Modeling and simulation of micro direct methanol Fuel Cells

Fuel cells have unique technological attributes: efficiency, absence of moving parts and low emissions. The Direct Methanol Fuel Cell (DMFC) has attracted much attention due to its potential applications as a power source for transportation and portable electronic devices. With the advance of micromachining technologies, miniaturization of power sources became one of the trends of evolution of research in this area. Based on the advantages of the scaling laws, miniaturization promises higher efficiency and performance of power generating devices, so, MicroDMFC is an emergent technology. Models play an important role in fuel cell development since they facilitate a better understanding of parameters affecting the performance of fuel cells. In this work, a steady state, one-dimensional model accounting for coupled heat and mass transfer, along with the electrochemical reactions occurring in a fuel cell, already developed and validated for DMFC in [1-3], is used to predict Micro DMFC performance. The model takes in account all relevant phenomena occurring in a DMFC. Polarization curves predicted by the model are compared with experimental data existing in literature and the model shows good agreement, mainly for lower current densities. The model is used to predict some important parameters to analyze fuel cell performance, such as water transport coefficient and leakage current density. This easily to implement simplified model is suitable for use in real-time MicroDMFC simulations

Experimental and modeling studies of a micro direct methanol fuel cell

The Direct Methanol Fuel Cell (DMFC) has attracted much attention due to its potential applications as a power source for transportation and portable electronic devices. Based on the advantages of the scaling laws, miniaturization promises higher efficiency and performance of power generating devices and the MicroDMFC is therefore an emergent technology. In this work, a set of experiments with a MicroDMFC of 2.25 cm2 active area are performed in order to investigate the effect of important operating parameters. Maximum power density achieved was 32 mW/cm2 using a 4 M methanol concentration at room temperature. Polarization curves are compared with mathematical model simulations in order to achieve a better understanding of how parameters affect performance. The one-dimensional model used in this work takes in account coupled heat and mass transfer, along with the electrochemical reactions occurring in a direct methanol fuel cell and was already developed and validated for DMFC in previous work by Oliveira et al. [1–3]. The model is also used to predict some important parameters to analyze fuel cell performance, such as water transport coefficient and methanol crossover. This easy to implement simplified model is suitable for use in real-time MicroDMFC simulations. More experimental data are also reported bearing in mind the insufficient experimental data available in literature at room temperature, a goal condition to use this technology in portable applications

Heat and mass transfer effects in direct methanol fuel cell: 1D model

Models play an important role in fuel cell development since they facilitate a better understanding of parameters affecting the performance of fuel cells and fuel cells systems. In this work, a steady state, one-dimensional model accounting for coupled heat and mass transfer, along with the electrochemical reactions occurring in the DMFC is presented. The model accounts for the kinetics of the multi-step methanol oxidation at the anode while the kinetics of the cathodic oxygen reduction is modelled using the Tafel equation. Two-phase flow effects are neglected. The anode and cathode flow channels are treated using the continuous stirred tank reactor (CSTR) approach. The cell voltage expression incorporates the anodic and cathodic overpotentials as well as the ohmic losses across the membrane. The mixed potential of the cathode due to methanol crossover is also included. The reactions in the catalyst layers are considered homogeneous. Pressure gradients across the layers are assumed as negligible. Methanol and water transport through the membrane is assumed to be due to the combined effect of the concentration gradient and electro-osmotic force. Mass transport in the diffusion layers and membrane is described using effective Fick models. Local equilibrium at interfaces is represented by partition functions. The methanol flux in the cathode catalyst layer is considered as well as methanol crossover. The transport of heat through the gas diffusion layers is assumed to be a conduction-dominated process. The thermal conductivity for all the materials is assumed to be constant. Heat generation is considered in the catalyst layers. The analytical solutions for concentration and temperature across the cell are compared with recently data existing in literature and with in-house obtained results, for a wide range of operating conditions. The model shows very good agreement. This easily implemented simplified model is suitable for use in real-time DMFC simulation

Review on micro-direct methanol fuel cells

Fuel cells have unique technological attributes: efficiency, minimization of moving parts and low emissions. The Direct Methanol Fuel Cell (DMFC) has attracted much attention due to its potential applications as a power source for transportation and portable electronic devices. With the advance of micromachining technologies, miniaturization of power sources became one of the trends of evolution of research in this area. Based on the advantages of the scaling laws, miniaturization promises higher efficiency and performance of power generating devices, therefore, Micro-DMFC is an emergent technology. There has been a growing interest in the development of this type of micro cells in the last years, resulting both in experimental studies (operating conditions, cell design and new materials) and in modeling studies. Despite the increase in the knowledge acquired, many challenges are still to be reached. This book provides a detailed comprehensive review both on fundamental and technological aspects of Micro-DMFC. Special attention is devoted to systematization of published results on experimental area and also to a special section dedicated to modeling studies

Avaliação genética de progênies e indivíduos de açaizeiro para número de perfilhos e índice de produtividade volumétrica de palmito.

