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Record W4389264834 · doi:10.3390/min13121514

Compressive Stress Dewaterability Limit in Fluid Fine Tailings

2023· article· en· W4389264834 on OpenAlexafffund
Alebachew Demoz

Bibliographic record

VenueMinerals · 2023
Typearticle
Languageen
FieldMaterials Science
TopicClay minerals and soil interactions
Canadian institutionsNatural Resources Canada
FundersNatural Resources CanadaUniversity of AlbertaOffice of Energy Research and DevelopmentGovernment of CanadaAustralian Government
KeywordsMaterials scienceCompressive strengthThermogravimetric analysisVoid ratioComposite materialChemistry

Abstract

fetched live from OpenAlex

Reclamation of fluid fine tailing (FFT) storage facilities to their pre-disturbance equivalent landforms is hampered because micrometer size fines, whose surface-area-to-volume ratio is remarkably high, are occupied with siloxane and hydroxy groups, which bind water strongly. The purpose of this study is to differentiate the forms of water physically distributions in FFT and determine their propensities for dewaterability under compressive stresses. Two thermal and two mechanical methods were used to analyze water distributions in FFT. Dynamic and isothermal thermogravimetric analyses of FFT gave a transition from predominately bulk water to coevolution with water of higher enthalpy of vaporization at 81% (w/w) solids. Differential scanning calorimeter studies were used to determine the non-freezable water amount, with the premise that water that does not freeze by −30 °C is also unlikely to be removable by compressive stresses encountered in tailing treatment processes. The solid weight percent of FFTs with the non-freezable water was 79.6%. A 1D finite-strain model simulation using the constitutive relations of void ratio and effective stress, void ratio, and hydraulic conductivity show that deep-pits filled with such clayey-silt FFT will consolidate to a maximum solids content of 74% (w/w). For separation by centrifugation, the solids content plateaued to a mean of 74% (w/w) for total centrifugal force of ≥30 mega Newtons. These solid contents represent upper thresholds and demonstrate dewatering limit property of an FFT under compressive stresses.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.011
Threshold uncertainty score1.000

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)0.0020.001

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 head0.036
GPT teacher head0.297
Teacher spread0.262 · 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; both teacher heads agree on what is shown here.

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

Citations4
Published2023
Admission routes2
Has abstractyes

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