WATER TRANSPORT THROUGH POROUS MEDIA AND IN FLOW CHANNELS OF PROTON EXCHANGE MEMBRANE FUEL CELL

Proton exchange membrane (PEM) fuel cell has been known as a promising power source for different applications such as automotive, residential and stationary. During the operation of a PEM fuel cell, hydrogen is oxidized in anode and oxygen is reduced in the cathode to produce the intended power. Water and heat are inevitable byproducts of these reactions. The water produced in the cathode should be properly removed from inside the cell. Otherwise, it may block the path of reactants passing through the gas channels and/or gas diffusion layer (GDL). This deteriorates the performance of the cell and eventually can cease the operation of the cell. Water transport in PEM fuel cell has been the subject of this PhD study. Water transport on the surface of the GDL, through the gas flow channels, and through GDL has been studied in details. For water transport on the surface of the GDL, droplet detachment has been measured for different GDL conditions and for anode and cathode gas flow channels. Water transport through gas flow channels has been investigated by measuring the two-phase flow pressure drop along the gas flow channels. As accumulated liquid water within gas flow channels resists the gas flow, the pressure drop increases along the flow channels. The two-phase flow pressure drop can reveal useful information about the amount of liquid water accumulated within gas flow channels. Liquid water transport though GDL has also been investigated by measuring the liquid water breakthrough pressure for the region between the capillary fingering and the stable displacement on the drainage phase diagram. The breakthrough pressure has been measured for different variables such as GDL thickness, PTFE/Nafion content within the GDL, GDL compression, the inclusion of a micro-porous layer (MPL), and different water flow rates through the GDL. Prior to all these studies, GDL microstructural properties have been studied. GDL microstructural properties such as mean pore diameter, pore diameter distribution, and pore roundness distribution have been investigated by analyzing SEM images of GDL samples.

Sonic log prediction in carbonates

This work is conducted to study the complications associated with the sonic log prediction in carbonate logs and to investigate the possible solutions to accurately predict the sonic logs in Traverse Limestone. Well logs from fifty different wells were analyzed to define the mineralogy of the Traverse Limestone by using conventional 4-mineral and 3-mineral identification approaches. We modified the conventional 3-mineral identification approach (that completely neglects the gamma ray response) to correct the shale effects on the basis of gamma ray log before employing the 3-mineral identification. This modification helped to get the meaningful insight of the data when a plot was made between DGA (dry grain density) and UMA (Photoelectric Volumetric Cross-section) with the characteristic ternary diagram of the quartz, calcite and dolomite. The results were then compared with the 4-mineral identification approach. Contour maps of the average mineral fractions present in the Traverse Limestone were prepared to see the basin wide mineralogy of Traverse Limestone. In the second part, sonic response of Traverse Limestone was predicted in fifty randomly distributed wells. We used the modified time average equation that accounts for the shale effects on the basis of gamma ray log, and used it to predict the sonic behavior from density porosity and average porosity. To account for the secondary porosity of dolomite, we subtracted the dolomitic fraction of clean porosity from the total porosity. The pseudo-sonic logs were then compared with the measured sonic logs on the root mean square (RMS) basis. Addition of dolomite correction in modified time average equation improved the results of sonic prediction from neutron porosity and average porosity. The results demonstrated that sonic logs could be predicted in carbonate rocks with a root mean square error of about 4μsec/ft. We also attempted the use of individual mineral components for sonic log prediction but the ambiguities in mineral fractions and in the sonic properties of the minerals limited the accuracy of the results.