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Record W1917734658 · doi:10.1139/t10-084

Distribution of residual load and true shaft resistance for a driven instrumented test pile

2011· article· en· W1917734658 on OpenAlexvenueno aff
Sung‐Ryul Kim, Sung-Gyo Chung, Bengt H. Fellenius

Bibliographic record

VenueCanadian Geotechnical Journal · 2011
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsGeotechnical engineeringPileStrain gaugeLoad testingGroutSettlement (finance)GeologyPenetration testResidualStructural engineeringEngineeringSubgrade

Abstract

fetched live from OpenAlex

Foundation conditions are studied for a series of apartment buildings in a shore area reclaimed from the Nakdong River estuary delta west of Busan, South Korea, in full-scale field tests on two 600 mm, post-driving grouted, concrete cylinder piles instrumented with strain gages, driven through compressible layers and a short distance into underlying dense sand at depths of 56 m (Shinho) and 35 m (Myeongji). One test pile was provided with an O-cell so that after an initial O-cell test, a subsequent head-down test only affected pile shaft resistance. The purpose was to evaluate drivability of the piles, magnitude of the drag load due to consolidating soils, and potential settlement (downdrag) of the piled foundations. Early in the study, it became apparent that the internal process of heating and cooling of the grout during the hydration process and swelling from absorption of water affected the strain records and the assessment of residual load in the test piles during the wait time before the static loading test. The paper reports the measurements, analyses, and method for determining residual load, strain-dependent modulus of test piles, and actual load distribution in the test piles. The results are correlated to cone penetration test (CPTU) sounding data and effective stress analysis.

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 score0.361
Threshold uncertainty score0.632

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.182
Teacher spread0.171 · 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

Citations22
Published2011
Admission routes1
Has abstractyes

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