No abstract

Solid oxide fuel cell (SOFC) systems can be fueled by natural gas when the reforming reaction is conducted in a stack. Due to its maturity and safety, indirect internal reforming is usually used. A strong endothermic methane/steam reforming process needs a large amount of heat, and it is convenient to provide thermal energy by burning the remainders of fuel from a cell. In this work, the mathematical model of afterburner-powered methane/steam reformer is proposed. To analyze the effect of a fuel composition on SOFC performance, the zero-dimensional model of a fuel cell connected with a reformer is formulated. It is shown that the highest efficiency of a solid oxide fuel cell is achieved when the steam-to-methane ratio at the reforming reactor inlet is high. List of symbols a, b reaction orders, (-)Tafel equation coefficients, (V) C p constant pressure specific heat, (J molFaraday constant, F = 96485.3329 C mol −1Marcin Mozdzierz

No abstract

Segmentation of images from scanning electron microscope, especially multiphase, poses a drawback in their microstructure quantification process. The labeling process must be automatized due to the time consumption and irreproducibility of the manual labeling procedure. Here we show a swarm intelligence-driven filtration methodology performed on raw solid oxide fuel cell anode’s material images to improve the segmentation methods’ performance. The methodology focused on two significant parts of the segmentation process, which are filtering and labeling. During the first one, the images underwent filtering by applying a series of filters, whose operation parameters were determined using Particle Swarm Optimization upon a dedicated cost function. Next, Seeded Region Growing, k-Means Clustering, Multithresholding, and Simple Linear Iterative Clustering Superpixel algorithms were utilized to label the filtered images’ regions into consecutive phases in the microstructure. The improvement was presented for three different metrics: the Misclassification Ratio, Structural Similarity Index Measure, and Mean Squared Error. The obtained distribution of metrics’ performances was based on 200 images, with and without filtering. Results indicate an improvement up to 29%, depending on the metric and method used. The presented work contributes to the ongoing efforts to automatize segmentation processes fully for an increasing number of tomographic measurements, particularly in solid oxide fuel cell research.