Nanostructured catalysts for the development of the hydrogen economy

La catalyse joue un rôle essentiel dans de nombreuses applications industrielles telles que les industries pétrochimique et biochimique, ainsi que dans la production de polymères et pour la protection de l’environnement. La conception et la fabrication de catalyseurs efficaces et rentables est une étape importante pour résoudre un certain nombre de problèmes des nouvelles technologies de conversion chimique et de stockage de l’énergie. L’objectif de cette thèse est le développement de voies de synthèse efficaces et simples pour fabriquer des catalyseurs performants à base de métaux non nobles et d’examiner les aspects fondamentaux concernant la relation entre structure/composition et performance catalytique, notamment dans des processus liés à la production et au stockage de l’hydrogène. Dans un premier temps, une série d’oxydes métalliques mixtes (Cu/CeO2, CuFe/CeO2, CuCo/CeO2, CuFe2O4, NiFe2O4) nanostructurés et poreux ont été synthétisés grâce à une méthode améliorée de nanocasting. Les matériaux Cu/CeO2 obtenus, dont la composition et la structure poreuse peuvent être contrôlées, ont ensuite été testés pour l’oxydation préférentielle du CO dans un flux d’hydrogène dans le but d’obtenir un combustible hydrogène de haute pureté. Les catalyseurs synthétisés présentent une activité et une sélectivité élevées lors de l’oxydation sélective du CO en CO2. Concernant la question du stockage d’hydrogène, une voie de synthèse a été trouvée pour le composét mixte CuO-NiO, démontrant une excellente performance catalytique comparable aux catalyseurs à base de métaux nobles pour la production d’hydrogène à partir de l’ammoniaborane (aussi appelé borazane). L’activité catalytique du catalyseur étudié dans cette réaction est fortement influencée par la nature des précurseurs métalliques, la composition et la température de traitement thermique utilisées pour la préparation du catalyseur. Enfin, des catalyseurs de Cu-Ni supportés sur silice colloïdale ou sur des particules de carbone, ayant une composition et une taille variable, ont été synthétisés par un simple procédé d’imprégnation. Les catalyseurs supportés sur carbone sont stables et très actifs à la fois dans l’hydrolyse du borazane et la décomposition de l’hydrazine aqueuse pour la production d’hydrogène. Il a été démontré qu’un catalyseur optimal peut être obtenu par le contrôle de l’effet bi-métallique, l’interaction métal-support, et la taille des particules de métal.

Minimizar o sobrecusto da redução da capacidade de interligação com recurso ao counter-trading

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de energia

Sistema de emulação de aerogeradores para aplicação em geração distribuída de energia elétrica

Power generation from alternative sources is at present the subject of numerous research and development in science and industry. Wind energy stands out in this scenario as one of the most prominent alternative in the generation of electricity, by its numerous advantages. In research works, computer reproduction and experimental behavior of a wind turbine are very suitable tools for the development and study of new technologies and the use of wind potential of a given region. These tools generally are desired to include simulation of mechanical and electrical parameters that directly affect the energy conversion. This work presents the energy conversion process in wind systems for power generation, in order to develop a tool for wind turbine emulation testing experimental, using LabVIEW® software. The purpose of this tool is to emulate the torque developed in an axis wind turbine. The physical setup consists of a three phase induction motor and a permanent magnet synchronous generator, which are evaluated under different wind speed conditions. This tool has the objective to be flexible to other laboratory arrangements, and can be used in other wind power generation structures in real time. A modeling of the wind power system is presented, from the turbine to the electrical generator. A simulation tool is developed using Matlab/Simulink® with the purpose to pre-validate the experiment setup. Finally, the design is implemented in a laboratory setup.

