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Effects of installation disturbance on behavior of multi-helix piles in structured clays

2015· article· en· W2285495966 on OpenAlexaff
Farnoosh Bagheri, M. Hesham El Naggar

Bibliographic record

VenueDFI Journal The Journal of the Deep Foundations Institute · 2015
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsWestern University
Fundersnot available
KeywordsPileGeotechnical engineeringFoundation (evidence)Head (geology)Disturbance (geology)VibrationStructural engineeringHydraulic structureCompression (physics)EngineeringGeologyMaterials science

Abstract

fetched live from OpenAlex

Helical piles and anchors are installed by applying torque to the pile head. Their application as a foundation option has gained popularity in recent years because of their intrinsic advantages of rapid installation with minimal vibration and noise, and the development of powerful hydraulic driving heads. In spite of extensive research that investigated the behavior of helical piles and anchors, discrepancies between predictions and actual observations of axial behavior of helical piles installed in clay still exist. This is, in large part, because much of previous research involved installation of helical pile models in remolded (reconstituted) cohesive materials rather than natural soil deposits. Since the strength of the remolded materials does not change significantly, the effects of installation cannot be distinguished in remolded materials. In this study, full scale uplift and compression load tests data are analyzed and different failure patterns have been investigated for helical piles and anchors...

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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.020
GPT teacher head0.247
Teacher spread0.227 · 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

Citations52
Published2015
Admission routes1
Has abstractyes

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