24 resultados para formation of large scale structure
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Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014
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Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014
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Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014
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The Kraft pulping process is the dominant chemical pulping process in the world. Roughly 195 million metric tons of black liquor are produced annually as a by-product from the Kraft pulping process. Black liquor consists of spent cooking chemicals and dissolved organics from the wood and can contain up to 0.15 wt% nitrogen on dry solids basis. The cooking chemicals from black liquor are recovered in a chemical recovery cycle. Water is evaporated in the first stage of the chemical recovery cycle, so the black liquor has a dry solids content of 65-85% prior to combustion. During combustion of black liquor, a portion of the black liquor nitrogen is volatilized, finally forming N2 or NO. The rest of the nitrogen remains in the char as char nitrogen. During char conversion, fixed carbon is burned off leaving the pulping chemicals as smelt, and the char nitrogen forms mostly smelt nitrogen (cyanate, OCN-). Smelt exits the recovery boiler and is dissolved in water. The cyanate from smelt decomposes in the presence of water, forming NH3, which causes nitrogen emissions from the rest of the chemical recovery cycle. This thesis had two focuses: firstly, to determine how the nitrogen chemistry in the recovery boiler is affected by modification of black liquor; and secondly, to find out what causes cyanate formation during thermal conversion, and which parameters affect cyanate formation and decomposition during thermal conversion of black liquor. The fate of added biosludge nitrogen in chemical recovery was determined in Paper I. The added biosludge increased the nitrogen content of black liquor. At the pulp mill, the added biosludge did not increase the NO formation in the recovery boiler, but instead increased the amount of cyanate in green liquor. The increased cyanate caused more NH3 formation, which increased the NCG boiler’s NO emissions. Laboratory-scale experiments showed an increase in both NO and cyanate formation after biosludge addition. Black liquor can be modified, for example by addition of a solid biomass to increase the energy density of black liquor, or by separation of lignin from black liquor by precipitation. The precipitated lignin can be utilized in the production of green chemicals or as a fuel. In Papers II and III, laboratory-scale experiments were conducted to determine the impact of black liquor modification on NO and cyanate formation. Removal of lignin from black liquor reduced the nitrogen content of the black liquor. In most cases NO and cyanate formation decreased with increasing lignin removal; the exception was NO formation from lignin lean soda liquors. The addition of biomass to black liquor resulted in a higher nitrogen content fuel mixture, due to the higher nitrogen content of biomass compared to black liquor. More NO and cyanate were formed from the fuel mixtures than from pure black liquor. The increased amount of formed cyanate led to the hypothesis that black liquor is catalytically active and converts a portion of the nitrogen in the mixed fuel to cyanate. The mechanism behind cyanate formation during thermal conversion of black liquor was not clear before this thesis. Paper IV studies the cyanate formation of alkali metal loaded fuels during gasification in a CO2 atmosphere. The salts K2CO3, Na2CO3, and K2SO4 all promoted char nitrogen to cyanate conversion during gasification, while KCl and CaCO3 did not. It is now assumed that cyanate is formed when alkali metal carbonate or an active intermediate of alkali metal carbonate (e.g. -CO2K) reacts with the char nitrogen forming cyanate. By testing different fuels (bark, peat, and coal), each of which had a different form of organic nitrogen, it was concluded that the form of organic nitrogen in char also has an impact on cyanate formation. Cyanate can be formed during pyrolysis of black liquor, but at temperatures 900°C or above, the formed cyanate will decompose. Cyanate formation in gasifying conditions with different levels of CO2 in the atmosphere was also studied. Most of the char nitrogen was converted to cyanate during gasification at 800-900°C in 13-50% CO2 in N2, and only 5% of the initial fuel nitrogen was converted to NO during char conversion. The formed smelt cyanate was stable at 800°C 13% CO2, while it decomposed at 900°C 13% CO2. The cyanate decomposition was faster at higher temperatures and in oxygen-containing atmospheres than in an inert atmosphere. The presence of CO2 in oxygencontaining atmospheres slowed down the decomposition of cyanate. This work will provide new information on how modification of black liquor affects the nitrogen chemistry during thermal conversion of black liquor and what causes cyanate formation during thermal conversion of black liquor. The formation and decomposition of cyanate was studied in order to provide new data, which would be useful in modeling of nitrogen chemistry in the recovery boiler.
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Demand for the use of energy systems, entailing high efficiency as well as availability to harness renewable energy sources, is a key issue in order to tackling the threat of global warming and saving natural resources. Organic Rankine cycle (ORC) technology has been identified as one of the most promising technologies in recovering low-grade heat sources and in harnessing renewable energy sources that cannot be efficiently utilized by means of more conventional power systems. The ORC is based on the working principle of Rankine process, but an organic working fluid is adopted in the cycle instead of steam. This thesis presents numerical and experimental results of the study on the design of small-scale ORCs. Two main applications were selected for the thesis: waste heat re- covery from small-scale diesel engines concentrating on the utilization of the exhaust gas heat and waste heat recovery in large industrial-scale engine power plants considering the utilization of both the high and low temperature heat sources. The main objective of this work was to identify suitable working fluid candidates and to study the process and turbine design methods that can be applied when power plants based on the use of non-conventional working fluids are considered. The computational work included the use of thermodynamic analysis methods and turbine design methods that were based on the use of highly accurate fluid properties. In addition, the design and loss mechanisms in supersonic ORC turbines were studied by means of computational fluid dynamics. The results indicated that the design of ORC is highly influenced by the selection of the working fluid and cycle operational conditions. The results for the turbine designs in- dicated that the working fluid selection should not be based only on the thermodynamic analysis, but requires also considerations on the turbine design. The turbines tend to be fast rotating, entailing small blade heights at the turbine rotor inlet and highly supersonic flow in the turbine flow passages, especially when power systems with low power outputs are designed. The results indicated that the ORC is a potential solution in utilizing waste heat streams both at high and low temperatures and both in micro and larger scale appli- cations.
