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Record W4221041265 · doi:10.1139/cgj-2021-0260

DEM study of the alteration of the stress state in granular media around a bio-inspired probe

2022· article· en· W4221041265 on OpenAlexvenueno aff
Yuyan Chen, Alejandro Martínez, Jason T. DeJong

Bibliographic record

VenueCanadian Geotechnical Journal · 2022
Typearticle
Languageen
FieldEngineering
TopicAdhesion, Friction, and Surface Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsGeotechnical engineeringPenetration (warfare)Discrete element methodPrincipal stressStress relaxationPenetration depthStress (linguistics)GeologyMaterials scienceMechanicsStructural engineeringEngineeringPhysicsComposite materialOptics

Abstract

fetched live from OpenAlex

Soil penetration is a ubiquitous energy-intensive process in geotechnical engineering that is typically accomplished by quasi-static pushing, impact driving, or excavating. In contrast, organisms such as marine and earthworms, razor clams, and plants have developed efficient penetration strategies. Using motion sequences inspired by these organisms, a probe that uses a self-contained anchor to generate the reaction force required to advance its tip to greater depths has been conceptualized. This study explores the interactions between this probe and coarse-grained soil using 3D discrete element modeling. Spatial distributions of soil effective stresses indicate that expansion of the anchor produces arching and rotation of principal effective stresses that facilitate penetration by inducing stress relaxation around the probe’s tip and stress increase around the anchor. Spatial strain maps highlight the volumetric deformations around the probe, while measurements of both stresses and strains show that the state of the soil around the anchor and tip evolves toward the critical state line. During subsequent tip advancement, the stresses and strains are similar to those during initial insertion, leading to the remobilization of the tip resistance. Longer anchor and shorter anchor-to-tip distance better facilitate tip advancement by producing greater stress relaxation ahead of the tip.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.789
Threshold uncertainty score0.992

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 head0.011
GPT teacher head0.206
Teacher spread0.195 · 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

Citations19
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Geotechnical JournalSame topicAdhesion, Friction, and Surface InteractionsFrench-language works237,207