Thermal analysis of air-cooled fuel cells
Bibliographic record
Abstract
Temperature distribution in a fuel cell significantly affects the performance and efficiency of the fuel cell system. Particularly, in low temperature fuel cells, improvement of the system requires proper thermal management, which indicates the need for developing accurate thermal models. In this study, a 3D numerical thermal model is presented to analyze the heat transfer and predict the temperature distribution in air-cooled proton exchange membrane fuel cells (PEMFC). In the modeled fuel cell stack, forced air flow supplies oxidant as well as cooling. Conservation equations of mass, momentum, and energy are solved in the oxidant channel, while energy equation is solved in the entire domain, including the gas diffusion layers and separator plates, which play a significant role in heat transfer. Parametric studies are performed to investigate the effects of various properties and operating conditions on the maximum cell temperature. The present results are further validated with experiment. This model provides a theoretical foundation for thermal analysis of air-cooled PEMFC stacks, where temperature non-uniformity is high and thermal management and stack cooling is a significant challenge.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".