:10.1680/jees.13.00005

Fluidisation behaviour of struvite recovered from wastewater

2014· article· en· W2070220351 on OpenAlexafffundvenueabout
Md. Saifur Rahaman, Donald S. Mavinic, Naoko Ellis

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicPhosphorus and nutrient management
Canadian institutionsUniversity of British ColumbiaConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStruviteSettlingMechanicsMaterials scienceParticle (ecology)Particle sizeReynolds numberWastewaterThermodynamicsMineralogyChemistryEnvironmental scienceGeologyPhysicsEnvironmental engineering

Abstract

fetched live from OpenAlex

A comprehensive characterisation of struvite particles produced from the Edmonton, AB, Canada, wastewater treatment plant was performed. The characterisation of struvite particles included the determination of intrinsic static parameters such as size, density, shape and morphology, as well as the determination of their dynamic behaviour in relation to liquid flow; this included terminal settling velocity, minimum fluidisation velocity and bed expansion characteristics for both monosized and multiparticle systems. The different sizes of struvite particles possessed almost identical dry densities and a nearly spheroidal shape. A very good correlation between average experimental terminal velocities and those predicted by the existing correlations was observed. A correlation reported in the literature was found to provide conservative values of the minimum fluidisation velocity (Umf) for all size groups, with an average deviation of 10%. The expansion characteristics of the monodispersed struvite particle bed were well represented by the Richardson–Zaki relationship, and the expansion index for the struvite particles could be correlated with the particle Reynolds number at terminal settling velocities. Finally, for a multiparticle system, the bed expansion behaviour for struvite particles was better predicted by the serial model than by the average model.

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 score0.758
Threshold uncertainty score0.259

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 head0.003
GPT teacher head0.160
Teacher spread0.157 · 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

Citations6
Published2014
Admission routes4
Has abstractyes

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