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Record W2167727075 · doi:10.2528/pierm10072609

FDTD MODELING AND SIMULATION OF MICROWAVE HEATING OF IN-SHELL EGGS

2010· article· en· W2167727075 on OpenAlexfundno aff
Satyanarayan Dev, Yvan Gariépy, Valérie Orsat, G. S. V. Raghavan

Bibliographic record

VenueProgress In Electromagnetics Research M · 2010
Typearticle
Languageen
FieldEngineering
TopicInduction Heating and Inverter Technology
Canadian institutionsnot available
FundersFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsFinite-difference time-domain methodMicrowave heatingMicrowaveShell (structure)Materials scienceEnvironmental sciencePhysicsComputer scienceOpticsTelecommunicationsComposite material

Abstract

fetched live from OpenAlex

Abstract—Considering microwaves as a viable alternative for the pasteurization of In-shell eggs, preliminary trials performed had confirmed that microwave at 2450MHz can be successfully used to raise the temperature of in-shell eggs to the required pasteurization temperatures in a few minutes. Based on these trials a finite difference time domain (FDTD) model was developed using C language and MATLAB to simulate the E field and power distribution in lossy dielectric media like that of the egg components (egg white and yolk) taking into consideration the complex shape, dielectric properties and heterogeneous composition of the in-shell egg. This can be used to assist in the design and development of an industrial microwave in-shell eggs pasteurization unit. 1.

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: none
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.033
GPT teacher head0.350
Teacher spread0.317 · 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

Citations27
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueProgress In Electromagnetics Research MSame topicInduction Heating and Inverter TechnologyFrench-language works237,207