Optimization of Design Parameters for an Open-cathode Polymer Electrolyte Fuel Cells Stack Utilizing Taguchi Method
Bibliographic record
Abstract
The design of open-cathode polymer electrolyte fuel cells (PEFC) stacks with forced-convection requires a careful consideration on the geometrical and operating conditions as well as the characteristic of PEFC stacks and fan used. The operating point should be located at the intersection point between the fan and the stack characteristic curve. This paper evaluates the effect of key parameters and operating conditions on the system characteristic and stack performance of forced convection PEFC by utilizing computational fluid dynamic approach and Taguchi statistical method. A validated three dimensional open-cathode PEFC stack model with fan and immediate ambient were employed together with an L 27 orthogonal array (OA) of Taguchi matrix of six factors and three level designs to determine the optimum combination of parameters as well as their interactions. The result indicates that fuel cell length plays important role on determining the fuel cell performance in term of current density and net power. Optimum combination of design and operating parameters were obtained with the objective function of maximizing net power generated by stack by taking into account the parasitic loads.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".