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Record W4239325481 · doi:10.1139/cgj-37-2-485

Determination of passive earth pressure coefficients by the method of triangular slices

2000· article· en· W4239325481 on OpenAlexvenueno aff
Dayong Zhu, Qihu Qian

Bibliographic record

VenueCanadian Geotechnical Journal · 2000
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsnot available
Fundersnot available
KeywordsLateral earth pressureFunction (biology)Limit (mathematics)Series (stratigraphy)GeologyMoment (physics)ScalingRock mass classificationMathematicsMathematical analysisMechanicsApplied mathematicsGeometryGeotechnical engineeringClassical mechanicsPhysics

Abstract

fetched live from OpenAlex

A new procedure is proposed for determination of passive earth pressure coefficients using triangular slices within the framework of the limit equilibrium method. The potential sliding mass is subdivided into a series of triangular slices, rather than vertical slices as usual, with inclinations of the slice bases to be determined. The forces between two adjacent slices (interslice forces) are expressed in terms of interslice force coefficients, and recursive equations for solving interslice coefficients are derived. By using the principle of optimality, the critical inclinations of slice bases, minimum interslice force coefficients, and passive earth pressure coefficients are determined. A form of function for describing the distribution of interslice force inclination (interslice force function) is suggested and the scaling parameter contained in the function is determined by satisfying the moment equilibrium condition for the final sliding mass. Comparisons are made with other accepted methods and tables for passive earth pressure coefficients are presented for practical use.Key words: passive earth pressure coefficient, retaining walls, limit equilibrium method, the principle of optimality.

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: none
Teacher disagreement score0.928
Threshold uncertainty score0.348

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 head0.006
GPT teacher head0.212
Teacher spread0.207 · 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

Citations18
Published2000
Admission routes1
Has abstractyes

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