Comparison of Taut and Catenary Mooring Systems for Finfish Aquaculture
Bibliographic record
Abstract
Finfish aquaculture has been expanding in areas like Norway and Canada over the last 20 years, and is projected to expand further in the next decades as the planet’s population and demand for seafood increases. Finding appropriate salmon farm sites is becoming increasingly difficult, as there are fewer protected nearshore locations available for development. As a result, there is interest in increased utilization of existing leases (i.e. permitted sites). These leases have a boundary in which the anchors and mooring lines must be contained. Reducing the footprint of the mooring arrangement will allow for an increased utilization of existing leases. A possible method to reduce the footprint of a spread moored salmon farm is to use a taut mooring rather than a chain catenary mooring. This requires the use of mooring materials and components that allows for handling of tidal elevation changes and wave action. This paper investigates the performance of a taut moored configuration with integrated Seaflex elastomeric mooring components in comparison with a conventional chain catenary configuration using dynamic analysis. The results show that a reduced footprint taut mooring configuration with integrated elastomeric mooring components can be substituted for a typical chain catenary mooring with no significant increase in peak mooring line loads at extreme sea states and significant reduction in peak loading at moderate and calm seastates.
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 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".