Coupling of Lattice Boltzmann and Volume of Fluid Approaches to Study the Droplet Behavior at the Gas Diffusion Layer/Gas Channel Interface
Bibliographic record
Abstract
With the increased concern about energy security, global warming, and air pollution, the possibility of using polymer electrolyte fuel cells (PEFCs) in approaching renewable and sustainable energy systems has reached significant momentum [1,2]. A typical PEFC flow field consists of a series of micro/minichannels. The continuous removal of liquid water from the cathode channels is a critical issue, as water droplets forming in the channels can block the transport of gaseous oxygen to the active sites. This phenomenon gives not only an uneven current distribution, substantial loss of performance, but also, unstable operation and increased degradation rates [1]. Water generated by the electrochemical reactions often condenses into liquid form, potentially flooding the GC (gas channel), the GDL (gas diffusion layer), the micro porous layer (MPL) and the catalyst layer. Insight into the fundamental processes of liquid water transport and evolution is still not complete, preventing further FC development [1]. Computational fluid dynamics (CFD) models make it possible to reduce the number of experiments needed for cell design and development [1,3]. The aim of this work is to obtain an increased understanding of the droplet behavior at the GDL/GC interface by coupling of Lattice Boltzmann and Volume of Fluid (VOF) approaches, for gas channels relevant for PEFCs. The VOF model is an interface-resolving method and has become a widespread methodology for solving two-phase flow phenomena inside PEFCs. The volume fraction of liquid water at the computational cell volume schemes, are used to track the interface between the phases [1,3]. Input parameters in the VOF model are extracted from our in-house Lattice Boltzmann calculations [4], i.e., establishing a multiscale environment. It is clear that the contact angle as well as the size of the liquid droplet vary with positions at the interface, depending on the stochastic GDL geometry. A model describing one straight channel with one gas inlet, one liquid inlet (at the GDL surface) and one two-phase outlet is developed. The operating parameters belong to the laminar flow regime. Notice that a developing flow region covers the entire channel. The uniqueness of this work includes a calculation of contact angles at the GDL interface as well as the size of the liquid inlet, by the authors, with Lattice Boltzmann calculations (3D nineteen-velocity (D3Q19) pseudopotential multiphase multicomponent isothermal LBM) [4]. References [1] M. Andersson, S. Beale, M. Espinoza, Z. Wu, W. Lehnert, A Review of Cell-Scale Multiphase Flow Modelling, including Water Management, in Polymer Electrolyte Fuel Cells, Applied Energy, 180, 757–778, 2016 [2] S.B. Beale, U. Reimer, D. Froning, H. Jasak, M. Andersson, J. Pharoah, W. Lehnert, Stability Issues for Fuel Cell Models in the Activation and Concentration Regimes, Journal of Electrochemical Energy Conversion and Storage, 2018 (in press) [3] M. Andersson, S.B. Beale, U. Reimer, W. Lehnert, D. Stolten, Interface resolving two-phase flow simulations in gas channels relevant for polymer electrolyte fuel cells using the volume of fluid approach, International Journal of Hydrogen Energy 43, 2961-2976, 2018 [4] J. Yu, D. Froning, U. Reimer, W. Lehnert, Apparent contact angles of liquid water droplet breaking through a gas diffusion layer of polymer electrolyte membrane fuel cell, International Journal of Hydrogen Energy 43, 6318-6330, 2018
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".