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Record W4402842707 · doi:10.1139/cgj-2023-0701

Nonisothermal fractional order two-surface viscoplastic model for stiff clays

2024· article· en· W4402842707 on OpenAlexvenueno aff
Wei Cheng, Zhen‐Yu Yin, Yu-Jun Cui, Maozhu Peng

Bibliographic record

VenueCanadian Geotechnical Journal · 2024
Typearticle
Languageen
FieldEngineering
TopicGrouting, Rheology, and Soil Mechanics
Canadian institutionsnot available
FundersHong Kong Polytechnic University
KeywordsViscoplasticityGeotechnical engineeringIsothermal processGeologySurface (topology)MechanicsMaterials scienceMathematicsConstitutive equationThermodynamicsFinite element methodGeometryPhysics

Abstract

fetched live from OpenAlex

Stiff clay exists widely in the world, but its significant time- and temperature-dependent mechanical features have not been fully modeled. In the context of fractional consistency viscoplasticity and bounding/subloading surface theory, this study proposes a novel nonisothermal fractional order two-surface viscoplastic model for stiff clays. First, by proposing a generalized plastic strain rate, the isotach viscosity is modified and extended to both over-consolidated and nonisothermal conditions that take into consideration the effects of temperature and OCR on thermal accelerated creep. Then, two strain rate and temperature-dependent yield surfaces are proposed with isotropic and progressive hardening rules to consider thermal collapse, strain rate effects, and smooth transition from elastic to viscoplastic behaviors. Next, the stress-fractional operator of the loading surface, according to the principle of fractional consistency viscoplasticity, is introduced to describe the nonassociativity of stiff clays. Finally, the predictive ability of the model is validated by simulating triaxial tests on Boom clay with various stress paths considering the temperature- and time-dependent features of stiff clays.

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: none
Teacher disagreement score0.982
Threshold uncertainty score0.819

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 integrity0.0000.001
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 head0.013
GPT teacher head0.237
Teacher spread0.224 · 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

Citations6
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Geotechnical JournalSame topicGrouting, Rheology, and Soil MechanicsFrench-language works237,207