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Record W1981935601 · doi:10.1139/t10-021

Contact versus noncontact piled raft foundations

2010· article· en· W1981935601 on OpenAlexvenueno aff
V. Fioravante, Daniela Giretti

Bibliographic record

VenueCanadian Geotechnical Journal · 2010
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsnot available
Fundersnot available
KeywordsCentrifugeRaftGeotechnical engineeringPileSettlement (finance)GeologySoil structure interactionLateral earth pressureEngineeringMaterials scienceStructural engineeringFinite element methodComposite material

Abstract

fetched live from OpenAlex

In the last few decades there has been a rapid increase in the number of piled foundations where the piles have been employed as settlement reducers; in some recent projects, the piles have been separated from the raft by a granular layer, which creates a more uniform pressure distribution on the raft bottom and reduces constraint reactions in the soil, foundation, and superstructure. A series of centrifuge model tests has been performed to investigate the load transfer mechanisms between a square rigid raft and a group of instrumented piles jacked in dry dense sand, in direct contact with the raft or separated from the raft by an interposed granular layer. The test results have shown that contact piles act as settlement reducers by diffusing the load applied to their heads to greater and deeper volumes of soil. The insertion of a deformable layer between a raft and pile heads does not ensure displacement compatibility, and the pressure diffused by the granular fill acts partly on the pile heads and partly produces shallow soil settlements, which mobilize negative skin friction on the upper part of the pile shaft. Noncontact piles act mainly as soil reinforcement.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0080.002

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 head0.010
GPT teacher head0.216
Teacher spread0.206 · 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

Citations111
Published2010
Admission routes1
Has abstractyes

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