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Record W7115593141 · doi:10.1002/cjce.70208

Analysis of flow dynamics and heat transfer in a combustion chamber

2025· article· en· W7115593141 on OpenAlexvenueno aff

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicCombustion and flame dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsCombustionCombustion chamberHeat transferFlow (mathematics)Magnetohydrodynamic driveThermal efficiencyThermalThermal scienceComputational fluid dynamics

Abstract

fetched live from OpenAlex

Abstract The study of steady flow, heat transfer, and mass transport within combustion chambers plays a pivotal role in optimizing industrial energy systems, ensuring enhanced efficiency and environmental sustainability. These phenomena are central to advanced combustion technologies' design and performance evaluation. To advance combustion technologies, this paper investigates the heat flow dynamics, thermal behaviour, and concentration variation within a combustion chamber filled with a homogeneously mixed magnetohydrodynamic fluid (MHD). The current study aims to identify the optimal physical parameters to provide valuable insight into achieving consistent and efficient combustion performance. The mathematical model representing the case study is derived based on mass, momentum, and energy conservation principles, focusing on a steady‐state regime. The solutions for the governing equations are approximated numerically using the spectral quasilinearization method (SQLM), offering accurate and computationally efficient predictions. The findings have significant implications for industrial applications, contributing to the design of safer and more sustainable combustion systems.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.290

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.003
GPT teacher head0.174
Teacher spread0.171 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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