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Record W2620870055 · doi:10.1061/9780784480700.045

Probabilistic Design of Slopes in Normally Consolidated Clays

2017· article· en· W2620870055 on OpenAlexaff
Desheng Zhu, D. V. Griffiths, Jinsong Huang, Gordon A. Fenton

Bibliographic record

VenueGeo-Risk 2017 · 2017
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Analysis
Canadian institutionsDalhousie University
Fundersnot available
KeywordsProbabilistic logicGeologyGeotechnical engineeringComputer scienceReliability engineeringEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Natural soils always exhibit spatial variability with the properties varying from point to point. The majority of probabilistic slope stability analyses model strength parameters as stationary random fields, i.e. the mean and standard deviation of strength are constant everywhere. Due to the influence of the effective overburden pressure however, normally consolidated soils regularly display an increasing undrained strength trend with depth. Using recently published deterministic solutions as a benchmark, this paper uses random finite element method (RFEM) to investigate the influence of spatial variability on the undrained stability of non-stationary random slopes, where the mean strength increases linearly with depth while the coefficient of variation remains constant. Results are presented in the form of charts that give the mean and standard deviation of the dimensionless stability number. By reading the charts presented in this paper, engineers can obtain a preliminarily assessment of the probability of slope failure for normally consolidated clay slopes.

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: Empirical
Teacher disagreement score0.261
Threshold uncertainty score0.556

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 head0.016
GPT teacher head0.221
Teacher spread0.205 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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