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Record W4412699972 · doi:10.11159/ffhmt25.175

Stability Analysis of Magnetoconvection in a Fluid-Porous System with Thermal Effects

2025· article· en· W4412699972 on OpenAlexvenueno aff
Anil Kumar, D. Bhargavi

Bibliographic record

VenueProceedings of the ... International Conference on Fluid Flow, Heat and Mass Transfer · 2025
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
FundersMinistry of Education, India
KeywordsPorous mediumStability (learning theory)MechanicsThermalPorosityMaterials scienceThermal stabilityThermodynamicsComputer sciencePhysicsComposite material

Abstract

fetched live from OpenAlex

This study investigates the linear and nonlinear stability analysis of thermal convection in a fluid layer overlying a highly porous material, subjected to a vertical magnetic field and maintained at a constant wall temperature.A two-layer approach is adopted, where the Darcy-Brinkman model is used to describe fluid flow within the porous medium.The influence of the magnetic field on both linear and nonlinear stability is analysed.The Chebyshev-Tau-QZ spectral method is employed to solve the coupled ordinary differential equations, formulated as an eigenvalue problem.This approach is particularly advantageous for fluid-porous convection problems due to its high accuracy.Nonlinear stability analysis is conducted using the energy method, and the results are validated against existing literature.The magnetic field shows stabilizing effect and with increase in depth ratio also revealed stabilizing effect.The findings of this study have significant applications in geophysical fluid dynamics, magnetohydrodynamics, and industrial processes such as thermal insulation, cooling systems, and crystal growth, where heat transfer in porous-fluid systems plays a critical role.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.163
Threshold uncertainty score0.465

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 head0.212
Teacher spread0.204 · 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 teacher head, 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
Published2025
Admission routes1
Has abstractyes

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