Este trabalho teve como objetivo a avaliação genotípica de progênies e indivíduos de uma população de açaizeiro e estimação de parâmetros genéticos para os caracteres número de perfilhos e índice de produtividade volumétrica de palmito nos perfilhos

Estimativas de parâmetros genéticos e ganhos de seleção em progênies de polinização aberta de açaizeiro.

O presente trabalho teve como objetivos estudar a variabilidade genética, estimar parâmetros genéticos e fenotípicos, e realizar a predição de valores genéticos dos indivíduos de açaizeiro irrigado no Estado do Pará, utilizando a metodologia BLUP/REML a partir da avaliação de progênies com base nos caracteres altura do primeiro cacho (APC), peso total do cacho (PTC), peso total de frutos (PTF), número de cachos (NC), peso médio do cacho (PMC), comprimento médio da ráquis (CMR), número médio de ráquilas (NMR), número de perfilhos (NP) e peso médio de cem frutos (P100). Cinqüenta progênies foram avaliadas em dois látices 5 x 5 com duas repetições e parcelas lineares de cinco plantas cada, no espaçamento de 5 m x 5 m. O programa computacional Selegen- Reml/ Blup foi utilizado para as análises genéticas e a identificação dos melhores indivíduos para compor a população de produção de sementes para um programa a curto prazo e a de melhoramento para um programa a longo prazo. As correlações genotípicas de maiores magnitudes foram aquelas envolvendo o peso total de frutos e peso total do cacho, peso total do cacho e número de cacho e peso total de fruto e número de cacho, indicando que a seleção para peso total de frutos pode ser realizada por meio da seleção daquela de mais fácil seleção. As estimativas dos parâmetros genéticos obtidos revelam excelente potencial seletivo da população e variabilidade genética suficiente para o melhoramento genético da população a curto e longo prazos. Ganho genético considerável de 45,33% em relação à média do experimento pode ser obtido com a seleção dos 20 melhores indivíduos para o caráter produção total de frutos

Estimativas de parâmetros genéticos e ganhos de seleção em progênies de polinização aberta do açaizeiro.

O presente trabalho teve como objetivos estudar a variabilidade genética, estimar parâmetros genéticos e fenotípicos, e realizar a predição de valores genéticos dos indivíduos de açaizeiro irrigado no Estado do Pará, utilizando a metodologia BLUP/REML a partir da avaliação de progênies com base nos caracteres altura do primeiro cacho (APC), peso total do cacho (PTC), peso total de frutos (PTF), número de cachos (NC), peso médio do cacho (PMC), comprimento médio da ráquis (CMR), número médio de ráquilas (NMR), número de perfilhos (NP) e peso médio de cem frutos (P100). Cinqüenta progênies foram avaliadas em dois látices 5 x 5 com duas repetições e parcelas lineares de cinco plantas cada, no espaçamento de 5 m x 5 m. O programa computacional Selegen- Reml/Blup foi utilizado para as análises genéticas e a identificação dos melhores indivíduos para compor a população de produção de sementes para um programa a curto prazo e a de melhoramento para um programa a longo prazo. As correlações genotípicas de maiores magnitudes foram aquelas envolvendo o peso total de frutos e peso total do cacho, peso total do cacho e número de cacho e peso total de fruto e número de cacho, indicando que a seleção para peso total de frutos pode ser realizada por meio da seleção daquela de mais fácil seleção. As estimativas dos parâmetros genéticos obtidos revelam excelente potencial seletivo da população e variabilidade genética suficiente para o melhoramento genético da população a curto e longo prazos. Ganho genético considerável de 45,33% em relação à média do experimento pode ser obtido com a seleção dos 20 melhores indivíduos para o caráter produção total de fruto

A Q-Ising model application for linear-time image segmentation

A computational method is presented which efficiently segments digital grayscale images by directly applying the Q-state Ising (or Potts) model. Since the Potts model was first proposed in 1952, physicists have studied lattice models to gain deep insights into magnetism and other disordered systems. For some time, researchers have realized that digital images may be modeled in much the same way as these physical systems (i.e., as a square lattice of numerical values). A major drawback in using Potts model methods for image segmentation is that, with conventional methods, it processes in exponential time. Advances have been made via certain approximations to reduce the segmentation process to power-law time. However, in many applications (such as for sonar imagery), real-time processing requires much greater efficiency. This article contains a description of an energy minimization technique that applies four Potts (Q-Ising) models directly to the image and processes in linear time. The result is analogous to partitioning the system into regions of four classes of magnetism. This direct Potts segmentation technique is demonstrated on photographic, medical, and acoustic images.Comment: 7 pages, 8 figures, revtex, uses subfigure.sty. Central European Journal of Physics, in press (2010