Using interaction data for improving the offline and online evaluation of search engines

This thesis investigates how web search evaluation can be improved using historical interaction data. Modern search engines combine offline and online evaluation approaches in a sequence of steps that a tested change needs to pass through to be accepted as an improvement and subsequently deployed. We refer to such a sequence of steps as an evaluation pipeline. In this thesis, we consider the evaluation pipeline to contain three sequential steps: an offline evaluation step, an online evaluation scheduling step, and an online evaluation step. In this thesis we show that historical user interaction data can aid in improving the accuracy or efficiency of each of the steps of the web search evaluation pipeline. As a result of these improvements, the overall efficiency of the entire evaluation pipeline is increased. Firstly, we investigate how user interaction data can be used to build accurate offline evaluation methods for query auto-completion mechanisms. We propose a family of offline evaluation metrics for query auto-completion that represents the effort the user has to spend in order to submit their query. The parameters of our proposed metrics are trained against a set of user interactions recorded in the search engine’s query logs. From our experimental study, we observe that our proposed metrics are significantly more correlated with an online user satisfaction indicator than the metrics proposed in the existing literature. Hence, fewer changes will pass the offline evaluation step to be rejected after the online evaluation step. As a result, this would allow us to achieve a higher efficiency of the entire evaluation pipeline. Secondly, we state the problem of the optimised scheduling of online experiments. We tackle this problem by considering a greedy scheduler that prioritises the evaluation queue according to the predicted likelihood of success of a particular experiment. This predictor is trained on a set of online experiments, and uses a diverse set of features to represent an online experiment. Our study demonstrates that a higher number of successful experiments per unit of time can be achieved by deploying such a scheduler on the second step of the evaluation pipeline. Consequently, we argue that the efficiency of the evaluation pipeline can be increased. Next, to improve the efficiency of the online evaluation step, we propose the Generalised Team Draft interleaving framework. Generalised Team Draft considers both the interleaving policy (how often a particular combination of results is shown) and click scoring (how important each click is) as parameters in a data-driven optimisation of the interleaving sensitivity. Further, Generalised Team Draft is applicable beyond domains with a list-based representation of results, i.e. in domains with a grid-based representation, such as image search. Our study using datasets of interleaving experiments performed both in document and image search domains demonstrates that Generalised Team Draft achieves the highest sensitivity. A higher sensitivity indicates that the interleaving experiments can be deployed for a shorter period of time or use a smaller sample of users. Importantly, Generalised Team Draft optimises the interleaving parameters w.r.t. historical interaction data recorded in the interleaving experiments. Finally, we propose to apply the sequential testing methods to reduce the mean deployment time for the interleaving experiments. We adapt two sequential tests for the interleaving experimentation. We demonstrate that one can achieve a significant decrease in experiment duration by using such sequential testing methods. The highest efficiency is achieved by the sequential tests that adjust their stopping thresholds using historical interaction data recorded in diagnostic experiments. Our further experimental study demonstrates that cumulative gains in the online experimentation efficiency can be achieved by combining the interleaving sensitivity optimisation approaches, including Generalised Team Draft, and the sequential testing approaches. Overall, the central contributions of this thesis are the proposed approaches to improve the accuracy or efficiency of the steps of the evaluation pipeline: the offline evaluation frameworks for the query auto-completion, an approach for the optimised scheduling of online experiments, a general framework for the efficient online interleaving evaluation, and a sequential testing approach for the online search evaluation. The experiments in this thesis are based on massive real-life datasets obtained from Yandex, a leading commercial search engine. These experiments demonstrate the potential of the proposed approaches to improve the efficiency of the evaluation pipeline.

