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Record W2598544199 · doi:10.1061/9780784480441.001

Polymeric Shell-Confined Aggregate Pier Ground Improvement Method to Support Bridge Embankments over Soft Clay Soil

2017· article· en· W2598544199 on OpenAlexaffabout
Tony Sangiuliano, Jason Brown, Brian Metcalfe, Kord J. Wissmann

Bibliographic record

VenueGeotechnical Frontiers 2017 · 2017
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsMinistry of Transportation of Ontario
Fundersnot available
KeywordsGeotechnical engineeringPierAggregate (composite)CompressibilityLeveeShell (structure)Materials scienceSettlement (finance)GeologyEngineeringStructural engineeringComposite materialComputer science

Abstract

fetched live from OpenAlex

Densified aggregate piers have been widely used for ground improvement since the mid 1990s. The piers are typically constructed by backfilling cylindrical cavities with densified stone using a vertical ramming apparatus. The strength and compressibility of densified aggregate piers systems are confining stress dependent and tend to have low capacities in highly compressible soil because of their tendency to bulge into weak soil. This paper describes the design and construction of a densified aggregate pier system with polymeric shells for confinement in soft soil for a highway embankment in Seeley’s Bay, Ontario, Canada. The method allows for the insertion of high density polyethylene (HDPE) sleeves into the ground through the soft materials using a specially adapted mandrel. This paper is of particular significance because it presents significant insight into an effective ground improvement method in weak and sensitive soil subject to shear strength degradation by traditional aggregate pier methods.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.917
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.015
GPT teacher head0.263
Teacher spread0.248 · 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.

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

Citations0
Published2017
Admission routes2
Has abstractyes

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