Matching Items (3)
Filtering by
- All Subjects: engineering
Description
Portable devices rely on battery systems that contribute largely to the overall device form factor and delay portability due to recharging. Membraneless microfluidic fuel cells are considered as the next generation of portable power sources for their compatibility with higher energy density reactants. Microfluidic fuel cells are potentially cost effective and robust because they use low Reynolds number flow to maintain fuel and oxidant separation instead of ion exchange membranes. However, membraneless fuel cells suffer from poor efficiency due to poor mass transport and Ohmic losses. Current microfluidic fuel cell designs suffer from reactant cross-diffusion and thick boundary layers at the electrode surfaces, which result in a compromise between the cell's power output and fuel utilization. This dissertation presents novel flow field architectures aimed at alleviating the mass transport limitations. The first architecture provides a reactant interface where the reactant diffusive concentration gradients are aligned with the bulk flow, mitigating reactant mixing through diffusion and thus crossover. This cell also uses porous electro-catalysts to improve electrode mass transport which results in higher extraction of reactant energy. The second architecture uses porous electrodes and an inert conductive electrolyte stream between the reactants to enhance the interfacial electrical conductivity and maintain complete reactant separation. This design is stacked hydrodynamically and electrically, analogous to membrane based systems, providing increased reactant utilization and power. These fuel cell architectures decouple the fuel cell's power output from its fuel utilization. The fuel cells are tested over a wide range of conditions including variation of the loads, reactant concentrations, background electrolytes, flow rates, and fuel cell geometries. These experiments show that increasing the fuel cell power output is accomplished by increasing reactant flow rates, electrolyte conductivity, and ionic exchange areas, and by decreasing the spacing between the electrodes. The experimental and theoretical observations presented in this dissertation will aid in the future design and commercialization of a new portable power source, which has the desired attributes of high power output per weight and volume and instant rechargeability.
ContributorsSalloum, Kamil S (Author) / Posner, Jonathan D (Thesis advisor) / Adrian, Ronald (Committee member) / Christen, Jennifer (Committee member) / Phelan, Patrick (Committee member) / Chen, Kangping (Committee member) / Arizona State University (Publisher)
Created2010
Description
Image segmentation is of great importance and value in many applications. In computer vision, image segmentation is the tool and process of locating objects and boundaries within images. The segmentation result may provide more meaningful image data. Generally, there are two fundamental image segmentation algorithms: discontinuity and similarity. The idea behind discontinuity is locating the abrupt changes in intensity of images, as are often seen in edges or boundaries. Similarity subdivides an image into regions that fit the pre-defined criteria. The algorithm utilized in this thesis is the second category.
This study addresses the problem of particle image segmentation by measuring the similarity between a sampled region and an adjacent region, based on Bhattacharyya distance and an image feature extraction technique that uses distribution of local binary patterns and pattern contrasts. A boundary smoothing process is developed to improve the accuracy of the segmentation. The novel particle image segmentation algorithm is tested using four different cases of particle image velocimetry (PIV) images. The obtained experimental results of segmentations provide partitioning of the objects within 10 percent error rate. Ground-truth segmentation data, which are manually segmented image from each case, are used to calculate the error rate of the segmentations.
This study addresses the problem of particle image segmentation by measuring the similarity between a sampled region and an adjacent region, based on Bhattacharyya distance and an image feature extraction technique that uses distribution of local binary patterns and pattern contrasts. A boundary smoothing process is developed to improve the accuracy of the segmentation. The novel particle image segmentation algorithm is tested using four different cases of particle image velocimetry (PIV) images. The obtained experimental results of segmentations provide partitioning of the objects within 10 percent error rate. Ground-truth segmentation data, which are manually segmented image from each case, are used to calculate the error rate of the segmentations.
ContributorsHan, Dongmin (Author) / Frakes, David (Thesis advisor) / Adrian, Ronald (Committee member) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2015
Description
The applications utilizing nanoparticles have grown in both industrial and academic areas because of the very large surface area to volume ratios of these particles. One of the best ways to process and control these nanoparticles is fluidization. In this work, a new microjet and vibration assisted (MVA) fluidized bed system was developed in order to fluidize nanoparticles. The system was tested and the parameters optimized using two commercially available TiO2 nanoparticles: P25 and P90. The fluidization quality was assessed by determining the non-dimensional bed height as well as the non-dimensional pressure drop. The non-dimensional bed height for the nanosized TiO2 in the MVA system optimized at about 5 and 7 for P25 and P90 TiO2, respectively, at a resonance frequency of 50 Hz. The non-dimensional pressure drop was also determined and showed that the MVA system exhibited a lower minimum fluidization velocity for both of the TiO2 types as compared to fluidization that employed only vibration assistance. Additional experiments were performed with the MVA to characterize the synergistic effects of vibrational intensity and gas velocity on the TiO2 P25 and P90 fluidized bed heights. Mathematical relationships were developed to correlate vibrational intensity, gas velocity, and fluidized bed height in the MVA. The non-dimensional bed height in the MVA system is comparable to previously published P25 TiO2 fluidization work that employed an alcohol in order to minimize the electrostatic attractions within the bed. However, the MVA system achieved similar results without the addition of a chemical, thereby expanding the potential chemical reaction engineering and environmental remediation opportunities for fluidized nanoparticle systems.
In order to aid future scaling up of the MVA process, the agglomerate size distribution in the MVA system was predicted by utilizing a force balance model coupled with a two-fluid model (TFM) simulation. The particle agglomerate size that was predicted using the computer simulation was validated with experimental data and found to be in good agreement.
Lastly, in order to demonstrate the utility of the MVA system in an air revitalization application, the capture of CO2 was examined. CO2 breakthrough time and adsorption capacities were tested in the MVA system and compared to a vibrating fluidized bed (VFB) system. Experimental results showed that the improved fluidity in the MVA system enhanced CO2 adsorption capacity.
In order to aid future scaling up of the MVA process, the agglomerate size distribution in the MVA system was predicted by utilizing a force balance model coupled with a two-fluid model (TFM) simulation. The particle agglomerate size that was predicted using the computer simulation was validated with experimental data and found to be in good agreement.
Lastly, in order to demonstrate the utility of the MVA system in an air revitalization application, the capture of CO2 was examined. CO2 breakthrough time and adsorption capacities were tested in the MVA system and compared to a vibrating fluidized bed (VFB) system. Experimental results showed that the improved fluidity in the MVA system enhanced CO2 adsorption capacity.
ContributorsAn, Keju (Author) / Andino, Jean (Thesis advisor) / Phelan, Patrick (Thesis advisor) / Adrian, Ronald (Committee member) / Emady, Heather (Committee member) / Kasbaoui, Mohamed (Committee member) / Arizona State University (Publisher)
Created2019