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Record W1811081419 · doi:10.17930/agl201419

NUMERICAL AND EXPERIMENTAL INVESTIGATIONS OF WIND LOADS ON PV SOLAR PANELS MOUNTED ON FLAT-ROOFS

2014· article· en· W1811081419 on OpenAlexafffundabout
Elena Dragomirescu, Ya Liu

Bibliographic record

VenueAgroLife Scientific Journal · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhotovoltaic systemRoofRenewable energyEnvironmental scienceWind engineeringWind powerSolar energyMeteorologyMarine engineeringEngineeringStructural engineeringElectrical engineeringPhysics

Abstract

fetched live from OpenAlex

As a vast renewable energy resource, solar energy is currently one of the most widely used types of new energy. For collecting solar energy devices based on photovoltaic (PV) cells are installed in locations with optimum exposure to sunlight. Wind-induced load is a main concern; however detailed guidelines and design codes for wind loads on PV solar panels are very limited. Therefore measurements were performed on a PV solar panel installed on the Mann Parking Building of the University of Ottawa. The wind load calculation was performed in conformity with the ASCE7-05 (2005) and SEAOC (2013) design codes, and it was noticed that the roof wind zone, building edge and the parapet effect were the main parameters affecting the estimated wind load value on each PV panel. The maximum wind load of 1,208.0 N was obtained on the northwest corner of the PV solar panel arrays, and the minimum wind load of 806.0 N was obtained on the centre of PV solar panel arrays.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.243
Teacher spread0.228 · 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 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
Published2014
Admission routes3
Has abstractyes

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