0000000001219848
AUTHOR
Sasanka N. Ranasinghe
Modelling of single cell solid oxide fuel cells using COMSOL multiphysics
Solid oxide fuel cells (SOFCs) have the potential to become one of the efficient and cost effective systems for direct conversion of a wide variety of fuels to electricity. In this study, we developed a three-dimensional multiphysics model for a single cell SOFC using COMSOL multiphysics (version 5.2) software and performed simulations to examine the effect of gas flow patterns (radial flow and counter flow) in different operating temperatures (700° C, 800° C and 1000° C) for a planar anode supported SOFC. With the help of the simulation results, we have analyzed the electrical characteristics of the single cell SOFCs. From the simulation results, it is observable that the radial gas flow p…
Performance analysis of single cell solid oxide fuel cells
Solid oxide fuel cells (SOFCs) are a class of fuel cells operating on high temperatures which have the potential to become one of the efficient and cost effective system for direct conversion of a wide variety of fuels to electricity. For proper operation of SOFCs, evaluation of cell stability and optimization of fuel utilization is of paramount importance. In this paper, we have performed experiments to obtain current-voltage (I–V) characteristics by using three different Hydrogen (H 2 ) flow rates(100 ml/min, 150 ml/min and 200 ml/min). Furthermore, we perform oxidation and reduction (redox) cycles to determine how many redox cycles a SOFC can withstand without cracking the cell which we …
Intrusion Detection with Interpretable Rules Generated Using the Tsetlin Machine
The rapid deployment in information and communication technologies and internet-based services have made anomaly based network intrusion detection ever so important for safeguarding systems from novel attack vectors. To this date, various machine learning mechanisms have been considered to build intrusion detection systems. However, achieving an acceptable level of classification accuracy while preserving the interpretability of the classification has always been a challenge. In this paper, we propose an efficient anomaly based intrusion detection mechanism based on the Tsetlin Machine (TM). We have evaluated the proposed mechanism over the Knowledge Discovery and Data Mining 1999 (KDD’99) …