MétaCan
Menu
Back to cohort
Record W2806149526 · doi:10.1061/9780784481622.008

Savings from Testing the Driven-Pile Foundation for a High-Rise Building

2018· article· en· W2806149526 on OpenAlexaff
Van E. Komurka, Adam G. Theiss

Bibliographic record

VenueIFCEE 2018 · 2018
Typearticle
Languageen
FieldEngineering
TopicConstruction Engineering and Safety
Canadian institutionsGolder Associates (Canada)
Fundersnot available
KeywordsPileFoundation (evidence)ScheduleEngineeringStructural engineeringLoad testingProduction (economics)Geotechnical engineeringComputer science

Abstract

fetched live from OpenAlex

The project consists of a high-rise building supported on driven piles. Design objectives included determining the highest maximum long-term capacity which could be reasonably obtained from a drivability perspective, using readily available equipment. A pre-production test program was performed on 16-in. -diameter (406-mm-diameter) ASTM 252, Grade 3 (45 ksi and 310 MPa) steel pipe piles, having a wall thickness of 0.50 in. (13 mm). Based on evidenced capacities, including long-term set-up, a maximum allowable pile load of 600 kips (2,670 kN) was used on the project. The cost-effectiveness of the test program was evaluated by comparing the cost of a design using 600-kip allowable load piles to alternative designs using the same pile section, but assuming that various lesser testing scenarios had been performed, warranting higher safety factors. Six complete alternative foundation designs were performed for these lower allowable pile loads. Costs associated with the piles (based on production-pile driving behavior), concrete caps and mat, and construction-control methods were estimated for the redesigns. Foundation costs were evaluated for piles designed both with and without the benefit of capacity contribution from set-up. Cost differences among the various construction-control methods were determined in terms of total cost, and support cost. Pile-driving schedule impacts associated with the six alternative allowable loads were also estimated. Additional savings that resulted from applying test-program results to production piles which were damaged or terminated short were quantified.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.016
GPT teacher head0.217
Teacher spread0.201 · 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 designObservational
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

Citations2
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueIFCEE 2018Same topicConstruction Engineering and SafetyFrench-language works237,207