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Record W2954409405 · doi:10.1139/cgj-2019-0026

Bearing capacity of spread footings on aggregate pier–reinforced clay: updates and stress concentration

2019· article· en· W2954409405 on OpenAlexvenueno aff
Taeho Bong, Armin W. Stuedlein, John P. Martin, Byoung-Il Kim

Bibliographic record

VenueCanadian Geotechnical Journal · 2019
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsnot available
Fundersnot available
KeywordsPierBearing capacityGeotechnical engineeringAggregate (composite)Structural engineeringShallow foundationBearing (navigation)GeologyEngineeringMaterials scienceComputer scienceComposite material

Abstract

fetched live from OpenAlex

Aggregate piers represent an economical ground improvement technique used to increase bearing capacity and reduce settlements of weak soils. Several approaches have been developed to estimate the bearing capacity of aggregate pier–reinforced clay, but these models exhibit large prediction bias and uncertainty. This study uses newly developed footing loading test data to investigate the relationship between the bearing capacity and the area replacement and slenderness ratios. The bearing capacity of a single aggregate pier, whether isolated or in groups, below a loaded footing increases as the area replacement ratio decreases due to increase in extent of confined soil surrounding the pier. The length and diameter of an aggregate pier is also shown to result in significantly increased bearing capacity, an effect that diminishes with increasing slenderness. New modifications are proposed to existing simplified and cavity expansion models to account for the effect of confinement, area replacement ratio, and slenderness ratio using a leave-one-out cross-validation technique. The cross-validation analysis resulted in robust bearing capacity models that are more accurate than existing analytical models. Additionally, the stress concentration ratio for shallow foundations supported by aggregate pier–reinforced plastic soils at failure was estimated and compared with the available data, indicating its sensitivity to design variables and showing that this critical design parameter may be predicted using the updated models.

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 score0.015
Threshold uncertainty score0.634

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 head0.007
GPT teacher head0.178
Teacher spread0.171 · 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

Citations15
Published2019
Admission routes1
Has abstractyes

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