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Record W2894288406 · doi:10.1016/j.eaef.2018.09.005

Multi-physics computer simulation of radio frequency heating to control pest insects in stored-wheat

2018· article· en· W2894288406 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEngineering in Agriculture Environment and Food · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Pest Control Strategies
Canadian institutionsUniversity of Saskatchewan
FundersWestern Grains Research Foundation
KeywordsMultiphysicsDielectric heatingRadio frequencyIsothermal processHeating elementHeating systemMaterials scienceElectric heatingThermalFluid dynamicsFinite element methodBiological systemMechanicsComposite materialMechanical engineeringEngineeringPhysicsOptoelectronicsElectrical engineeringThermodynamicsBiology

Abstract

fetched live from OpenAlex

Radio frequency (RF) selective heating, a novel method to control insect pests in the stored-grains, has many advantages over the existing methods that use pesticides, fumigants, heat, cold, and mechanical pressure. However, there are many variables that can affect the effectiveness of RF selective heating. The finite element method based COMSOL Multiphysics software was used to simulate the selective heating of rusty grain beetle (Cryptolestes ferrungineus, S) in the bulk stored-wheat at 12, 15, and 18% moisture content. The multi-physics – the electric model, and the non-isothermal fluid flow/heat transfer model were coupled, and the transient electrical and the thermal properties of the insect and wheat were used. Only one quadrant of the RF system including the sample was simulated because of the geometric symmetry in the system. The differences between the experimental and the simulated temperatures for the bulk wheat at MC of 12, 15, and 18% were not more than 13.3, 10.2 and 18.1% respectively. The temperature of the insect was 14.1 °C (maximum) higher than the temperature of the host grain. Therefore, there is a potential of this environmentally friendly method in controlling the insect pests in the stored-grains. The non-uniform heating of the samples was observed, and some recommendations to improve the heating uniformity are presented.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.883
Threshold uncertainty score0.289

Codex and Gemma teacher scores by category

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

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 head0.008
GPT teacher head0.172
Teacher spread0.163 · 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