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Record W2000807356 · doi:10.1080/17480930902951293

Staged construction analysis of surface tailings disposal facilities

2010· article· en· W2000807356 on OpenAlexafffundabout
Bassam Saad, Hani S. Mitri

Bibliographic record

VenueInternational Journal of Mining Reclamation and Environment · 2010
Typearticle
Languageen
FieldEngineering
TopicTailings Management and Properties
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaScience and Technology Development Fund
KeywordsTailingsUpstream (networking)Civil engineeringDeformation (meteorology)Mining engineeringSurface miningEngineeringTailings damGeotechnical engineeringCoal miningCoalConstruction engineeringGeologyWaste managementMaterials science

Abstract

fetched live from OpenAlex

Abstract One of the major challenges that faces the mining industry is the stability of surface tailings disposal facilities (STDF) particularly when they are raised with the more economical upstream method whereby the embankments are partially built on previously deposited soft tailing materials. Whether the effective or total stress analysis should be used to evaluate the stability of STDFs under construction/operation has been a controversial issue among the respective researchers. Although both analyses cannot compete with the coupled deformation approach, the latter is still grossly underused in the geotechnical evaluation process of STDFs. The goal of this article is to develop a numerical model that can more genuinely assess the stability of STDFs during staged construction using the coupled deformation approach. A number of simulation techniques are presented and discussed using actual data for an upstream coal wash STDF. Keywords: surface tailings disposal facilitiesstabilitycoupled analysisnumerical modelling Acknowledgements The research work is partially supported by Natural Sciences and Engineering Research Council of Canada, Canada (NSERC) and McGill University, Canada. The authors are grateful for their generous support.

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: Empirical
Teacher disagreement score0.145
Threshold uncertainty score0.297

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 head0.008
GPT teacher head0.195
Teacher spread0.187 · 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
Published2010
Admission routes3
Has abstractyes

Explore more

Same venueInternational Journal of Mining Reclamation and EnvironmentSame topicTailings Management and PropertiesFrench-language works237,207