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Record W2333786574 · doi:10.1061/40601(256)94

Load Capacity of Pipe Piles in Cohesive Ground

2002· article· en· W2333786574 on OpenAlexaff
Vishnu Diyaljee, Murthy Pariti

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsUniversity of Alberta
FundersU.S. Department of Transportation
KeywordsPilePierGeotechnical engineeringBridge (graph theory)EngineeringDynamic load testingLoad testingStructural engineeringFoundation (evidence)Civil engineering

Abstract

fetched live from OpenAlex

Very often highway departments drive test piles at proposed bridge locations to refusal or to a predetermined set and utilize these records to determine the pile capacity using the Hiley and Engineering News Record pile driving formulae. This test pile driving also provides information on the depth to which the piles can be driven and on problems that may likely be encountered during production piling. The pile capacity obtained from pile driving formulae is generally used by the structural engineer to undertake the preliminary design of the bridge foundations. The use of the pile driving approach to capacity determination often works well when the ground is competent at relatively shallow depths. However, where piles cannot achieve refusal unless driven into stiff or hard ground a geotechnical evaluation of pile capacity becomes more relevant and is often relied upon for pile capacity determination. This paper describes a site where H-pile and closed end pipe piles attained refusal at a depth of 31 metres in hard clay till and where the geotechnical evaluation recommended that the pier piles be terminated at a higher elevation. To demonstrate that the geotechnical recommendations were acceptable, static load testing and Pile Driving Analyzer tests were undertaken. The detailed testing program demonstrated that the driving of piles to refusal was not necessary to achieve the desired pile capacities and that conventional static analysis provided capacities that were sufficiently reliable for design.

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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.017
GPT teacher head0.170
Teacher spread0.153 · 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

Citations3
Published2002
Admission routes1
Has abstractyes

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