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Record W1507243914 · doi:10.1109/secon.2015.7132902

Performance impact analysis of solar cell retrofitted electric golf cart

2015· article· en· W1507243914 on OpenAlexfundno aff
Bikiran Guha, Rami J. Haddad, Youakim Kalaani

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsnot available
FundersCommission for Environmental CooperationGeorgia Southern University
KeywordsAutomotive engineeringEnvironmental scienceRange (aeronautics)CartSolar powerSolar energyElectric powerEngineeringEnvironmental economicsPower (physics)Electrical engineeringMechanical engineering

Abstract

fetched live from OpenAlex

The utilization of golf carts is gaining wide popularity especially in places like universities and large corporations. The conventional gasoline powered golf carts are inefficient and produce very harmful emissions to the environment. Electric golf carts, on the other hand, are quite efficient and environmentally friendly. However, they do not have a long driving range and the batteries need to be frequently recharged. This paper presents a thorough performance analysis of a typical electric golf cart retrofitted with a 100W solar panel. The electrical power requirements, energy savings, and the environmental pollution prevented were also investigated. In this analysis, the performance improvement in the driving range of the golf cart was tested using a series of experiments with and without the solar panel. These experimental results indicated that using a fleet of solar-powered electric golf carts will result in significant energy savings and reduce pollution taking the institution a step forward towards a greener environment.

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 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 score0.197
Threshold uncertainty score0.997

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)0.0030.000

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 head0.011
GPT teacher head0.214
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

Citations3
Published2015
Admission routes1
Has abstractyes

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