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Record W4225157503 · doi:10.11159/icgre22.203

Prediction of Cyclic Behaviour of Quaternary Alluvial Soil using Finite Element Approach

2022· article· en· W4225157503 on OpenAlexvenueno aff
Angshuman Das, Rohan Deb, Subhadeep Banerjee

Bibliographic record

VenueProceedings of the World Congress on Civil, Structural, and Environmental Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsnot available
Fundersnot available
KeywordsAlluviumFinite element methodGeotechnical engineeringGeologyParametric statisticsAlluvial soilsDisplacement (psychology)Constitutive equationStress (linguistics)Stress–strain curveCyclic stressStructural engineeringEngineeringMathematicsGeomorphology

Abstract

fetched live from OpenAlex

This paper presents a numerical simulation to describe the stress-strain responses of sands under large strain cyclic loading using the finite element method.Initially a class C1 Prediction has been performed using two different fully-coupled effective stress constitutive modelling.The calibrated model has been validated further against the experimental data from displacement controlled cyclic triaxial tests for different alluvial soils.In the last part, a parametric study has been conducted to predict the cyclic behaviour and dynamic properties of sands available in the alluvial deposits for variation in site and motion characteristics.The study demonstrates that the proposed model can be used with caution by geotechnical engineer to predict the large strain cyclic behaviour of similar types of sand available worldwide in the alluvial deposits.

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 score0.058
Threshold uncertainty score0.726

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 head0.175
Teacher spread0.166 · 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
Published2022
Admission routes1
Has abstractyes

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