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Record W7116040755 · doi:10.82417/pwnv-cr15

Feasibility of highway wind and solar energy harvesting using VAWT in Canada

2025· other· en· W7116040755 on OpenAlexaboutno aff

Bibliographic record

VenueEspace ÉTS (ETS) · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsWind powerRenewable energySolar energyTurbineElectricity generationSolar powerPower (physics)Photovoltaic system

Abstract

fetched live from OpenAlex

The objective of this experiment was to investigate the potential of using renewable energy sources along highways to generate electricity, focusing on the wind created by passing vehicles and the sunlight that falls on the road surfaces. Vertical-Axis Wind Turbines (VAWTs) were employed to harness the wind energy, while solar power was considered to enhance the energy output. The study explored the theoretical and practical efficiency of VAWTs and the impact of design modifications, such as adding fins to the turbine blades, on power production. A series of statistical tests, including one sample and two-sample t-tests, were used to compare theoretical predictions with actual energy production. The results were used to estimate the potential energy generation along highways in Canada, combining wind and solar power in a hybrid system. The experiment concluded with estimations for daily power production from VAWTs and solar panels and highlighted the potential of renewable energy along highways.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.441
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.021
GPT teacher head0.253
Teacher spread0.232 · 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.

Study designNot applicable
Domainnot available
GenreOther

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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