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Record W4392474732 · doi:10.1061/9780784485309.035

Element and System Level Impact of Strength Loss on Cyclic Performance of Sensitive Clays

2024· article· en· W4392474732 on OpenAlexaff
Tyler J. Oathes, Trevor J. Carey

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMaterials scienceReliability engineeringEngineering

Abstract

fetched live from OpenAlex

This paper presents the results of a numerical investigation into the combined influence of static shear bias and post-peak strength loss on the cyclic behavior of plastic silts and clays at the element and system level. Numerical analyses were performed using the finite difference program FLAC 8.1 with the PM4Silt constitutive model. The element-level impact was investigated using stress-ratio controlled, undrained, cyclic direct simple shear loading simulations with different magnitudes of initial static shear stress and uniform cyclic stress cycles. System-level impacts were investigated with nonlinear dynamic analyses of a levee using a ground motion recording from the 1999 Kocaeli earthquake. Six PM4Silt calibrations were considered to represent a range of clay soil properties. Study findings show that strength loss did not significantly influence the cyclic behavior at the element level; however, strength loss had substantial impact on the overall performance of the levee system, particularly regarding crest deformations and accelerations. The implications of the results on practice and future research needs are 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 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 score0.014
Threshold uncertainty score0.253

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 head0.009
GPT teacher head0.219
Teacher spread0.210 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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