966 resultados para Gas- and particle PAHs


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In the present chapter some prototype gas and gas-surface processes occurring within the hypersonic flow layer surrounding spacecrafts at planetary entry are discussed. The discussion is based on microscopic dynamical calculations of the detailed cross sections and rate coefficients performed using classical mechanics treatments for atoms, molecules and surfaces. Such treatment allows the evaluation of the efficiency of thermal processes (both at equilibrium and nonequilibrium distributions) based on state-to-state and state specific calculations properly averaged over the population of the initial states. The dependence of the efficiency of the considered processes on the initial partitioning of energy among the various degrees of freedom is discussed.

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Better models are needed for radiative heat transfer in boiler furnaces. If the process is known better, combustion in the furnace can be optimized to produce low emissions. It makes the process to be environmental friendly. Furthermore, if there is a better model of the furnace it can more fully explain what is happening inside the furnace. Using of the model one can quickly and easily analyze how it operates with bio fuels, moist fuels or difficult fuels and improve the operation. Models helps with better estimation of furnace dimensions and result in more accurate understanding of operation. Key component lacking in these models is radiative heat transfer in particle laden gases. If there are no particles than radiative heat transfer can be calculated approximately. There are two problems with current models when used with flow modeling. The first one is a need to account for a particle laden gas and the second one is an absence of a fast algorithm. Fast calculation is needed if radiative heat transfer calculation is done for a large CDF model. Computations slow down if time is required for calculating radiative properties over and over again. This thesis presents a band model for radiative heat transfer in boiler furnaces. Advantage is a quickness of calculation and account of particles in the process.

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This thesis gathers knowledge about ongoing high-temperature reactor projects around the world. Methods for calculating coolant flow and heat transfer inside a pebble-bed reactor core are also developed. The thesis begins with the introduction of high-temperature reactors including the current state of the technology. Process heat applications that could use the heat from a high-temperature reactor are also introduced. A suitable reactor design with data available in literature is selected for the calculation part of the thesis. Commercial computational fluid dynamics software Fluent is used for the calculations. The pebble-bed is approximated as a packed-bed, which causes sink terms to the momentum equations of the gas flowing through it. A position dependent value is used for the packing fraction. Two different models are used to calculate heat transfer. First a local thermal equilibrium is assumed between the gas and solid phases and a single energy equation is used. In the second approach, separate energy equations are used for the phases. Information about steady state flow behavior, pressure loss, and temperature distribution in the core is obtained as results of the calculations. The effect of inlet mass flow rate to pressure loss is also investigated. Data found in literature and the results correspond each other quite well, considered the amount of simplifications in the calculations. The models developed in this thesis can be used to solve coolant flow and heat transfer in a pebble-bed reactor, although additional development and model validation is needed for better accuracy and reliability.

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Particulate nanostructures are increasingly used for analytical purposes. Such particles are often generated by chemical synthesis from non-renewable raw materials. Generation of uniform nanoscale particles is challenging and particle surfaces must be modified to make the particles biocompatible and water-soluble. Usually nanoparticles are functionalized with binding molecules (e.g., antibodies or their fragments) and a label substance (if needed). Overall, producing nanoparticles for use in bioaffinity assays is a multistep process requiring several manufacturing and purification steps. This study describes a biological method of generating functionalized protein-based nanoparticles with specific binding activity on the particle surface and label activity inside the particles. Traditional chemical bioconjugation of the particle and specific binding molecules is replaced with genetic fusion of the binding molecule gene and particle backbone gene. The entity of the particle shell and binding moieties are synthesized from generic raw materials by bacteria, and fermentation is combined with a simple purification method based on inclusion bodies. The label activity is introduced during the purification. The process results in particles that are ready-to-use as reagents in bioaffinity. Apoferritin was used as particle body and the system was demonstrated using three different binding moieties: a small protein, a peptide and a single chain Fv antibody fragment that represents a complex protein including disulfide bridge.If needed, Eu3+ was used as label substance. The results showed that production system resulted in pure protein preparations, and the particles were of homogeneous size when visualized with transmission electron microscopy. Passively introduced label was stably associated with the particles, and binding molecules genetically fused to the particle specifically bound target molecules. Functionality of the particles in bioaffinity assays were successfully demonstrated with two types of assays; as labels and in particle-enhanced agglutination assay. This biological production procedure features many advantages that make the process especially suited for applications that have frequent and recurring requirements for homogeneous functional particles. The production process of ready, functional and watersoluble particles follows principles of “green chemistry”, is upscalable, fast and cost-effective.

