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Record W4407920156 · doi:10.1139/cgj-2024-0229

Effect of loading rate on the undrained bearing capacity of nonassociated clay

2025· article· en· W4407920156 on OpenAlexvenueno aff
Yuepeng Dong

Bibliographic record

VenueCanadian Geotechnical Journal · 2025
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsGeotechnical engineeringBearing capacityShear strength (soil)Strain rateGeologyShear (geology)Clay soilSoil mechanicsSoil waterMaterials scienceSoil scienceComposite material

Abstract

fetched live from OpenAlex

The soil behavior is rate-dependent as observed in the laboratory and field tests, and the undrained shear strength of clay is shown to increase with the strain rate in different shear modes. In practical situations, the foundations can be loaded at various time and rate scales, which will result in a wide range of magnitudes and inhomogeneous distribution of strain rates in the surrounding soil. This may cause difficulties in calculating the undrained bearing capacity of clay using the undrained shear strength from standard laboratory and field tests at a reference strain rate. In addition, the rate-dependent soil behavior will also affect the interpretation of in situ tests conducted at different loading rates (e.g., CPT, T-Bar, and pressuremeter tests) using procedures based on rate-independent soil models. This paper investigates the effect of loading rate on the undrained bearing capacity of clay using finite element analyses and a rate-dependent constitutive model, the MIT-SR, based on two classical problems in soil mechanics (i.e., the deeply-embedded rigid pile/pipe section, and the rigid strip footing). Computed results suggest that the undrained bearing capacity of clay is strongly affected by the loading rate of foundations, which is consistent with the model and field tests. It also highlights the difficulty to select appropriate undrained shear strength used for practical design, and the uncertainty to interpret field tests using bearing capacity factors derived from analytical solutions.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.125
Threshold uncertainty score0.495

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.006
GPT teacher head0.196
Teacher spread0.190 · 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
Published2025
Admission routes1
Has abstractyes

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