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Record W2046099234 · doi:10.1080/17480930.2013.772698

Reliability-based approach to the geotechnical design of tailings dams

2013· article· en· W2046099234 on OpenAlexaff
Tarek Hamade, Hani S. Mitri

Bibliographic record

VenueInternational Journal of Mining Reclamation and Environment · 2013
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Analysis
Canadian institutionsMcGill University
Fundersnot available
KeywordsTailingsTailings damGeotechnical engineeringCohesion (chemistry)Reliability (semiconductor)EngineeringFactor of safetySafety factorCivil engineeringHydraulic conductivityEnvironmental scienceSoil waterSoil science

Abstract

fetched live from OpenAlex

Mine tailings dams are geotechnical structures that are designed to provide adequate and safe storage of tailings materials both during and after the end of mine life. The design of such structures is thus of utmost importance not only to the success of the mining operation, but more importantly to the safety of the surrounding environment such as freshwater resources, wildlife and community developments. This paper presents a reliability-based approach for the geotechnical design of mine tailings dams through a real life case study of a water retention tailings dam. The stability analysis is conducted with a hydromechanical, elasto-plastic finite difference model. The reliability analysis is carried out for three stochastic parameters namely the cohesion and friction angle of the dam core material as well as its hydraulic conductivity. The results are presented in the form of probability distribution functions of the generated factor of safety. The generated reliability indices are compared to target reliability indices to help evaluate the geotechnical design of the dam.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.725
Threshold uncertainty score0.207

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 head0.010
GPT teacher head0.198
Teacher spread0.188 · 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

Citations8
Published2013
Admission routes1
Has abstractyes

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