Steady and Unsteady Modeling of Single PEMFC with Detailed Thermoelectrochemical Model
Bibliographic record
Abstract
A steady and unsteady water and thermal model was developed to consider the effects of local pressure on the cell performance, pressure drop, open-circuit voltage variation with stack temperature, and water-vapor effects on membrane conductivity. These considerations made the model physically more reasonable as well as more suitable for various operating conditions. Additionally, this model combined the along-flow-channel model and catalyst layer model, which represent a significant improvement to proton exchange membrane fuel cell (PEMFC) modeling. The model could predict the distributions of a series of important parameters along the flow channel and in the catalyst layer. Furthermore, the transient performance of the fuel cell can be simulated with this model. The modeling results agreed reasonably with the available experimental results from the literature. The results show that the humidification of both anode and cathode is very important for the performance of PEMFC which could also be improved by increasing the flow inlet temperatures within a reasonable range. Pressure loss is one of the important parameters that affect total system efficiency and optimization. This model could be used as part of a PEMFC stack or entire system modeling.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".