MétaCan
Menu
Back to cohort
Record W1926854437

Innovative Pavement Design: Are Solar Roads Feasible?

2012· article· en· W1926854437 on OpenAlexaff
Andrew B. Northmore, Susan Tighe

Bibliographic record

VenueUSC Research Bank (University of the Sunshine Coast) · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPhotovoltaic systemEngineeringRenewable energySustainabilityElectricityWork (physics)Civil engineeringArchitectural engineeringTransport engineeringConstruction engineeringMechanical engineeringElectrical engineering
DOInot available

Abstract

fetched live from OpenAlex

Sustainability is critical in current engineering designs, particularly in the field of pavement engineering, and is based on having only limited resources while trying to maximize designs for performance. To this end, developing infrastructure that can meet multiple needs is highly beneficial to society’s will to live at our current standard of living. One such project is the proposal to build roads that have been integrated with photovoltaic cells in order to provide a high performance driving surface while generating renewable electricity. This electricity could then be used by local infrastructure, adjacent buildings, or sold to the electrical grid. In order to do this there are many challenges that need to be overcome, as these roads cannot be made from traditional road surface materials, and a thorough analysis of many design aspects needs to be considered. This paper looks to determine, based on existing pavement materials research, how such a road panel can be constructed and manufactured. Specific elements investigated include the design of each layer of the solar road panel, how the panel can be integrated with photovoltaic electronics, how such a design can be weatherproofed, and how to optimize between solar capture area and structural integrity. The analysis will be influenced by designing around available materials and engineering calculations of the panel under loading. The end result of this paper is a detailed solar road panel design that will be built and evaluated through physical and finite element testing in future work.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.074
GPT teacher head0.277
Teacher spread0.203 · 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 designObservational
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

Citations11
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueUSC Research Bank (University of the Sunshine Coast)Same topicSmart Materials for ConstructionFrench-language works237,207