MétaCan
Menu
Back to cohort
Record W1806147607 · doi:10.1139/cgj-2013-0239

Integrating Eurocode 7 (load and resistance factor design) using nonconventional factoring strategies in slope stability analysis

2013· article· en· W1806147607 on OpenAlexvenueno aff
Lysandros Pantelidis, D. V. Griffiths

Bibliographic record

VenueCanadian Geotechnical Journal · 2013
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsEurocodeLimit state designFactor of safetyFactoringStructural engineeringSafety factorSlope stabilityLimit (mathematics)Geotechnical engineeringStability (learning theory)Shear strength (soil)Shear (geology)EngineeringComputer scienceMathematicsSoil waterGeology

Abstract

fetched live from OpenAlex

In traditional allowable stress design, as known, the safety factor is calculated with respect to shear strength of soil(s) by dividing the available shear strength by the mobilized stresses. The limit-state method, on the other hand, compares — in the form of the inequality E d ≤ R d — the effects of all the actions, E d , with the corresponding resistance of the ground, R d . Although this method considers different loading conditions by using suitable combinations of design values, it is still based on direct comparison of the available shear strength with the mobilized stresses. In the present paper, various factoring strategies (in addition to the traditional one with respect to shear strength of soils) are integrated into a limit-state method framework. Eurocode 7 has been chosen for this purpose. The whole procedure aims at giving a more comprehensive insight into the design of slopes and the sensitivity of safety level of slopes to the various parameters. In addition, the proposed methodology, as shown, may result in a safety level of slopes significantly lower than the respective one obtained using the limit-state method in its traditional form. As man-made slopes that conform to design standards often fail in practice, even though conservative input values are used, these failures must be treated with more skepticism by practitioners adopting supplementary design practices such the one presented herein.

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 categoriesMeta-epidemiology (narrow)
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 score0.677
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.022
GPT teacher head0.223
Teacher spread0.201 · 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.

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

Citations9
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Geotechnical JournalSame topicGeotechnical Engineering and AnalysisFrench-language works237,207