Impact of Wave Energy Converters and Port Layout on Coastal Dynamics: Case Study of Astara Port
Bibliographic record
Abstract
In the face of depleting fossil energy and the imperative of sustainable development, there is a compelling drive towards advancing renewable energies. In this context, sustainable and predictable alternatives, like marine energy, gain prominence. Marine energy presents a cleaner option devoid of the adverse effects associated with fossil fuels, playing a crucial role in environmental sustainability by safeguarding coastlines against erosion. This study focuses on Astara Port in the Caspian Sea, exploring the utilization of wave energy converters (WECs). The originality of this study’s research lies in exploring WECs’ dual role in energy generation and coastal protection. Using MIKE21 software simulations, the impact of number, location, arrangement, and orientation of WECs across various scenarios was investigated, including two WEC number scenarios (11 and 13), three structural placement scenarios (north, front, and south of the port), two structural arrangement scenarios (linear and staggered), two port layout scenarios (original layout and modified layout), and two orientation scenarios for the structures (facing north-east, which is the dominant wave direction, and facing southeast). The results show a remarkable decrease in the significant wave height behind WECs, notably with 13 staggered devices facing dominant waves (from northeast), reducing the significant wave height Hs by 23–25%. This setup also shows the highest wave height reduction, notably 36.26% during a storm event. However, linear WEC setup offers more extensive coastline protection, covering 47.88% of the model boundary during storms. Furthermore, the 11 staggered WECs facing southeast (SE) arrangement had the lowest sediment accumulation at 0.0358 m over one year, showing effective sedimentation mitigation potential. Conversely, the 13 linear WECs facing northeast (NE) had the highest accumulation at 0.1231 m. Finally, the proposed port design redirects high-velocity flow away from the port entrance and removes rotatory flow, reducing sediment accumulation near the harbor entrance.
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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) | 0.000 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".