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Record W4405310430 · doi:10.1016/j.wri.2024.100273

Numerical simulations of solid suspensions in a gravity thickener

2024· article· en· W4405310430 on OpenAlexafffund
Mahmoud A. Alzoubi, Antoine Monot, David Rancourt, Sébastien Poncet

Bibliographic record

VenueWater Resources and Industry · 2024
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsQueen's UniversityUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of CanadaUniversité de Sherbrooke
KeywordsGravity separationPhysicsMechanicsMaterials scienceChemistryMetallurgy

Abstract

fetched live from OpenAlex

Reducing the overall water and energy consumptions in deep mines is a necessity in moving toward a more sustainable mining industry. Underground water treatment is a key requirement to achieve this goal. This study numerically investigates the dynamics of a continuous decantation process as a technique to recycle and reuse wastewater in deep mines without pumping it to the surface. A three-dimensional mathematical model that considers the conservation of mass and momentum has been derived, validated, and implemented to simulate the turbulent two-phase flow inside a decantation tank. The validation is achieved by comparing the numerical simulations to experimental data from the literature for two reference cases: (i) turbulent slurry flows (water and glass particles) in a horizontal pipe; (ii) turbulent swirling flow of limestone ore - water in a hydrocyclone. The framework of the validated model has been extended to examine the effect of various design parameters on the efficiency of a full-scale conical-shaped decantation tank (diameter of 1 [m] and total height of 0.97 [m]). The inlet values of flowrate and particle volume concentration are fixed to 50 [GPM] and 4.5 [%], respectively. The diameter and density of the solid particles are equal to 150 [ μ m] and 1.15, respectively. The results compare the efficiency of 20 different designs of the decantation tank (with/without inner cylinder, scrapers, feedwell, …) in terms of the overflow water quality. The results indicate that the efficiency of the decantation tank increases with inner surface area at fixed volume. Also the plain decanter with scrapers exhibits the highest efficiency, whereas the design with the center extract performs the worst. • Investigate the dynamics of a decantation process in a gravity thickener. • Comprehensive analysis of the turbulent, two-phase flow inside a decantation tank. • Parametric study based on various structure obstacles, flow rates, particles diameter. • Examine the impact of the proposed designs on the overflow water quality. • A plain decanter with scrapers exhibit the best overflow water quality.

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 score0.507
Threshold uncertainty score0.223

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 head0.238
Teacher spread0.226 · 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

Citations5
Published2024
Admission routes2
Has abstractyes

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