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Record W4295926144 · doi:10.1061/9780784484395.035

Design and Construction of New Shiploader Foundations within Existing Post-Tensioned Wharf in Region of High Seismicity

2022· article· en· W4295926144 on OpenAlexaff
Christopher Meisl, Andre Dratwa, Eric Liu, Andrew Quinn, Robert Schwetzke

Bibliographic record

VenuePorts 2022 · 2022
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsTransport CanadaPraxis Spinal Cord Institute
Fundersnot available
KeywordsWharfPileInduced seismicityFoundation (evidence)DeckGeotechnical engineeringEngineeringStructural engineeringDisplacement (psychology)GeologyLiquefactionCivil engineering

Abstract

fetched live from OpenAlex

A new export facility required the installation of three new, fixed 2,000 tph grain shiploaders at an existing wharf. The site is located within a high seismicity zone with liquefiable soils. Each shiploader foundation was constructed as an independent structure from the existing wharf, which was expected to undergo significant damage and lateral displacements in a seismic event due to liquefaction. The locations of the new shiploaders required cutting the existing post-tensioned concrete deck to fit new foundation piles and provide a gap between the structures to minimize pounding during seismic activity. The existing wharf was also modified to introduce seismic fuses such that it could experience localized failure without impacting the new foundations. Each shiploader has a self-weight of approximately 600 t, and their foundations consist of a concrete deck atop vertical steel pipe piles. The geotechnical analysis software FLAC was used to estimate a maximum displacement of 1.3 m at the top of the new foundation structure due to liquefaction and lateral spreading. The foundation was analyzed via SAP2000 structural analysis software. To accommodate the large lateral displacement demands, a heavily reinforced pile-plug and pile-to-deck connection was required. This paper presents the unique engineering solutions that were implemented.

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 score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.021
GPT teacher head0.214
Teacher spread0.193 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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