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Desiccation in dewatering and strength development of high-density hard rock tailings

2013· article· en· W2883712767 on OpenAlexaff
Paul Simms, S. Sivathayalan, Farzad Daliri

Bibliographic record

VenuePaste/˜Pœaste · 2013
Typearticle
Languageen
FieldEngineering
TopicTailings Management and Properties
Canadian institutionsCarleton University
Fundersnot available
KeywordsTailingsDewateringGeotechnical engineeringShrinkageDesiccationConsolidation (business)Cohesion (chemistry)GeologyWater contentEnvironmental scienceMaterials scienceComposite materialEcologyMetallurgy

Abstract

fetched live from OpenAlex

The time for a freshly deposited layer of high-density tailings to reach a given water content and the contribution of desiccation to the geotechnical behaviour of the stack are complementary pieces of information. Generic modelling analyses to predict dewatering time, first presented at the 13th International Seminar on Paste and Thickened Tailings in 2010 (Paste 2010), are compared with a laboratory simulation of multilayer deposition and select field data. The multilayer experiment supports the finding of the generic modelling predictions: the rate of dewatering decreases over time, as evaporation can be supplied by water from the underlying pre-desiccated tailings. Geotechnical behaviour is discussed using results from simple shear and vane tests on samples with different degrees of desiccation and different levels of subsequent consolidation. Desiccation appears to substantially increase strength and imparts strain hardening behaviour to tailings even after they are re-saturated and consolidated. Substantial increases in strength occur well before the shrinkage limit is reached. Finally, the relevance of shear strength development to overall stack geometry and beach angle is briefly discussed.

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 score0.434
Threshold uncertainty score0.490

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 head0.011
GPT teacher head0.167
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

Citations2
Published2013
Admission routes1
Has abstractyes

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