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Record W2943991950 · doi:10.1139/cgj-2018-0513

Upper-bound limit analysis of soils with a nonlinear failure criterion

2019· article· en· W2943991950 on OpenAlexvenueno aff
Rui Zhang, Colin C. Smith

Bibliographic record

VenueCanadian Geotechnical Journal · 2019
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsLimit analysisNonlinear systemUpper and lower boundsWedge (geometry)MathematicsYield surfaceGeotechnical engineeringStructural engineeringMathematical analysisEngineeringGeometryPhysicsConstitutive equation

Abstract

fetched live from OpenAlex

Limit analysis is a widely used technique for the analysis of geotechnical collapse states and there exists a significant body of literature covering its application to soils with a linear failure criterion. However, such a failure criterion is often an idealization of an actual nonlinear response for which available analytical techniques are limited. This paper presents a new fully general solution procedure for generating multi-wedge rigid-block upper-bound mechanisms for a soil with a nonlinear failure criterion, utilizing a curved interface that obeys the nonlinear yield function flow rule along its full length. This work extends the long-established kinematic sliding-wedge approach for linear soils and is illustrated through application to active and passive retaining wall and anchor–trapdoor problems. Through additional consideration of the lower-bound solution, close bounds on the retaining wall problem to within ∼1% are established. The ability of the nonlinear upper bound solution to predict the shear and normal stress at every point along the failure surface is discussed.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
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 head0.004
GPT teacher head0.181
Teacher spread0.177 · 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 designTheoretical or conceptual
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

Citations21
Published2019
Admission routes1
Has abstractyes

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