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Record W2023563206 · doi:10.1139/cgj-2014-0087

Piled raft with hollow auger piles founded in a Brazilian granular deposit

2014· article· en· W2023563206 on OpenAlexvenueno aff
Wilson Cartaxo Soares, Roberto Quental Coutinho, Renato Pinto da Cunha

Bibliographic record

VenueCanadian Geotechnical Journal · 2014
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsnot available
FundersUniversidade Federal de PernambucoUniversidade Estadual de Campinas
KeywordsFoundation (evidence)Geotechnical engineeringRaftSettlement (finance)Shallow foundationGeologyEngineeringCivil engineeringBearing capacityComputer scienceGeographyMaterials science

Abstract

fetched live from OpenAlex

Geotechnical projects typically achieve load transfer to the ground using shallow or deep foundations. The conventional design approach does not provide for the combination of these two types of foundation. The piled raft philosophy allows the association of the soil elements, raft, and piles to obtain technical and economic advantages over conventional design. The city of João Pessoa, in northeastern Brazil, has developed foundation practices with hollow auger piles in piled raft design. The coastal area of the city has topsoil layers with favorable conditions for using such a technique. This paper addresses the results of a research project with instrumented load tests on foundation systems of hollow auger piles and a piled raft. The analysis is based on the load–settlement curve through extrapolation criteria. The Poulos–Davis–Randolph (PDR) method is applied according to a trilinear and hyperbolic approach to simulate the load–settlement curve of piled rafts. The results indicate that the raft absorbs most of the load, and the raft–soil contact significantly increases the load capacity of the foundation. The PDR hyperbolic method could apply to practical use in the foundations of the region, as it allows a more detailed assessment of the behavior of the foundation and can forecast the behavior of the (locally nontraditional) piled raft foundation system.

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 score0.306
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.004
GPT teacher head0.168
Teacher spread0.164 · 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

Citations13
Published2014
Admission routes1
Has abstractyes

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