Modeling Mass and Thermal Transport in Thin Porous Media of PEM Fuel Cells

Water transport in the Porous Transport Layer (PTL) plays an important role in the efficient operation of polymer electrolyte membrane fuel cells (PEMFC). Excessive water content as well as dry operating conditions are unfavorable for efficient and reliable operation of the fuel cell. The effect of thermal conductivity and porosity on water management are investigated by simulating two-phase ow in the PTL of the fuel cell using a network model. In the model, the PTL consists of a pore-phase and a solid-phase. Different models of the PTLs are generated using independent Weibull distributions for the pore-phase and the solid-phase. The specific arrangement of the pores and solid elements is varied to obtain different PTL realizations for the same Weibull parameters. The properties of PTL are varied by changing the porosity and thermal conductivity. The parameters affecting operating conditions include the temperature, relative humidity in the ow channel and voltage and current density. In addition, a novel high-speed capable Surface Plasmon Resonance (SPR) microscope was built based on Kretschmann\u27s configuration utilizing a collimated Kohler illumination. The SPR allows thin film characterization in a thickness of approximately 0-200nm by measuring the changes in the refractive index. Various independent experiments were run to measure film thickness during droplet coalescence during condensation

A Unified End-to-End Communication Paradigm for Heterogeneous Networks

The aim of this thesis research is to develop a unified communication paradigm that provides an end-to-end bursting model across heterogeneous realms. This model generates end-to-end bursts, thereby eliminating edge node burst assembly and its effect on TCP performance. Simulation models are developed in ns-2 to validate this work by comparing it with edge burst assembly on OBS networks. Analysis shows improved end-to-end performance for a variety of burst sizes, timeouts, and other network parameters

Static and dynamic contact angle measurement on rough surfaces using sessile drop profile analysis with application to water management in low temperature fuel cells

Fuel Cells are a promising alternative energy technology. One of the biggest problems that exists in fuel cell is that of water management. A better understanding of wettability characteristics in the fuel cells is needed to alleviate the problem of water management. Contact angle data on gas diffusion layers (GDL) of the fuel cells can be used to characterize the wettability of GDL in fuel cells. A contact angle measurement program has been developed to measure the contact angle of sessile drops from drop images. Digitization of drop images induces pixel errors in the contact angle measurement process. The resulting uncertainty in contact angle measurement has been analyzed. An experimental apparatus has been developed for contact angle measurements at different temperature, with the feature to measure advancing and receding contact angles on gas diffusion layers of fuel cells

Rebalancing of exchange traded funds in stock market using option trading strategies

Motivation: The finance and academic industries are highly discussed in the stock market trading domain. The increase in economic globalization shows the connection among stock markets in different countries, which produces the effect of risk conduction in the market. Forecasting the direction of every day’s stock market return is important and challenging. The growing complexity and dynamic features in stock markets are difficult in the financial industry. The inflexible trading method developed by financial practitioners utilized a larger amount of stock market features and is failed to achieve a satisfactory result in every condition of the market. Further, the existing data mining approaches are incomplete and inefficient. Aim: To overcome the issues in stock and problem of existing methods, proposed option trading strategies for rebalancing Exchange Traded Fund (ETF) in the stock market. Rebalancing-ETF measure the volatility of the stock to track the error of model and rebalance the threshold quality to improve the trade. The proposed method increases the order of threshold quantity to rebalance the trade. Results: The result showed that the minimum orders increases in rebalancing trade, which reduces the impact of price formations in market. The tracking error occurs when the larger quantity of threshold value reduces the quantity. Then, the markets are changed significantly when the Net Asset Values (NAV) of rebalancing ETF increases

Assessing the feasibility and mechanism of destructive removal of per- and polyfluoroalkyl substances (PFAS) from water

One of the most pertinent challenges faced by the drinking water community is the widespread contamination of per- and polyfluoroalkyl substances (PFAS). These anthropogenic chemicals have been ubiquitously used in everyday products such as carpets, stain repellents, dyes, shampoos, non-stick cookware as well as in aqueous firefighting foams. PFAS are linked with adverse health effects in humans such as thyroid disease, obesity, immunological and reproductive disorders and linked to cancer in adults and low birth weight and developmental defects in infants. Conventional water treatment technologies have proven to be largely ineffective in PFAS remediation, due to their extreme stability and resistance to degradation. The overall goal of this dissertation is to assess the feasibility and performance of novel destructive technologies in treating PFAS. The specific objectives of this study are to: (i) investigate the impact of water quality and operating parameters on the treatment of a suite of PFAS using two destructive techniques, a) electron beam (e-beam) and b) electrochemical oxidation process (eAOP); (ii) elucidate the primary degradation mechanism of PFAS in these systems; (iii) differentiate the performance (energy requirements) of these systems in treating PFAS isomers; and (iv) develop a novel air-bubbling system to extract PFAS from contaminated soils to combine with destructive technologies via a treatment-train approach. The effect of chain length and functional group is observed while treating PFAS with e-beam technology with the short chain perfluorobutanoic acid and perfluorobutanesulfonic acid showing highest resistance to degradation. This chapter additionally highlights previously unknown degradation pathways of PFAS using a combination of fluorine mass balance and suspect screening. In eAOP system, the composition of supporting electrolyte and anodic voltage did not impact PFAS degradation. PFAS degradation strongly correlates with compound hydrophobicity and this study is the first to differentiate between degradation and loss in concentration due to the phenomena of electrochemical aerosolization of PFAS. Branched PFAS isomers preferentially degrade by e-beam treatment but show comparative/poorer removal in an eAOP system, compared to their linear forms. Soil washing is studied as a removal approach for PFAS-contaminated soils, that can be used as a standalone technique or along with destructive techniques in a treatment train system. A novel air-bubbling assisted soil washing system is used to investigate the removal of adsorbed PFAS from contaminated soils. The extraction efficiency from the soil is found to be inversely proportional to PFAS hydrophobicity, with poorest results observed for long chain perfluorodecanoic acid. Results from this dissertation (i) identify ideal conditions and energy requirements for the destructive removal of PFAS, (ii) highlight the challenges and knowledge gaps for the remediation of contaminated soils, and (iii) provide insight into the variable mechanisms of PFAS destruction and removal, impacted by the PFAS structure and operating parameters in both aqueous and soil matrices

