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Record W4382310225 · doi:10.31534/engmod.2023.1.ri.04a

Containment Lining Solutions and Hydrodynamic Stability of Tailings Dam

2023· article· en· W4382310225 on OpenAlexaff
Violeta Mirčevska, Ana Nanevska, Miroslav Nastev, Trajce Zafirov

Bibliographic record

VenueInternational Journal for Engineering Modelling · 2023
Typearticle
Languageen
FieldEngineering
TopicTailings Management and Properties
Canadian institutionsGeological Survey of CanadaNatural Resources Canada
Fundersnot available
KeywordsTailingsContainment (computer programming)Tailings damEnvironmental scienceGeotechnical engineeringMining engineeringGeologyMaterials scienceComputer scienceMetallurgy

Abstract

fetched live from OpenAlex

The study investigates the impact of reservoir lining on the hydrodynamic stability of a tailings dam.A 3D coupled fluid-solid finite element model was used for detailed seepage analyses based on conventional flow-net and steady seepage conditions.Pore pressure, stationary seepage velocities, static liquefaction and the ratio between manifested and critical hydraulic gradients were predicted under three different lining conditions.The highest potential for internal erosion and heave was observed in the lined reservoir and starter dam scenario.Although there are environmental benefits, the incorporation of liners in dam design requires a comprehensive engineering assessment of the negative hydrodynamic effects.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.514
Threshold uncertainty score0.473

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.034
GPT teacher head0.234
Teacher spread0.201 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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