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Record W2887778802 · doi:10.1139/cgj-2017-0647

Effect of perforations on the bearing capacity of shallow foundation on clay

2018· article· en· W2887778802 on OpenAlexvenueno aff
Run Liu, Meng-meng Liu, Ying-hui Tian, Xinli Wu

Bibliographic record

VenueCanadian Geotechnical Journal · 2018
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
Fundersnot available
KeywordsShallow foundationGeotechnical engineeringSubseaBearing capacityFoundation (evidence)PerforationGeologyDimensionless quantityWaves and shallow waterSeabedMaterials scienceMechanicsComposite materialPhysics

Abstract

fetched live from OpenAlex

As a type of shallow foundation, a mudmat serves as the seabed support structure for subsea wells, pipeline manifolds, and pipeline terminations. The shallow foundations are usually designed with perforations to facilitate installation and removal, but the influence of these perforations has not been fully understood. This paper presents a method to analyze the bearing capacities of both two-dimensional (2D) and three-dimensional (3D) perforated shallow foundations using finite element analysis. The soil was idealized as a Tresca material, with the undrained strength increasing linearly with depth. The outcome indicates that perforations have nonnegligible effects on the bearing capacity of shallow foundations. The bearing capacity decreases with increasing perforation ratio, R, and the degree of reduction increases with the increase of the dimensionless ratio kB/Suo, where k is the shear strength gradient, B is the width of the foundation, and Suo is the shear strength at the mudline. For 2D shallow foundations, there exists a critical perforation ratio, Rc; when the perforation ratio is lower than the critical perforation ratio, the perforated foundation does not lose its bearing capacity. For 3D shallow foundations, the bearing capacity decreases directly with the increase of perforation ratio, R.

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)0.002
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.211
Teacher spread0.200 · 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

Citations9
Published2018
Admission routes1
Has abstractyes

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