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Record W2769907695 · doi:10.5539/eer.v7n2p48

Renewable Plasma Turbine System

2017· article· en· W2769907695 on OpenAlexvenueno aff
Rimon Louis

Bibliographic record

VenueEnergy and Environment Research · 2017
Typearticle
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsnot available
Fundersnot available
KeywordsRenewable energyElectricityWind powerElectricity generationEnvironmental scienceSolar energyFossil fuelAutomotive engineeringComputer scienceProcess engineeringPower (physics)Electrical engineeringEngineeringWaste managementPhysics

Abstract

fetched live from OpenAlex

The design of the new principle for creating electricity and increase the efficiency of both solar panels and wind power to be commercial source of energy for cities and manufacture depends on solar cells, gas turbine, compressor, magnets and electric generator to create plasma instead of fossil fuel. This paper presents the design of turbine depend on plasma from solar power to increase the efficiency of solar cells or wind turbines and the fuel considered as Plasma. The computational approach attempts to strike a reasonable balance to handle the needs of manufacture and cities. The principle of the solar reactor is approach to get clean, safe and cheap source of electricity in addition to contribute to solve the global warming problem in order to increase the investment and manufacture. Accordingly, in present study an attempt has been made through new device create hyper energy to generate electricity through the creation of direct electric current of the solar cells then interact electricity and compressed air to transform the gas into plasma to reach the ultimate goal to generate 1500 Megawatt from unlimited source of energy and with high assurance of clean and safety.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0320.011

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 head0.039
GPT teacher head0.274
Teacher spread0.235 · 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 designBench or experimental
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
Published2017
Admission routes1
Has abstractyes

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