Towards Performance-Based Seismic Design of Shiploaders
Bibliographic record
Abstract
Large shiploaders that transfer bulk materials are one of the most critical components of a bulk materials handling port. Any disruption in a shiploader service can cause major interruptions in port operations. The design of shiploaders is covered in a few mobile and semi-mobile equipment standards that are limited in scope and clarity regarding seismic design. To compensate for the limited scope of the mobile and semi-mobile equipment standards, design engineers revert to building codes that are created for human-occupied spaces. Building codes are not suitable for the seismic design of shiploaders as they ignore the shiploaders’ ability to move and rotate. Applying the seismic design rules of building codes to shiploaders will result in a significant uncertainty. In this paper, a case study is presented to highlight the importance of performance-based seismic design for shiploaders. The analysis and design approach that implemented the use of seismic structural fuses to control the structural response to earthquakes are explained. The need for integrating the superstructure with the foundations to simulate the soil-structure interaction is highlighted. The study concluded that the proper modelling of certain mechanical components is essential to simulate their true behaviour during an earthquake.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".