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Investigation and Modification of a CSSM-Based Elastic–Thermoviscoplastic Model for Clay

2022· article· en· W4285899978 on OpenAlexaff
Marziyeh Fathalikhani, J. Graham, David Kurz, Pooneh Maghoul

Bibliographic record

VenueInternational Journal of Geomechanics · 2022
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsPolytechnique MontréalKGS Group (Canada)University of Manitoba
Fundersnot available
KeywordsConsolidation (business)Critical state soil mechanicsGeotechnical engineeringSoil mechanicsViscoplasticityConstitutive equationMaterials scienceConstant (computer programming)MechanicsFinite element methodSoil waterGeologyStructural engineeringEngineeringSoil sciencePhysicsComputer science

Abstract

fetched live from OpenAlex

This paper examines the accuracy of a new elastic–thermoviscoplastic (E-TVP) constitutive model developed based on critical state soil mechanics. The model can be used for simulating the temperature-dependent and strain-rate-dependent behavior of clay soils. The study compares the E-TVP behavior of a single soil element with previously published thermo-mechanical experimental results performed on saturated clay specimens at different temperatures. Suggestions regarding unloading and reloading at constant temperatures as well as thermal consolidation under constant loads are presented. A modification for unloading–reloading adds a new criterion to the volumetric thermoviscoplastic strain rate formulation. A physics-based term is added to the current specific volume of the soil to include the viscous effect induced by temperature change. These modifications improve the convergence of laboratory data and simulated model responses. Comparisons of results from an earlier E-TVP model and the newly improved model provide evidence of improved predictive capabilities.

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 score0.842
Threshold uncertainty score0.382

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 head0.021
GPT teacher head0.228
Teacher spread0.207 · 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

Citations9
Published2022
Admission routes1
Has abstractyes

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