The Influence of Place Attachment, Aspirations, and Rapidly Changing Environments on Resettlement Decisions

Resettlement associated with development projects results in a variety of negative impacts. This dissertation uses the resettlement context to frame the dynamic relationships formed between peoples and places experiencing development. Two case studies contribute: (a) the border zone of Mozambique’s Limpopo National Park where residents contend with changes to land access and use; and (b) Bairro Chipanga in Moatize, Mozambique where a resettled population struggles to form place attachment and transform the post-resettlement site into a “good” place. Through analysis of data collected at these sites between 2009 and 2015, this dissertation investigates how changing environments impact person-place relationships before and after resettlement occurs. Changing environments create conditions leading to disemplacement—feeling like one no longer belongs—that reduces the environment’s ability to foster place attachment. Research findings indicate that responses taken by individuals living in the changing environment depend heavily upon whether resettlement has already occurred. In a pre-resettlement context, residents adjust their daily lives to diminish the effects of a changing environment and re-create the conditions to which they initially formed an attachment. They accept impoverishing conditions, including a narrowing of the spaces in which they live their daily lives, because it is preferred to the anxiety that accompanies being forced to resettle. In a post-resettlement context, resettlement disrupts the formation of place attachment and resettled peoples become a placeless population. When the resettlement has not resulted in anticipated outcomes, the aspiration for social justice—seeking conditions residents had reason to expect—negatively influences residents’ perspectives about the place. The post-resettlement site becomes a bad place with a future unchanged from the present. At best, this results in a population in which more members are willing to move away from the post-resettlement site, and, at worse, complete disengagement of other members from trying to improve the community. Resettlement thus has the potential to launch a cycle of movement- displacement-movement that prevents an entire generation from establishing place attachment and realizing its benefits. At the very least, resettlement impedes the formation of place attachment to new places. Thus, this dissertation draws attention to the unseen and uncompensated losses of resettlement.

Novel Automotive Waste Heat Recovery Techniques

The United States transportation industry is predicted to consume approximately 13 million barrels of liquid fuel per day by 2025. If one percent of the fuel energy were salvaged through waste heat recovery, there would be a reduction of 130 thousand barrels of liquid fuel per day. This dissertation focuses on automotive waste heat recovery techniques with an emphasis on two novel techniques. The first technique investigated was a combination coolant and exhaust-based Rankine cycle system, which utilized a patented piston-in-piston engine technology. The research scope included a simulation of the maximum mass flow rate of steam (700 K and 5.5 MPa) from two heat exchangers, the potential power generation from the secondary piston steam chambers, and the resulting steam quality within the steam chamber. The secondary piston chamber provided supplemental steam power strokes during the engine's compression and exhaust strokes to reduce the pumping work of the engine. A Class-8 diesel engine, operating at 1,500 RPM at full load, had a maximum increase in the brake fuel conversion efficiency of 3.1%. The second technique investigated the implementation of thermoelectric generators on the outer cylinder walls of a liquid-cooled internal combustion engine. The research scope focused on the energy generation, fuel energy distribution, and cylinder wall temperatures. The analysis was conducted over a range of engine speeds and loads in a two cylinder, 19.4 kW, liquid-cooled, spark-ignition engine. The cylinder wall temperatures increased by 17% to 44% which correlated well to the 4.3% to 9.5% decrease in coolant heat transfer. Only 23.3% to 28.2% of the heat transfer to the coolant was transferred through the TEG and TEG surrogate material. The gross indicated work decreased by 0.4% to 1.0%. The exhaust gas energy decreased by 0.8% to 5.9%. Due to coolant contamination, the TEG output was not able to be obtained. TEG output was predicted from cylinder wall temperatures and manufacturer documentation, which was less than 0.1% of the cumulative heat release. Higher TEG conversion efficiencies, combined with greater control of heat transfer paths, would be needed to improve energy output and make this a viable waste heat recovery technique.

A COST-BENEFIT ANALYSIS OF A 25% RPS IN MICHIGAN

Michigan depends heavily on fossil fuels to generate electricity. Compared with fossil fuels, electricity generation from renewable energy produces less pollutants emissions. A Renewable Portfolio Standard (RPS) is a mandate that requires electric utilities to generate a certain amount of electricity from renewable energy sources. This thesis applies the Cost-Benefits Analysis (CBA) method to investigate the impacts of implementing a 25% in Michigan by 2025. It is found that a 25% RPS will create about $20.12 billion in net benefits to the State. Moreover, if current tax credit policies will not change until 2025, its net present value will increase to about $26.59 billion. Based on the results of this CBA, a 25% RPS should be approved. The result of future studies on the same issue can be improved if more state specific data become available.