Studies on Metal Chelates

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Circular economy : can it be an effective economic re-design?

Circular Economy recently has gained massive attention in terms of its implications across multiple industrial verticals. Various schools of thoughts like permaculture, cradle to cradle, industrial symbiosis have been associated with the Circular Economy, yet the application of circular practices is still relatively low. This research addresses the gaps between the theory and practice and analyses the reasons why there is the delay in its application. Moreover, the research also reflects on the understanding of Circular Economy with its circular business models and how those business models can tackle and address the challenges in the traditional linear production systems. Apart from this, the benefits for the key stakeholders in the economy i.e., corporations, governments and consumers have been identified and explained. Multiple case research methodology has been followed to understand the ground reality of the delay in the application of circular economy, four industrial verticals have been chosen and using a semi-structured interview process, various examples, strategies, opportunities and challenges have been understood and they form the analytical structure of the research. The research then uses the results from the case study to be interpreted by using the theory of absorptive capacity in an open innovation system and hence the results are analyzed accordingly, concluded with the understanding of technological, leadership, consumer behavior enabling factors and the monopoly played by corporations as a disabler. Moreover, the recommendations are directed towards the government enabling stricter EPR (Extended Producer Responsibility) and post occupancy evaluation regulations.A Economia Circular tem ganho recentemente grande atenção em termos das suas implicações em vários setores industriais. Várias escolas de pensamento, como a permacultura, o gradle-to-gradle, a simbiose industrial, entre outros, têm sido associadas à Economia Circular, embora a implementação de práticas circulares ainda seja relativamente baixa. Esta pesquisa aborda as lacunas entre a teoria e prática, e analisa as principais razões que têm atrasado a sua implementação. A pesquisa reflete ainda o entendimento da Economia Circular com seus modelos de negócios circulares, e como esses modelos de negócios podem enfrentar os desafios dos tradicionais sistemas de produção linear. Além disso, foram também identificados e explicados os benefícios para os principais stakeholders na economia (corporações, governos e consumidores). Foi aplicada a metodologia de pesquisa de casos múltiplos para entender a realidade do atraso na implementação da economia circular: foram escolhidos quatro setores industriais, e, usando um processo de entrevista semi-estruturada, foram analisados vários exemplos, estratégias, oportunidades e desafios, que formam a estrutura analítica da pesquisa. A pesquisa usou os resultados do estudo de caso, interpretando-os com base na teoria da capacidade absortiva num sistema de inovação aberta. De seguida, os resultados foram analisados adequadamente, e concluídos com a compreensão de fatores tecnológicos, de liderança, de comportamento do consumidor e do monopólio pelas corporações como uma barreira. Além disso, as recomendações foram direcionadas para o Governo, permitindo uma aplicação mais rigorosa do EPR (Extended Producer Responsibility) e regulamentos de avaliação pós-ocupação

Object Recognition and Clustering based on Latent Semantic Analysis (LSA)

Object Recognition and clustering are prime techniques in Computer Vision, Pattern Recognition, Artificial Intelligence and Robotics. Conventionally these techniques are implemented in Visual-Feature based methods. However, these methods have drawbacks they do not efficiently deal with the differences in shapes and colours of objects. Another method which uses semantic similarity to solve this kind of problem, i.e. Cosine Similarity method, but this method also has problems. The problems are synonymies and polysemies. In this paper we propose a method in which objects with different shapes and different colours which function similarly can be recognized and clustered. If the text printed on the object the semantic feature of that object is extracted and clustered according to semantic feature. Proposed method is based on semantic information so we conduct an experiment with the dataset of images which contains the packing cases of commercial products (e.g. Mobile, Laptop etc). Semantic information in dataset is retrieved using text extraction module and then the results of text extraction are passed through an Internet search module. Finally objects are described and clustered using the latent semantic analysis (LSA) module. The clustering results are more accurate than the Visual feature based method and cosine similarity based methods. DOI: 10.17762/ijritcc2321-8169.150512