Investigation of Water Transport Within a Proton Exchange Membrane Fuel Cell by Diffusion Layer Saturation Analysis
Bibliographic record
Abstract
Diffusion layer saturation analysis (DLSA) is introduced in order to further investigate water transport within the cell. The analysis relies on two separate experimental processes. First, an ex-situ investigation of the relative humidity of the gas streams and their resulting pressure drop is performed. Next, multiple variables of the cathode and anode gas streams are manipulated in-situ to create an evaporative driving force to remove water out of the porous layers. Multiple gas stream settings are investigated as well as the temperature set point of the cell. The ex-situ pressure drop data is used to infer how much water is being removed from the system and to begin to estimate an overall water balance. Multiple cathode and anode GDL configurations are tested in order to further investigate initial saturation conditions of the GDLs. By coupling the voltage results to the calculated water removed from the system, it can be seen which configurations had low initial voltage due to GDL oversaturation. The potential for DLSA both as a diagnostic tool and an investigative technique into multiphase flow in the porous layer is demonstrated.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".