FACTORS INFLUENCING MATERIAL LOSS DURING IRON ORE PELLET HANDLING

Iron ore concentrate pellets have the potential to fracture and abrade during transportation and handling, which produces unwanted fine particulates and dust. Consequently, pellet producers characterize the abrasion resistance of their pellets, using an Abrasion Index (AI), to indicate whether their products will produce unacceptable levels of fines. However, no one has ever investigated whether the AI correlates to pellet dustiness. During the course of this research, we investigated the relationship between AI and iron ore concentrate pellet dustiness using a wide range of industrial and laboratory pellet samples. The results showed that, in general, AI can be used to indicate high levels of dust. However, for good-quality pellets, there was no correlation between the two. Thus, dust generation from shipping and handling pellets will depend on the quantity of pellets handled and how much they are handled. These results also showed that the type of industrial furnace used to harden iron ore concentrate pellets may affect their fines generation and potential dustiness.

Sustainable Energy Production in the United States: Life Cycle Assessment of Biofuels and Bioenergy

The United States of America is making great efforts to transform the renewable and abundant biomass resources into cost-competitive, high-performance biofuels, bioproducts, and biopower. This is the key to increase domestic production of transportation fuels and renewable energy, and reduce greenhouse gas and other pollutant emissions. This dissertation focuses specifically on assessing the life cycle environmental impacts of biofuels and bioenergy produced from renewable feedstocks, such as lignocellulosic biomass, renewable oils and fats. The first part of the dissertation presents the life cycle greenhouse gas (GHG) emissions and energy demands of renewable diesel (RD) and hydroprocessed jet fuels (HRJ). The feedstocks include soybean, camelina, field pennycress, jatropha, algae, tallow and etc. Results show that RD and HRJ produced from these feedstocks reduce GHG emissions by over 50% compared to comparably performing petroleum fuels. Fossil energy requirements are also significantly reduced. The second part of this dissertation discusses the life cycle GHG emissions, energy demands and other environmental aspects of pyrolysis oil as well as pyrolysis oil derived biofuels and bioenergy. The feedstocks include waste materials such as sawmill residues, logging residues, sugarcane bagasse and corn stover, and short rotation forestry feedstocks such as hybrid poplar and willow. These LCA results show that as much as 98% GHG emission savings is possible relative to a petroleum heavy fuel oil. Life cycle GHG savings of 77 to 99% were estimated for power generation from pyrolysis oil combustion relative to fossil fuels combustion for electricity, depending on the biomass feedstock and combustion technologies used. Transportation fuels hydroprocessed from pyrolysis oil show over 60% of GHG reductions compared to petroleum gasoline and diesel. The energy required to produce pyrolysis oil and pyrolysis oil derived biofuels and bioelectricity are mainly from renewable biomass, as opposed to fossil energy. Other environmental benefits include human health, ecosystem quality and fossil resources. The third part of the dissertation addresses the direct land use change (dLUC) impact of forest based biofuels and bioenergy. An intensive harvest of aspen in Michigan is investigated to understand the GHG mitigation with biofuels and bioenergy production. The study shows that the intensive harvest of aspen in MI compared to business as usual (BAU) harvesting can produce 18.5 billion gallons of ethanol to blend with gasoline for the transport sector over the next 250 years, or 32.2 billion gallons of bio-oil by the fast pyrolysis process, which can be combusted to generate electricity or upgraded to gasoline and diesel. Intensive harvesting of these forests can result in carbon loss initially in the aspen forest, but eventually accumulates more carbon in the ecosystem, which translates to a CO2 credit from the dLUC impact. Time required for the forest-based biofuels to reach carbon neutrality is approximately 60 years. The last part of the dissertation describes the use of depolymerization model as a tool to understand the kinetic behavior of hemicellulose hydrolysis under dilute acid conditions. Experiments are carried out to measure the concentrations of xylose and xylooligomers during dilute acid hydrolysis of aspen. The experiment data are used to fine tune the parameters of the depolymerization model. The results show that the depolymerization model successfully predicts the xylose monomer profile in the reaction, however, it overestimates the concentrations of xylooligomers.

