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Record W2121284069 · doi:10.1139/t03-002

A simplified method for 3D slope stability analysis

2003· article· en· W2121284069 on OpenAlexvenueno aff
Zuyu Chen, MI Hong-liang, Faming Zhang, Xiaogang Wang

Bibliographic record

VenueCanadian Geotechnical Journal · 2003
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsLimit analysisSlope stability analysisStability (learning theory)Limit (mathematics)Slope stabilityUpper and lower boundsMathematicsMoment (physics)Range (aeronautics)Rotation (mathematics)Mathematical optimizationApplied mathematicsComputer scienceMathematical analysisGeometryGeotechnical engineeringGeologyEngineeringPhysicsClassical mechanics

Abstract

fetched live from OpenAlex

This paper presents a simplified three-dimensional (3D) slope stability analysis method based on the limit equilibrium theory. The assumption involved in this method is of a parallel intercolumn force inclination, similar to Spencer's method in the two-dimensional (2D) area. It allows for the satisfaction of complete overall force equilibrium conditions and the moment equilibrium requirement about the main axis of rotation. The method has been proven to be numerically tractable for many practical problems. By combining this method with the 3D upper bound approaches, it is possible to bracket the accurate solution of a 3D slope stability analysis problem into a small range.Key words: slope stability analysis, three-dimensional analysis, limit equilibrium method, upper bound method.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.005

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 head0.014
GPT teacher head0.236
Teacher spread0.222 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations110
Published2003
Admission routes1
Has abstractyes

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