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Record W4414976246 · doi:10.1177/0309524x251386646

Comparative analysis of offshore and onshore wind turbines: Efficiency, design, and environmental impact

2025· article· en· W4414976246 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWind Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsOffshore wind powerSea breezeSubmarine pipelineWind powerRenewable energyEnvironmental impact assessmentCost of electricity by sourceModular design

Abstract

fetched live from OpenAlex

This study provides a comparative analysis of offshore and onshore wind turbines, focusing on efficiency, design, environmental impacts, and regulatory frameworks. Offshore turbines, benefiting from higher, more consistent wind speeds (∼9 m/s at hub height), achieve capacity factors exceeding 50%, with individual outputs reaching up to 15 MW. Onshore systems operate at lower wind speeds (∼5–8 m/s), achieving capacity factors of 30–40% and outputs of 2–4 MW. Offshore systems, exemplified by Hywind Scotland’s 56% capacity factor, offer scalability but involve higher levelized cost of energy (LCOE) of $80/MWh and potential marine ecosystem impacts. Onshore turbines, more economically viable ($50/MWh LCOE), face land-use conflicts, and biodiversity risks. The study underscores the need for site-specific solutions, balancing energy efficiency, sustainability, and cost-effectiveness, with technological advancements like floating foundations and modular designs enhancing future wind energy scalability. These findings guide investments in clean energy systems tailored to geographic and economic contexts.

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.

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 score0.244
Threshold uncertainty score0.688

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.232
Teacher spread0.223 · 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