Load Profile Analysis Tool for Electrical Appliances in Households

This paper presents a methodology to forecast the hourly and daily consumption in households. The methodology was validated for households in Lisbon region, Portugal. The paper shows that the forecast tool allows obtaining satisfactory results for forecasting. Models of demand response allow the support of consumer’s decision in exchange for an economic benefit by the redefinition of load profile or changing the appliance consumption period. It is also in the interest of electric utilities to take advantage of these changes, particularly when consumers have an action on the demand-side management or production. Producers need to understand the load profile of households that are connected to a smart grid, to promote a better use of energy, as well as optimize the use of micro-generation from renewable sources, not only to delivering to the network but also in self-consumption.

The Basic Reproduction Number Obtained From Jacobian And Next Generation Matrices - A Case Study Of Dengue Transmission Modelling.

The basic reproduction number is a key parameter in mathematical modelling of transmissible diseases. From the stability analysis of the disease free equilibrium, by applying Routh-Hurwitz criteria, a threshold is obtained, which is called the basic reproduction number. However, the application of spectral radius theory on the next generation matrix provides a different expression for the basic reproduction number, that is, the square root of the previously found formula. If the spectral radius of the next generation matrix is defined as the geometric mean of partial reproduction numbers, however the product of these partial numbers is the basic reproduction number, then both methods provide the same expression. In order to show this statement, dengue transmission modelling incorporating or not the transovarian transmission is considered as a case study. Also tuberculosis transmission and sexually transmitted infection modellings are taken as further examples.

Rhamnolipids as biosurfactants from renewable resources: Concepts for next-generation rhamnolipid production

Several microorganisms are known to produce a wide variety of surface-active substances, which are referred to as biosurfactants. Interesting examples for biosurfactants are rhamnolipids, glycolipids mainly known from Pseudomonas aeruginosa produced during cultivation on different substrates like vegetable oils, sugars, glycerol or hydrocarbons. However, besides costs for downstream processing of rhamnolipids, relatively high raw-material prices and low productivities currently inhibit potential economical production of rhamnolipids on an industrial scale. This review focuses on cost-effective and sustainable production of rhamnolipids by introducing new possibilities and strategies regarding renewable substrates. Additionally, past and recent production strategies using alternative substrates such as agro-industrial byproducts or wastes are summarized. Requirements and concepts for next-generation rhamnolipid producing strains are discussed and potential targets for strain-engineering are presented. The discussion of potential new strategies is supported by an analysis of the metabolism of different Pseudomonas species. According to calculations of theoretical substrate-to-product conversion yields and current world-market price analysis, different renewable substrates are compared and discussed from an economical point of view. A next-generation rhamnolipid producing strain, as proposed within this review, may be engineered towards reduced formation of byproducts, increased metabolic spectrum, broadened substrate spectrum and controlled regulation for the induction of rhamnolipid synthesis. (C) 2012 Elsevier Ltd. All rights reserved.

