A Simulation Model for a Hybrid-Electric Craft in Restricted Waters
Bibliographic record
Abstract
Sustainable mobility is one of the most challenging issues for passenger transport inside environmental protected areas and ecologically fragile environments. To reduce the pollutant emissions, the adoption of electric or hybrid-electric solutions for crafts propulsion is a suitable option for green navigation. However, the operation in restricted basin leads also to specific critical issues for the vessel sailing, as dealing with shallow or restricted waters and transit under low air-gap bridges. The combination of these constraints with the adoption of a hybrid-electric propulsion system increases the design difficulties also for a small craft, requiring the use of advanced simulation models to assess the vessel performances. This work presents a simulation model for a small passenger craft that will operate in the Grado Lagoon. The model combines the hydrodynamic issues of manoeuvring and propulsion in restricted water with the simulation of the electric loads and capacity of the energy storage system installed onboard. The simulations performed with the developed simulation system are in accordance with data measured during trials on a prototype of the vessel. The developed model is a powerful tool for designers in order to rapidly assess the green capabilities of new projects since the early design stages.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".