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Record W1889580169 · doi:10.1139/cgj-2015-0251

Contribution to the design methodologies of piled raft foundations under combined loadings

2015· article· en· W1889580169 on OpenAlexvenueno aff
Emilios M. Comodromos, Mello C. Papadopoulou, Lyesse Laloui

Bibliographic record

VenueCanadian Geotechnical Journal · 2015
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsRaftPileGeotechnical engineeringFoundation (evidence)Settlement (finance)Structural engineeringNonlinear systemDesign methodsEngineeringComputer scienceMechanical engineeringMaterials science

Abstract

fetched live from OpenAlex

Although simplified design methods for piled raft foundations have been proposed to allow for the group effect and soil–pile–raft interaction, most of them are concentrated on one type of loading, rendering the applicability of these methods limited to cases under such loads. In the case of a combined pile raft foundation (CPRF), the structural loads are carried partly by the piles and partly by the raft as a function of the foundation settlement, rendering the CPRF a complex soil–structure interaction issue. Despite the recent development of computational resources and advances in numerical expertise, a detailed three-dimensional (3-D) numerical analysis, accounting for soil nonlinearities, nonlinear behavior of the interfaces between the soil, piles, and raft under various combinations of loadings remains impractical. The objective of this paper is to provide a rather simplified and straightforward design methodology for pile foundations under combined loadings. To achieve this goal, previous research works on the group effect under axial and lateral loading have been evaluated and the piles–raft interaction effect has been considered. The proposed procedure is fully compatible with structural software codes and can be straightforwardly applied to the design of the structural members, as it is able to effectively solve a CPRF under the numerous combinations of loadings required by most design codes.

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)0.002
metaresearch head score (Gemma)0.002
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: Methods · Consensus signal: none
Teacher disagreement score0.985
Threshold uncertainty score0.497

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
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 head0.065
GPT teacher head0.268
Teacher spread0.203 · 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
GenreMethods

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

Citations62
Published2015
Admission routes1
Has abstractyes

Explore more

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