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Record W2788688910 · doi:10.1139/cgj-2017-0602

Erosion of silty sand tailings through a geomembrane defect under filter incompatible conditions

2018· article· en· W2788688910 on OpenAlexaffvenue
Yung-Chin Chou, R. Kerry Rowe, R.W.I. Brachman

Bibliographic record

VenueCanadian Geotechnical Journal · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsGeomembraneTailingsGeotechnical engineeringPipingErosionLeveeEnvironmental scienceGeologyEnvironmental engineeringMaterials scienceMetallurgyGeomorphology

Abstract

fetched live from OpenAlex

At tailings storage facilities, a geomembrane may be used to contain tailings from relatively more permeable foundation or embankment materials. A “filter incompatible” condition may arise between the tailings and underliner materials. In this study, the potential for piping erosion of tailings through a 1 cm diameter geomembrane defect was evaluated in a series of physical experiments. The geomembrane defect was sandwiched between silty sand tailings and various underliners (DF15/DB85 = 5.6–13.5) not meeting typical retention criteria for filtration. The leakage rates and visual findings revealed that a critical stress condition existed where erosion occurred continuously for up to 24 h. This stress condition could be encountered during early deposition or development of a reclaim pond at a tailings storage facility. When allowed to occur, erosion during this stress condition resulted in subsequent leakage rates that were 2–3 orders of magnitude higher than previously observed with “filter compatible” conditions and higher stresses. Practitioners unaware of this potential for erosion near the defect may significantly underestimate leakage and underpredict pore pressures within the embankment.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.662
Threshold uncertainty score0.991

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.000

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 head0.018
GPT teacher head0.251
Teacher spread0.234 · 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.

Study designObservational
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

Citations18
Published2018
Admission routes2
Has abstractyes

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