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Record W3208346421 · doi:10.1139/cjce-2021-0204

Nonlinear soil–structure behavior of a deployable and compliant anchor system

2021· article· en· W3208346421 on OpenAlexvenueno aff
Ann C. Sychterz, Isabella Bernardi, Joe G. Tom, Ryan D. Beemer

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicTree Root and Stability Studies
Canadian institutionsnot available
FundersUniversity of Illinois at Urbana-ChampaignUniversity of Massachusetts DartmouthDartmouth College
KeywordsTension (geology)Nonlinear systemSoftware deploymentStructural engineeringFinite element methodPileGeotechnical engineeringDeformation (meteorology)Displacement (psychology)Scale (ratio)EngineeringAgricultural engineeringCivil engineeringGeologyUltimate tensile strengthMaterials sciencePhysics

Abstract

fetched live from OpenAlex

This paper presents a novel compliant geo-structural systems bio-inspired by awns on grass seeds for increasing anchor capacity while minimizing material usage. A compliant deployable structure is here defined as a system that reacts to global displacements by continued elastic shape change and awns are slender flexible structures rigidly connected to the exterior of an anchor. When the anchor is loaded in tension, the awns react off the soil mass and deploy outwards from the pile shaft, enabling space-saving measures for transportation. This paper creates a structural pushover model to establish awn deformations and stress values, a scale model of the compliant system fabricated using additive manufacturing, geo-plasticity numerical models of soil awn interaction, and a finite element model of an example application. This research elucidates the soil displacement mechanisms around the awns, the structural deformation of individual awns, and the enhancement of overall anchor capacity due to awn deployment.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.177
Teacher spread0.169 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations4
Published2021
Admission routes1
Has abstractyes

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