MétaCan
Menu
Back to cohort
Record W4403866685 · doi:10.1680/jgeen.24.00319

Stability analysis of tailings dams using limit equilibrium and finite element methods

2024· article· en· W4403866685 on OpenAlexaff
Jian Zheng, Michaël Demers Bonin, Jussi Nousiainen, E. Masengo, Marielle Limoges Shaigetz

Bibliographic record

VenueProceedings of the Institution of Civil Engineers - Geotechnical Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicTailings Management and Properties
Canadian institutionsAgnico Eagle (Canada)WSP (Canada)
Fundersnot available
KeywordsTailingsFinite element methodLimit (mathematics)Stability (learning theory)Tailings damEnvironmental scienceMathematicsGeologyEngineeringStructural engineeringMaterials scienceComputer scienceMathematical analysisMetallurgy

Abstract

fetched live from OpenAlex

This paper presents a case study of stability assessment conducted on a tailings storage facility divider dam. The stability assessment utilised limit equilibrium (LE) with Slope/W, incorporating various commonly used slip surface searching options, and the finite-element method (FEM) with Plaxis2D under static peak and post-liquefaction conditions. The results reveal a significant variation in the factor of safety (FoS) obtained from LE (FoS LE ), depending on the selected slip surface searching options. Notably, the commonly used searching options in Slope/W can yield significantly higher FoS than those obtained from Plaxis2D. This observation prompted the adoption of the fully specified (FS) searching option in Slope/W, where the critical slip surface was aligned with that determined by Plaxis2D, resulting in comparable results to Plaxis2D. The FoS LE obtained by FS searching closely approximated FoS FEM , with a difference of 3.4% under static peak and 15.4% under post-liquefaction conditions. The results indicate that certain slip surface searching options in LE may fail to identify the critical slip surface accurately, leading to an overestimation of the FoS for a given geometry. The FEM, on the other hand, can provide valuable insights by identifying potential critical slip surfaces that may not be identified in LE.

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: Empirical
Teacher disagreement score0.255
Threshold uncertainty score0.920

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
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 head0.022
GPT teacher head0.255
Teacher spread0.233 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Institution of Civil Engineers - Geotechnical EngineeringSame topicTailings Management and PropertiesFrench-language works237,207