Optimization of a proton exchange membrane fuel cell membrane electrode assembly

A computational framework for fuel cell analysis and optimization is presented as an innovative alternative to the time consuming trial-and-error process currently used for fuel cell design. The framework is based on a two-dimensional through-the-channel isothermal, isobaric and single phase membrane electrode assembly (MEA) model. The model input parameters are the manufacturing parameters used to build the MEA: platinum loading, platinum to carbon ratio, electrolyte content and gas diffusion layer porosity. The governing equations of the fuel cell model are solved using Netwon’s algorithm and an adaptive finite element method in order to achieve near quadratic convergence and a mesh independent solution respectively. The analysis module is used to solve the optimization problem of finding the optimal MEA composition for maximizing performance. To solve the optimization problem a gradient-based optimization algorithm is used in conjunction with analytical sensitivities. By using a gradient-based method and analytical sensitivities, the framework presented is capable of solving a complete MEA optimization problem with state-of-the-art electrode models in approximately 30 min, making it a viable alternative for solving large-scale fuel cell problems.     

Towards new web services based supervisory systems in complex industrial organizations: Basic principles and case study

Mobility, cooperation and the information access of the different human actors within a complex industrial organization are some of the concerns of web-based HMI design. In this paper we highlight the application of some key concepts of web services for the specification and design of a complex supervisory web-based HMI. Hence, a novel approach based on a service oriented architecture and web services allowing flexible and transparent interaction between the field devices and human operators currently being considered is now possible. An overall design framework is presented and discussed. A real representative case study illustrating this approach is described and discussed from the human-machine interaction point of view, as well as further work.     

Electrothermal Monte Carlo simulation of submicron wurtzite GaN/AlGaN HEMTs

We present results from the simulation of the electrothermal behaviour of submicron wurtzite GaN/AlGaN High Electron Mobility Transistors (HEMTs). The simulator uses an iterative procedure which couples a Monte Carlo simulation with a fast Fourier series solution of the Heat Diffusion Equation (HDE). The results demonstrate the dependence of the extent of the thermal droop observed in the I_ds-V_ds characteristics and the device peak temperature on the device bias. The paper also investigates the effect of the inclusion of thermal self-consistency on the device microscopic properties and studies the dependence of the device electrothermal characteristics on the type of substrate material used.     

Thermo-hydrodynamic aspect analysis of flows in solar chimney power plants—A case study

The purpose of the work presented in this study is related to heat transfer and airflow modelling analysis in solar chimneys, according to some dominant parameters. A typical case of application is given in this study. It consists in analyzing a natural laminar convective heat transfer problem taking place in a chimney. Heat transfer and fluid dynamic aspects of the airflow, through an axis symmetric system in a dimensionless form, with well defined boundary conditions is thus examined. Results are related to the temperature distribution and the velocity field in the chimney and in the collector, determined by solving the energy equation, and the Navier–Stokes equations, using finite volume method. The numerical code based on this modelling is validated through the Vahl Davis benchmark solution for natural convection and to other authors for other cases.     

Computational modelling of polymer electrolyte membrane (PEM) fuel cells: Challenges and opportunities

Fuel cells are still undergoing intense development, and the combination of new and optimized materials, improved product development, novel architectures, more efficient transport processes, and design optimization and integration are expected to lead to major gains in performance, efficiency, reliability, manufacturability and cost-effectiveness. Computational fuel cell engineering (CFCE) tools that allow systematic simulation, design and optimization of fuel cell systems would facilitate the integration of such advances, allow less heavy reliance on hardware prototyping, and reduce development cycles.     

Development of a dynamic regenerative fuel cell system

The development of a regenerative Integrated Renewable Energy Experiment (IRENE) is presented. IRENE is a laboratory-scale distributed energy system with a modular structure which can be re-configured to test newly developed components for generic regenerative systems integrating renewable energy, electrolysis, hydrogen and electricity storage and fuel cells. A special design feature of this test bed is the ability to accept transient inputs from and provide transient loads to real devices as well as from simulated energy sources/sinks. The findings of this study should be of interest to developers of small-scale renewable-regenerative systems intended to displace fossil fuel systems.     

State-dependent packet scheduling for QoS routing in a dynamically changing environment

The packet scheduling in router plays an important role in the sense to achieve QoS differentiation and to optimize the queuing delay, in particular when this optimization is accomplished on all routers of a path between source and destination. In a dynamically changing environment a good scheduling discipline should be also adaptive to the new traffic conditions. We model this problem as a multi-agent system in which each agent learns through continual interaction with the environment in order to optimize its own behaviour. So, we adopt the framework of Markov decision processes applied to multi-agent system and present a pheromone-Q learning approach which combines the Q-multi-learning technique with a synthetic pheromone that acts as a communication medium speeding up the learning process of cooperating agents.     

Chemometric Characterization of Eight Monovarietal Algerian Virgin Olive Oils

Differences in triacylglycerol, fatty acid, squalene, and tocopherol compositions were demonstrated between 8 varieties of virgin olive oils (Aberkane, Aguenaou, Aharoun, Aimel, Bouchouk Guergour, Bouichret, Chemlal, and Sigoise) from Petite Kabylie area, north eastern Algeria. Fatty acid and triacylglycerol morphotypes characterized each variety. A principal component analysis, based on triacylglycerol, fatty acid, and squalene compositions, differentiates between varieties. Minor fatty acids and squalene, usually not taken into account individually in authentication studies, are strongly involved in this differentiation, whereas the discriminant power of tocopherols is weak. Soft Independent Modeling of Class Analogy classification using chemical compositions as variables showed a high potential to authenticate the varietal origin of Algerian virgin olive oils.