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Record W3008541348 · doi:10.1061/9780784482803.019

Discrete Element Modelling of Undrained Consolidated Triaxial Test on Cohesive Soils

2020· article· en· W3008541348 on OpenAlex
Joash Bryan Adajar, Irene Olivia Ubay, Marolo Alfaro, Ying Chen

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGeo-Congress 2020 · 2020
Typearticle
Languageen
FieldEngineering
TopicSoil Mechanics and Vehicle Dynamics
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsGeotechnical engineeringTriaxial shear testFinite element methodSoil waterGeologyStructural engineeringEngineeringSoil scienceShear (geology)

Abstract

fetched live from OpenAlex

Microparameters of the clay component of an earth fill dam need to be identified in order to develop a reliable discrete element landslide model. To characterize clay microparameters, a calibration process of matching the simulated and actual undrained consolidated triaxial test results were performed. Linear parallel-bond model was used to describe the interactions of clay particles. The microparameters calibrated to match the real clay behavior were particle stiffness, friction, bond stiffness, and bond strength. Sensitivity analysis revealed that bond stiffness and bond strength dictate the peak stress behavior of the numerical model, while particle stiffness and friction influence its critical-state stress behavior. The designed calibration methodology based from the sensitivity analysis results was able to identify a suitable set of microparameters that can simulate the real behavior of clay. Integrating the calibrated microparameters to the numerical model yielded good agreement between the measured and simulated stress-strain relationships of clay at different consolidation pressures.

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.

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 score0.028
Threshold uncertainty score0.956

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 head0.022
GPT teacher head0.220
Teacher spread0.198 · 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