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Record W2097832906 · doi:10.1093/imamat/67.2.177

Thermal runaway and microwave heating in thin cylindrical domains

2002· article· en· W2097832906 on OpenAlexfundno aff
Michael J. Ward

Bibliographic record

VenueIMA Journal of Applied Mathematics · 2002
Typearticle
Languageen
FieldMaterials Science
TopicThermal and Kinetic Analysis
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Hong KongCity University of Hong Kong
KeywordsCylinderNonlinear systemThermal runawayMechanicsPhysicsMathematical analysisMathematicsGeometryThermodynamics

Abstract

fetched live from OpenAlex

The behaviour of the solution to two nonlinear heating problems in a thin cylinder of revolution of variable cross‐sectional area is analysed using asymptotic and numerical methods. The first problem is to calculate the fold point, corresponding to the onset of thermal runaway, for a steady‐state nonlinear elliptic equation that arises in combustion theory. In the limit of thin cylindrical domains, it is shown that the onset of thermal runaway can be delayed when a circular cylindrical domain is perturbed into a dumbell shape. Numerical values for the fold point for different domain shapes are obtained asymptotically and numerically. The second problem that is analysed is a nonlinear parabolic equation modelling the microwave heating of a ceramic cylinder by a known electric field. The basic model in a thin circular cylindrical domain was analysed in Booty & Kriegsmann (Meth. Appl. Anal.4 (1994) p. 403). Their analysis is extended to treat thin cylindrical domains of variable cross‐section. It is shown that the steady‐state and dynamic behaviours of localized regions of high temperature, called hot‐spots, depend on a competition between the maxima of the electric field and the maximum deformation of the circular cylinder. For a dumbell‐shaped region it is shown that two disconnected hot‐spot regions can occur. Depending on the parameters in the model, these regions, ultimately, either merge as time increases or else remain as disconnected regions for all time.

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)0.002
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.225
Teacher spread0.211 · 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

Citations9
Published2002
Admission routes1
Has abstractyes

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