Query rewriting in information retrieval: automatic context extraction from local user documents to improve query results

The central objective of research in Information Retrieval (IR) is to discover new techniques to retrieve relevant information in order to satisfy an Information Need. The Information Need is satisfied when relevant information can be provided to the user. In IR, relevance is a fundamental concept which has changed over time, from popular to personal, i.e., what was considered relevant before was information for the whole population, but what is considered relevant now is specific information for each user. Hence, there is a need to connect the behavior of the system to the condition of a particular person and his social context; thereby an interdisciplinary sector called Human-Centered Computing was born. For the modern search engine, the information extracted for the individual user is crucial. According to the Personalized Search (PS), two different techniques are necessary to personalize a search: contextualization (interconnected conditions that occur in an activity), and individualization (characteristics that distinguish an individual). This movement of focus to the individual's need undermines the rigid linearity of the classical model overtaken the ``berry picking'' model which explains that the terms change thanks to the informational feedback received from the search activity introducing the concept of evolution of search terms. The development of Information Foraging theory, which observed the correlations between animal foraging and human information foraging, also contributed to this transformation through attempts to optimize the cost-benefit ratio. This thesis arose from the need to satisfy human individuality when searching for information, and it develops a synergistic collaboration between the frontiers of technological innovation and the recent advances in IR. The search method developed exploits what is relevant for the user by changing radically the way in which an Information Need is expressed, because now it is expressed through the generation of the query and its own context. As a matter of fact the method was born under the pretense to improve the quality of search by rewriting the query based on the contexts automatically generated from a local knowledge base. Furthermore, the idea of optimizing each IR system has led to develop it as a middleware of interaction between the user and the IR system. Thereby the system has just two possible actions: rewriting the query, and reordering the result. Equivalent actions to the approach was described from the PS that generally exploits information derived from analysis of user behavior, while the proposed approach exploits knowledge provided by the user. The thesis went further to generate a novel method for an assessment procedure, according to the "Cranfield paradigm", in order to evaluate this type of IR systems. The results achieved are interesting considering both the effectiveness achieved and the innovative approach undertaken together with the several applications inspired using a local knowledge base.

Connecting people and ideas from around the world: global innovation platforms for next-generation ecology and beyond

We present a case for using Global Community Innovation Platforms (GCIPs), an approach to improve innovation and knowledge exchange in international scientific communities through a common and open online infrastructure. We highlight the value of GCIPs by focusing on recent efforts targeting the ecological sciences, where GCIPs are of high relevance given the urgent need for interdisciplinary, geographical, and cross-sector collaboration to cope with growing challenges to the environment as well as the scientific community itself. Amidst the emergence of new international institutions, organizations, and meetings, GCIPs provide a stable international infrastructure for rapid and long-term coordination that can be accessed by any individual. This accessibility can be especially important for researchers early in their careers. Recent examples of early-career GCIPs complement an array of existing options for early-career scientists to improve skill sets, increase academic and social impact, and broaden career opportunities. We provide a number of examples of existing early-career initiatives that incorporate elements from the GCIPs approach, and highlight an in-depth case study from the ecological sciences: the International Network of Next-Generation Ecologists (INNGE), initiated in 2010 with support from the International Association for Ecology and 20 member institutions from six continents.

ScriptLattes: an open-source knowledge extraction system from the Lattes platform

The Lattes platform is the major scientific information system maintained by the National Council for Scientific and Technological Development (CNPq). This platform allows to manage the curricular information of researchers and institutions working in Brazil based on the so called Lattes Curriculum. However, the public information is individually available for each researcher, not providing the automatic creation of reports of several scientific productions for research groups. It is thus difficult to extract and to summarize useful knowledge for medium to large size groups of researchers. This paper describes the design, implementation and experiences with scriptLattes: an open-source system to create academic reports of groups based on curricula of the Lattes Database. The scriptLattes system is composed by the following modules: (a) data selection, (b) data preprocessing, (c) redundancy treatment, (d) collaboration graph generation among group members, (e) research map generation based on geographical information, and (f) automatic report creation of bibliographical, technical and artistic production, and academic supervisions. The system has been extensively tested for a large variety of research groups of Brazilian institutions, and the generated reports have shown an alternative to easily extract knowledge from data in the context of Lattes platform. The source code, usage instructions and examples are available at http://scriptlattes.sourceforge.net/.