Retrofitting a two-phase flow pressure drop model for PEM fuel cell flow channel bends

Author(s):  
Mehdi Mortazavi ◽  
Rebecca C. Shannon ◽  
Amir Abdollahpour
Author(s):  
Mehdi Mortazavi ◽  
Kazuya Tajiri

Proton exchange membrane (PEM) fuel cells produce power with water and heat as inevitable byproducts. Accumulated liquid water within gas channel blocks the reactant flow and cause pressure drop along the gas channel. It is of extreme importance to accurately predict the liquid and gas two-phase flow pressure drop in PEM fuel cell flow channels. This pressure drop can be considered as an in-situ diagnostic tool that reveals information about the amount of liquid water accumulated within the flow channels. In this paper, the two-phase flow pressure drops are measured in ex-situ PEM fuel cell parallel flow channels. The pressure drops were measured for air mass fluxes of 2.4–6.3kg/m2s and water mass fluxes of 0.0071–1.28kg/m2s. These mass fluxes correspond to 2–5.33m/s and 7.14 × 10−6 – 0.0012m/s air and water superficial velocities, respectively. The measured two-phase flow pressure drops are then compared with different two-phase flow pressure drop models. Qualitative and quantitative comparison between the experimental results and existing models is provided in this work.


Author(s):  
Mehdi Mortazavi ◽  
Jingru Benner ◽  
Anthony Santamaria

In this study, liquid-gas two-phase flow pressure drops were measured in an ex-situ PEM fuel cell test section. Pressure drop signatures were studied for three nominal air flow rates and different water flow rates within a flow channel. The pressure drop signatures showed an increasing trend at the beginning of the experiments which were followed by a drop to lower values before reaching uniform patterns. It was observed that as the water flow rate increased, the time interval at which pressure signatures reached uniform patterns decreased. In addition, a qualitative comparison with Mishima-Hibiki model [13] revealed that this two-phase flow pressure drop model showed the best prediction capability for the medium air flow rate used in this study, ∼300mℓ/min inflow channel, corresponding to ∼220 Reynolds number.


2011 ◽  
Vol 196 (19) ◽  
pp. 8031-8040 ◽  
Author(s):  
Ryan Anderson ◽  
David P. Wilkinson ◽  
Xiaotao Bi ◽  
L. Zhang

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