MétaCan
Menu
← Back to cohort
Record W4391663218 · doi:10.1149/ma2023-02391922mtgabs

In-Situ Fatigue Lifetime Modeling of a Reinforced Membrane by Projecting Critical Accumulated Plastic Dissipation Energy from Pressure Differential-Accelerated Mechanical Stress Tests

2023· article· en· W4391663218 on OpenAlexaffabout
Mohsen Mazrouei Sebdani, Heather Baroody, Erik Kjeang

Bibliographic record

VenueECS Meeting Abstracts · 2023
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsDissipationDifferential stressIn situMaterials scienceDifferential (mechanical device)Stress (linguistics)MechanicsStructural engineeringComposite materialPhysicsEngineeringThermodynamicsDeformation (meteorology)

Abstract

fetched live from OpenAlex

Polymer electrolyte fuel cells (PEFCs) have become increasingly appealing over internal combustion engines because of their high efficiency, low operating temperature, and zero CO2 emissions. Nevertheless, the transportation sector necessitates high durability and reliability, which may be difficult to predict for emerging technologies. A crucial aspect is the ability of the thin membranes that conduct ions in PEFCs to endure the chemical and mechanical stresses that arise during dynamic operations. For mechanical fatigue, temperature and relative humidity (RH) fluctuations induce dynamic stresses that lead to the formation and propagation of microcracks in the membrane. As the membrane is confined by other components in the membrane-electrode assembly (MEA), changes in temperature and humidity can generate thermal and swelling strains in the membrane, leading to dynamic and residual stresses [1]. The US Department of Energy sets a passing criterion of 20,000 RH cycles for mechanical fatigue assessment. However, many modern reinforced membranes have already passed this threshold without failing [2]. Therefore, Ref [3] introduced a pressure differential between the cathode and anode sides of the membrane at 80°C to speed up the testing. In this research, the pressure differential-accelerated mechanical stress test (ΔP-AMST) method was applied to a reinforced membrane at two different temperatures and with four times faster humidity cycles in a wider range of ΔPs. This objective is to project the mechanical fatigue lifetime from the ΔP-AMST to the membrane under its in-situ conditions by using the critical accumulated plastic dissipation energy (CAPDE) in ΔP-AMSTs and the plastic dissipation energy (PDE) during a single cycle of humidity that the membrane experiences under complete fuel cell settings. The first step involves performing a series of ∆P-AMST, and in the second step, a finite element model (FEM) for ∆P-AMST based on the developed constitutive model for the tensile tests that covers temperature, humidity, and swelling strain impacts is built, and therefore its S-N curve is extracted. Next, a FEM model for a complete fuel cell is created, and the mechanical fatigue life is estimated by dividing the CAPDE in ∆P-AMST by the PDE in one cycle of the in-situ modeled membrane by considering amplitude stress as a link between the full fuel cell model and ∆P-AMST, as illustrated in Figure 1 and verified by previous studies [4,5]. In the final step, we will also discuss opportunities to integrate the present mechanical fatigue model with a chemical degradation module to simulate its impacts on fatigue lifetime. This integration includes the two main effects of chemical degradation, which are reflected in the thickness of the reinforced membrane [6] and its updated CAPDE [7]. Acknowledgments The authors gratefully acknowledge AVL Fuel Cell Canada and Mitacs for supporting this project. The authors also thank Roger Penn and Amy Nelson for technical advice. References [1] Alavijeh AS, Bhattacharya S, Thomas O, Chuy C, Yang Y, Zhang H, et al. Effect of hygral swelling and shrinkage on mechanical durability of fuel cell membranes. J Power Sources 2019;427:207–14. [2] Rodgers MP, Bonville LJ, Mukundan R, Borup RL, Ahluwalia R, Beattie P, et al. Perfluorinated sulfonic acid membrane and membrane electrode assembly degradation correlating accelerated stress testing and lifetime testing. ECS Trans 2013;58:129. [3] Alavijeh AS, Bhattacharya S, Thomas O, Chuy C, Kjeang E. A rapid mechanical durability test for reinforced fuel cell membranes. J Power Sources Adv 2020;2:100010. [4] Chen J, Goshtasbi A, Soleymani AP, Ricketts M, Waldecker J, Xu C, et al. Effects of cycle duration and test hardware in relative humidity cycling of a polymer electrolyte membrane. J Power Sources 2020;476:228576. [5] Hasan M, Chen J, Waldecker JR, Santare MH. Predicting fatigue lifetimes of a reinforced membrane in polymer electrolyte membrane fuel cell using plastic energy. J Power Sources 2022;539:231597. [6] Liu H, Chen J, Hissel D, Hou M, Shao Z. A multi-scale hybrid degradation index for proton exchange membrane fuel cells. J Power Sources 2019;437:226916. [7] Sun X, Shi S, Fu Y, Chen J, Lin Q, Hu J, et al. Embrittlement induced fracture behavior and mechanisms of perfluorosulfonic-acid membranes after chemical degradation. J Power Sources 2020;453:227893. Figure 1

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.024
GPT teacher head0.262
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueECS Meeting Abstracts→Same topicFuel Cells and Related Materials→French-language works237,207→