Parametric modeling of microbial fuel cells

Microbial fuel cells use bacteria to generate electrical energy and are used for lower power density applications. This paper studies the effect of operational parameters on the performance of a microbial fuel cell. The effect of length of the anode compartment, inlet acetate concentration, acetate flow rate, temperature, thickness of the membrane and bio-film conductivity on the performance of the fuel cell is modeled. The thickness of the membrane is found to play a very limiting role in affecting the performance of the fuel cell. However, the length of the anode compartment, acetate flow rate and bio-film conductivity are found to play a significant role in the performance of the fuel cell. Model results are compared with experimental data and found to compare well

Modeling the effect of rib and channel dimensions on the performance of high temperature fuel cells-parallel configuration

This work investigates the effect of rib width, channel width and channel depth on the performance of a high temperature proton exchange membrane (HT-PEM) fuel cell with parallel flow field configuration. Simulation results indicate that the rib width has the maximum impact on the performance of the fuel cell. The lower the rib width, the better is performance of HT-PEM fuel cell. Changing the channel width seems to have a moderate effect, while changing the channel depth seems to have very limited impact on the fuel cell performance. The effect of various rib width and channel dimensions on the pressure drop across the channel is also studied. The concentration profile of the oxygen across the cathode gas channel is modeled as a function of the channel width and depth. Modeling results are found to be in well agreement with experimental data

Modelling the effect of anode particle radius and anode reaction rate constant on capacity fading of Li-ion batteries

This paper investigates the effect of anode particle radius and anode reaction rate constant on the capacity fading of lithium-ion batteries. It is observed through simulation results that capacity fade will be lower when the anode particle size is smaller. Simulation results also show that when reaction rate constant is highest, the capacity loss is the lowest of lithium-ion battery. The potential drop across the SEI layer (solid electrolyte interphase) is studied as a function of the anode particle radius and anode reaction rate constant. Modelling results are compared with experimental data and found to compare well

Modelling the leakage current in a solid oxide fuel cell with bi-layer electrolyte

A mathematical model is developed to study the leakage current in a solid oxide fuel cell (SOFC) with a bi-layer electrolyte. The model predicts the variation of leakage current and power density with various design and operating factors of SOFC, namely thickness of the bi-layer electrolyte, operating temperature and operating cell voltage. The interfacial oxygen pressure in SOFC is also studied as a function of the thickness of YSZ layer. Modelling results are compared with experimental data and found to compare well

Multimapper: Data Density Sensitive Topological Visualization

Mapper is an algorithm that summarizes the topological information contained in a dataset and provides an insightful visualization. It takes as input a point cloud which is possibly high-dimensional, a filter function on it and an open cover on the range of the function. It returns the nerve simplicial complex of the pullback of the cover. Mapper can be considered a discrete approximation of the topological construct called Reeb space, as analysed in the $1$-dimensional case by [Carriere et al.,2018]. Despite its success in obtaining insights in various fields such as in [Kamruzzaman et al., 2016], Mapper is an ad hoc technique requiring lots of parameter tuning. There is also no measure to quantify goodness of the resulting visualization, which often deviates from the Reeb space in practice. In this paper, we introduce a new cover selection scheme for data that reduces the obscuration of topological information at both the computation and visualisation steps. To achieve this, we replace global scale selection of cover with a scale selection scheme sensitive to local density of data points. We also propose a method to detect some deviations in Mapper from Reeb space via computation of persistence features on the Mapper graph.Comment: Accepted at ICDM