MétaCan
Menu
Back to cohort
Record W4407961959 · doi:10.14796/jwmm.s541

Investigating the Potential of Tide- and Wind-Induced Currents for Renewable Energy in Northern Vietnam

2025· article· en· W4407961959 on OpenAlexvenueno aff
Tuan Anh Le

Bibliographic record

VenueJournal of Water Management Modeling · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geophysical Studies
Canadian institutionsnot available
FundersViet Nam National University Ho Chi Minh CityHo Chi Minh City University of Technology and Education
KeywordsRenewable energyWind powerEnvironmental scienceOceanographyGeographyMeteorologyGeologyEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

Renewable energy is increasingly recognized as the trend and future of sustainable societies. With a long coastline of 3,260 km and vast open sea areas, Vietnam has significant potential for clean energy development. This potential is not limited to wind power alone but extends to encompass a broader range of water-related energy sources. In this paper, the authors employ Delft3D software to create a comprehensive hydrodynamic model that investigates the potential of current velocities in Northern Vietnam, particularly the area surrounding Coto Island, influenced by both tidal variations and wind fields. The model's objective is to preliminarily estimate the potential area for tidal stream energy based on the average current speed. The analysis is guided by international technical criteria (EMEC 2009; IEC-TS 2015), which recommend a yearly average current speed exceeding 0.5 m/s. Preliminary findings highlight several promising locations north of Coto Island, where current speeds reach up to 1.2 m/s. Further in-depth research needs to be conducted, considering the development of tidal stream energy technologies, to explore suitable development plans for Vietnam.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.137

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.021
GPT teacher head0.215
Teacher spread0.194 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Explore more

Same venueJournal of Water Management ModelingSame topicGeological and Geophysical StudiesFrench-language works237,207