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Record W2809638230 · doi:10.1061/9780784481691.014

Moving from 2D to a 3D Unsaturated Slope Stability Analysis

2018· article· en· W2809638230 on OpenAlexaff
M. D. Fredlund, D. G. Fredlund, Lulu Zhang

Bibliographic record

VenuePanAm Unsaturated Soils 2017 · 2018
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Analysis
Canadian institutionsSoilVision Systems (Canada)Golder Associates (Canada)
Fundersnot available
KeywordsSlope stabilitySlope stability analysisGeotechnical engineeringStability (learning theory)Factor of safetySafety factorWater tablePore water pressureLimit analysisGroundwaterSlope stability probability classificationGeologyLimit (mathematics)MathematicsEngineeringComputer scienceStructural engineeringFinite element methodMathematical analysis

Abstract

fetched live from OpenAlex

Two-dimensional (2D) limit equilibrium analyses remain the most common method of analysis in slope engineering practice. It is commonly perceived that 2D slope stability analysis always provides a more conservative estimate of the 3D slope stability problem. Most previous studies comparing 2D and 3D stability analysis also ignore the effect of negative pore-water pressures (i.e., matric suctions) in the soil zone above the groundwater table. In this paper, a comparison study is reported between 2D and 3D slope stability analysis for soil slopes with a portion of the soil profile having matric suctions. The differences between a 2D and a 3D factor of safety are found to be heightened when unsaturated conditions are considered. The paper also presents a framework for the inclusion of soil suctions in the calculated factor of safety for geotechnical engineering practice. A discussion on reducing a 3-D numerical model to give answers similar to a 2-D slope stability analysis will be presented. A basis for transitioning to 3-D analysis will be developed.

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)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.226
Teacher spread0.213 · 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
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

Citations10
Published2018
Admission routes1
Has abstractyes

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