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Record W2745815172 · doi:10.1139/cgj-2017-0317

A rigorous method for three-dimensional asymmetrical slope stability analysis

2017· article· en· W2745815172 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Geotechnical Journal · 2017
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Analysis
Canadian institutionsnot available
FundersNatural Science Foundation of Hubei ProvinceNational Natural Science Foundation of China
KeywordsSlope stability analysisDiscretizationFactor of safetySlope stabilitySlip (aerodynamics)Convergence (economics)Stability (learning theory)Safety factorTransverse planeMathematicsPlane (geometry)Geotechnical engineeringApplied mathematicsMathematical analysisMechanicsGeologyGeometryStructural engineeringComputer scienceEngineeringPhysics

Abstract

fetched live from OpenAlex

Most slope failures exhibit remarkable asymmetrical variation in the transverse direction. A rigorous method satisfying all six equilibrium conditions is proposed for evaluating three-dimensional (3-D) asymmetrical slope stability. As there is no need to predefine a symmetrical plane in this analysis, the method is applicable to slopes with complex geometries, geologies, and loading conditions. The proposed method can not only calculate the factor of safety, but also predict the direction of sliding of the potential failure mass. Global equilibrium equations are formulated in light of the safety factor, sliding direction, and an assumed distribution of normal stress on the slip surface. The Newton method is then used to solve these equations, which has been proven to enjoy both a large range of convergence and a fast convergence rate. Thereafter, physical admissibility conditions of the solutions, and the effects of the size of discretized columns on solution accuracy, are discussed in the present 3-D analysis. The method is validated by using five typical examples documented in the literature. The failure of the Kettleman, California, waste landfill slope is also re-evaluated using the proposed method. The calculated stability and direction of sliding match field observations.

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.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.963
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.253
Teacher spread0.234 · 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