Fracture Properties of Fuel Cell Membranes
Bibliographic record
Abstract
Understanding the crack propagation behavior of common perfluorosulfonic acid (PFSA) ionomer membranes under hygrothermal and mechanical cyclic loading is of vital significance in designing more durable fuel cell stacks (1). Hence, we have developed a test procedure to shed light on the crack propagation characteristics of membranes as a function of loading and environmental conditions. Rectangular specimens with a width of 10 mm and cracks with an average length of 0.7 mm on both sides are used. The specimens are placed under cyclic mechanical loading in a controlled level of environmental conditions (temperature and humidity). The crack propagation rate in the membrane is measured as a function of temperature, humidity and the amplitude of mechanical loading (Figure 1). It is found that a small linear decrease in the magnitude of the force results in an exponential decrement in the crack propagation rate. Furthermore, for a given state of mechanical load, it is found that increasing the relative humidity and/or temperature can significantly increase the crack propagation rate. In a parallel study, a fracture mechanics-based model capable of simulating the in-situ crack initiation and propagation in the membrane during fuel cell operation is also developed. The elastic-viscoplastic nature of PFSA membranes is well-established in (2). A finite element method (FEM) based constitutive model that can simulate this behavior is used to relate the stress and strain at different environmental conditions (3). Numerical simulations reveal the presence of cyclic mechanical stresses within the membrane due to dynamic hygrothermal conditions present in a running fuel cell that can cause the initiation and propagation of cracks through mechanical membrane degradation. The dynamic stress-field thus obtained is coupled with the fracture mechanics model. In-situ test cases for various temperature, humidity and strain rate conditions are run to fully understand their effect on crack propagation rates and ultimate failure of the membranes. Acknowledgements: This research is supported by Ballard Power Systems and the Natural Sciences and Engineering Research Council of Canada through an Automotive Partnership Canada (APC) grant. References 1. R. Borup, J. Meyers, B. Pivovar, Y. S. Kim, R. Mukundan et al, Chem. Rev. 107 3925 (2007). 2. M.A. Goulet, R.M.H. Khorasany, C. De Torres, M. Lauritzen, E. Kjeang, G.G. Wang, N. Rajapakse, J. Power Sources 234 38 (2013). 3. R.M.H. Khorasany, M.A. Goulet, A.S. Alavijeh, E. Kjeang, G.G. Wang, R.K.N.D. Rajapakse, J. Power Sources 252 176 (2014).
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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) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".