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Record W7110022604 · doi:10.11159/ijepr.2025.009

Bidirectional Tidal Energy Conversion System

2025· article· W7110022604 on OpenAlexvenueno aff

Bibliographic record

VenueInternational Journal of Environmental Pollution and Remediation · 2025
Typearticle
Language
FieldEngineering
TopicWave and Wind Energy Systems
Canadian institutionsnot available
Fundersnot available
KeywordsTidal powerDimensioningModular designTidal ModelTidal currentMarine energyScalability

Abstract

fetched live from OpenAlex

This paper introduces a novel tidal energy conversion concept specifically designed for low-range tidal environments (~1 m), where conventional tidal technologies are ineffective.The system employs a buoyancy-countermass coupled hydraulic design, capturing energy during both tidal uplift and gravitational descent.This bidirectional approach enables full utilization of tidal displacement, in contrast to turbine-based systems that harness only part of the flow.Key performance results indicate an overall efficiency of approximately 77%, straightforward modular scalability through caisson dimensioning and replication, and technical feasibility using existing offshore engineering practices.Together, these outcomes show that the system can be practically realized and adapted to different site conditions.By demonstrating that both feasibility and scalability are achievable, the study positions the proposed design as a practical foundation for new tidal energy solutions in underserved coastal regions.The concept represents a significant contribution to ocean energy research by showing that useful power can be generated even under minimal tidal ranges.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.005

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.

Opus teacher head0.003
GPT teacher head0.183
Teacher spread0.180 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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