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Record W2806281521 · doi:10.1061/9780784481615.004

Obstructed and Damaged Piles–Some Case Histories of Pile Repairs

2018· article· en· W2806281521 on OpenAlexaffabout
Ali Azizian, Brian E. Hall, Arma Dhaliwal, Robyn Barnett

Bibliographic record

VenueIFCEE 2018 · 2018
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsTetra Tech (Canada)
FundersFlatiron Health
KeywordsPileEmbedmentFoundation (evidence)Geotechnical engineeringDrillingGeologyEngineering

Abstract

fetched live from OpenAlex

Five piled foundation case histories from construction projects in Greater Vancouver, British Columbia are presented. Driven steel pipe piles and drilled shafts had to be repaired to address damage or concerns regarding insufficient ultimate capacity in compression, uplift and/or lateral loading. For many of the piles, lateral loading requirements under extreme seismic events controlled the design, which in turn required minimum embedment depths. These case histories demonstrate that piles which drive short are more difficult to deal with than piles which drive long. In two of the case histories, the presence of confined water pressures resulted in disturbance of the material at the drilled shaft base elevation. Driven pile obstructions occurred because of large glacial erratics that are often present in till-like deposits. In some cases, obstructions were caused by tree trunks entrained within ancient slide debris. Repair methods had to be used when drilling out and replacing obstructed piles was not possible. The repair methods included: driving stinger H-piles inside damaged pipe piles to increase vertical capacity, installing anchors inside and outside driven pipe piles to increase uplift resistance, base-grouting drilled shafts to harden loose zones at the base, and construction of a composite foundation with a shaft carrying lateral loads and a near-surface footing carrying compression loads. Identifying pile installation risks early in the project and providing guidance and potential remediation techniques for the piling contractor was useful for developing repair solutions under tight schedule constraints.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0040.002
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.006
GPT teacher head0.189
Teacher spread0.183 · 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 designCase report
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

Citations0
Published2018
Admission routes2
Has abstractyes

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