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Record W2909772253 · doi:10.5539/jas.v11n2p217

Evaluation of a Prototype for Water Heating in Agroindustries Using Foucault Current

2019· article· en· W2909772253 on OpenAlexvenueno aff
Marcos Vinícius Schlichting, Carlos Eduardo Camargo Nogueira, Reinaldo Aparecido Baricatti, Tatiane Martins de Assis, Jair Antônio Cruz Siqueira

Bibliographic record

VenueJournal of Agricultural Science · 2019
Typearticle
Languageen
FieldEnergy
TopicSolar Thermal and Photovoltaic Systems
Canadian institutionsnot available
Fundersnot available
KeywordsMagnetEfficient energy useContext (archaeology)Current (fluid)Rotor (electric)ConstructiveEnergy consumptionResistive touchscreenMechanical engineeringHeating systemEnergy (signal processing)Automotive engineeringEnvironmental scienceElectrical engineeringEngineering physicsComputer scienceEngineeringPhysicsProcess (computing)Geology

Abstract

fetched live from OpenAlex

Based on the observation of the effects of energy generation on climate change, efforts have been carried out to develop technologies to reduce polluting energy sources. In this context, the rational use and improvement of the efficiency of water heating systems can play an important role, contributing to lower energy consumption. This study evaluated a prototype for water heating for use in agroindustry. The prototype was designed for a possible utilization of mechanical energy in order to change the magnetic flux produced by permanent magnets, generating thermal energy by Foucault currents. This system presented yields of 64.74%, 65.13% and 64.48% for the rotor configurations with six magnets without pole reversal (6ISI), four magnets with reversal (4ICI), and four magnets without reversal (4ISI), respectively. For comparison purposes, a resistive water heating system was also evaluated for the same study conditions, obtaining an efficiency of 89.21%. The proposed inductive system did not present satisfactory results for constructive conditions presented in the study.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.321
Teacher spread0.247 · 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
Published2019
Admission routes1
Has abstractyes

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