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Record W4362576362 · doi:10.1139/cgj-2022-0196

Improvement of tailings impoundment seismic and post-seismic stability using densification and waste rock inclusions

2023· article· en· W4362576362 on OpenAlexafffundvenueabout
Carlos Andrés Contreras, Samuel Yniesta, Michel Aubertin

Bibliographic record

VenueCanadian Geotechnical Journal · 2023
Typearticle
Languageen
FieldEngineering
TopicTailings Management and Properties
Canadian institutionsPolytechnique Montréal
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsTailingsLiquefactionGeologyGeotechnical engineeringTailings damSeismic loadingMining engineering

Abstract

fetched live from OpenAlex

Tailings impoundments are often prone to failure due to various causes related to complex loading conditions. For instance, tailings impoundments can fail during or after a seismic event, mainly because of the liquefaction of loose, cohesionless tailings. To improve the seismic stability of impoundments, the density of the tailings can be increased or waste rock inclusions (WRI) can be added in the impoundment. This paper presents the results of numerical analyses of the impoundments loaded with a variety of ground motions with different frequencies, scaled at two different levels of intensity representative of two mining regions of Eastern Canada. The results show that the conventional impoundments are subjected to medium to high displacements at the end of shaking; these show a high probability of rupture during the earthquake or in the post-seismic phase. Tailings densification can decrease the volume of liquefied tailings and displacements during the seismic phase but does not significantly reduce the probability of post-seismic failure. WRI can slightly reduce the volume of liquefied tailings, depending on the intensity of the motions, but the reinforcement reduces significantly the lateral displacements; impoundments with WRI show even better performances during the post-seismic phase. The use of WRI is deemed a good approach to ensure the seismic stability of tailings impoundments and reduce the risk of seismically induced failure.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.645
Threshold uncertainty score0.942

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 head0.017
GPT teacher head0.209
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 designSimulation or modeling
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

Citations1
Published2023
Admission routes4
Has abstractyes

Explore more

Same venueCanadian Geotechnical JournalSame topicTailings Management and PropertiesFrench-language works237,207