Design and Construction of New Shiploader Foundations within Existing Post-Tensioned Wharf in Region of High Seismicity
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".