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Record W2050803092 · doi:10.2166/wst.2009.214

Recovering nutrients from wastewater treatment plants through struvite crystallization: CFD modelling of the hydrodynamics of UBC MAP fluidized-bed crystallizer

2009· article· en· W2050803092 on OpenAlexafffund
Md. Saifur Rahaman, D. S. Mavinic

Bibliographic record

VenueWater Science & Technology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicPhosphorus and nutrient management
Canadian institutionsUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsStruviteComputational fluid dynamicsFluidized bedCrystallizationSedimentationChemistryWastewaterMechanicsChemical engineeringWaste managementProcess engineeringMaterials scienceEnvironmental scienceEngineeringGeologyPhysics

Abstract

fetched live from OpenAlex

This paper is an attempt to model the hydrodynamics of the UBC (University of British Columbia) MAP (magnesium ammonium phosphate) fluidized bed crystallizer. In this study, a numerical investigation of hydrodynamics of the UBC MAP crystallizer was performed, using commercial computational fluid dynamics (CFD) software, Fluent 6.3. One of the main findings of this modelling effort is the relative distribution of the different phases, in this case solids (struvite crystals) and liquid (water), within the reactor. This information is very important, in the sense that it helps fixing the size of the crystallizer, which can be a significant factor, affecting the total cost of the process. Another finding of this simulation is the volume fraction distribution of the different sizes of solid particles, which actually provides insight into the hydrodynamics of the reactor and will fill up the knowledge gap in developing an overall mechanistic model for the crystallizer.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.546

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.204
Teacher spread0.192 · 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

Citations9
Published2009
Admission routes2
Has abstractyes

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