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The global interest towards renewable energy production such as wind and solar energy is increasing, which in turn calls for new energy storage concepts due to the larger share of intermittent energy production. Power-to-gas solutions can be utilized to convert surplus electricity to chemical energy which can be stored for extended periods of time. The energy storage concept explored in this thesis is an integrated energy storage tank connected to an oxy-fuel combustion plant. Using this approach, flue gases from the plant could be fed directly into the storage tank and later converted into synthetic natural gas by utilizing electrolysis-methanation route. This work utilizes computational fluid dynamics to model the desublimation of carbon dioxide inside a storage tank containing cryogenic liquid, such as liquefied natural gas. Numerical modelling enables the evaluation of the transient flow patterns caused by the desublimation, as well as general fluid behaviour inside the tank. Based on simulations the stability of the cryogenic storage and the magnitude of the key parameters can be evaluated.
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This thesis examines the determinants of financial leverage ratio of large publicly listed companies within Nordic Telecom sector. The study is done as a case study and it covers 5 case companies headquartered in Nordic countries during period of 2002 - 2014 and by using restated values of quarterly observations from each case company’s interim reports. The chosen hypotheses are tested with multiple linear regressions firm by firm. The Findings of the study showed that uniqueness of Telecom sector and the region of our sample could not provide us unequivocal determinants of leverage ratio within the sector. However, e.g. Pecking order theory’s statement of Liquidity was widely confirmed by 3 out of 5 case companies which is worth to be taken into account in the big picture. The findings also showed that theories and earlier empirical evidence are confirmed by our case companies individually and non-systematically. Though Telecom sector is considered as quite unique industry and we did not discover absolute common relationships that would have held through all the Nordic case companies, we got unique and valuable evidence to conduct the research of this sector in future.
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In the field of molecular biology, scientists adopted for decades a reductionist perspective in their inquiries, being predominantly concerned with the intricate mechanistic details of subcellular regulatory systems. However, integrative thinking was still applied at a smaller scale in molecular biology to understand the underlying processes of cellular behaviour for at least half a century. It was not until the genomic revolution at the end of the previous century that we required model building to account for systemic properties of cellular activity. Our system-level understanding of cellular function is to this day hindered by drastic limitations in our capability of predicting cellular behaviour to reflect system dynamics and system structures. To this end, systems biology aims for a system-level understanding of functional intraand inter-cellular activity. Modern biology brings about a high volume of data, whose comprehension we cannot even aim for in the absence of computational support. Computational modelling, hence, bridges modern biology to computer science, enabling a number of assets, which prove to be invaluable in the analysis of complex biological systems, such as: a rigorous characterization of the system structure, simulation techniques, perturbations analysis, etc. Computational biomodels augmented in size considerably in the past years, major contributions being made towards the simulation and analysis of large-scale models, starting with signalling pathways and culminating with whole-cell models, tissue-level models, organ models and full-scale patient models. The simulation and analysis of models of such complexity very often requires, in fact, the integration of various sub-models, entwined at different levels of resolution and whose organization spans over several levels of hierarchy. This thesis revolves around the concept of quantitative model refinement in relation to the process of model building in computational systems biology. The thesis proposes a sound computational framework for the stepwise augmentation of a biomodel. One starts with an abstract, high-level representation of a biological phenomenon, which is materialised into an initial model that is validated against a set of existing data. Consequently, the model is refined to include more details regarding its species and/or reactions. The framework is employed in the development of two models, one for the heat shock response in eukaryotes and the second for the ErbB signalling pathway. The thesis spans over several formalisms used in computational systems biology, inherently quantitative: reaction-network models, rule-based models and Petri net models, as well as a recent formalism intrinsically qualitative: reaction systems. The choice of modelling formalism is, however, determined by the nature of the question the modeler aims to answer. Quantitative model refinement turns out to be not only essential in the model development cycle, but also beneficial for the compilation of large-scale models, whose development requires the integration of several sub-models across various levels of resolution and underlying formal representations.
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This work focuses on the 159.5 kW solar photovoltaic power plant project installed at the Lappeenranta University of Technology in 2013 as an example of what a solar plant project could be in Finland. The project consists of a two row carport and a flat roof installation on the roof of the university laboratories. The purpose of this project is not only its obvious energy savings potential but also to serve as research and teaching laboratory tool. By 2013, there were not many large scale solar power plants in Finland. For this reason, the installation and data experience from the solar power plant at LUT has brought valuable information for similar projects in northern countries. This work includes a first part for the design and acquisition of the project to continue explaining about the components and their installation. At the end, energy produced by this solar power plant is studied and calculated to find out some relevant economical results. For this, the radiation arriving to southern Finland, the losses of the system in cold weather and the impact of snow among other aspects are taken into account.