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Late on 2011 November 3, STEREO-A, STEREO-B, MESSENGER, and near-Earth spacecraft observed an energetic particle flux enhancement. Based on the analysis of in situ plasma and particle observations, their correlation with remote sensing observations, and an interplanetary transport model, we conclude that the particle increases observed at multiple locations had a common single source active region and the energetic particles filled a very broad region around the Sun. The active region was located at the solar backside (as seen from Earth) and was the source of a large flare, a fast and wide coronal mass ejection, and an EIT wave, accompanied by type II and type III radio-emission. In contrast to previous solar energetic particle events showing broad longitudinal spread, this event showed clear particle anisotropies at three widely separated observation points at 1AU, suggesting direct particle injection close to the magnetic footpoint of each spacecraft, lasting for several hours.We discuss these observations and the possible scenarios explaining the extremely broad particle spread for this event.

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A systematic averaging procedure has been derived in order to obtain an integral form of conservation equations for dispersed multiphase flow, especially applicable to fluidized beds. A similar averaging method is applied further to formulate macroscopic integral equations, which can be used in one-dimensional and macroscopic multi dimensional models. Circulating fluid bed hydrodynamics has been studied experimentally and both macroscopic and microscopic flow profiles have been measured in a cold model. As an application of the theory, the one dimensional model has been used to study mass and momentum conservation of gas and solid in a circulating fluid bed. Axial solid mixing has also been modelled by the one dimensional model and mixing parameters have been evaluated.

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With the occurrence of fossil fuels such as oil, gas and coal we found new sources of energy that have played a critical role in the progress of our modern society. Coal is very ample compared to the other two fossil fuels. Global coal reserves at the end of 2005 were estimated at 847,5 billion tones. Along with the major energy sources, coal is the most fast growing fuel on a global basis, it provides 26% of primary energy needs and remains essential to the economies of many developed and developing countries. Coal-fired power generation accounts for 41% of the world‘s total electricity production and in some countries, such as South Africa, Poland, China, Australia, Kazakhstan and India is on very high level. Still, coal utilization represents challenges related to high emissions of air pollutants such as sulphur and nitrogen dioxides, particulate matter, mercury and carbon dioxide. In relation to these a number of technologies have been developed and are in marketable use, with further potential developments towards ―Near Zero Emission‖ coal plants. In present work, coals mined in Russia and countries of Former Soviet Union were reviewed. Distribution of coal reserves on the territory of Russia and the potential for power generation from coal-fired plants across Russia was shown. Physical and chemical properties of coals produced were listed and examined, as main factor influencing on design of the combustion facility and incineration process performance. The ash-related problems in coal-fired boilers were described. The analysis of coal ash of Russia and countries of Former Soviet Union were prepared. Feasible combustion technologies also were reviewed.

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The knowledge of the slug flow characteristics is very important when designing pipelines and process equipment. When the intermittences typical in slug flow occurs, the fluctuations of the flow variables bring additional concern to the designer. Focusing on this subject the present work discloses the experimental data on slug flow characteristics occurring in a large-size, large-scale facility. The results were compared with data provided by mechanistic slug flow models in order to verify their reliability when modelling actual flow conditions. Experiments were done with natural gas and oil or water as the liquid phase. To compute the frequency and velocity of the slug cell and to calculate the length of the elongated bubble and liquid slug one used two pressure transducers measuring the pressure drop across the pipe diameter at different axial locations. A third pressure transducer measured the pressure drop between two axial location 200 m apart. The experimental data were compared with results of Camargo's1 algorithm (1991, 1993), which uses the basics of Dukler & Hubbard's (1975) slug flow model, and those calculated by the transient two-phase flow simulator OLGA.

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The purpose of this study is to investigate whether there exists any kind of relationship between the spot and future prices of the different commodities or not. Commodities like cocoa, coffee, crude oil, gold, natural gas and silver are considered from January 3, 2000 to December 31, 2012. For this purpose, ADF test and KPSS test are used in testing the stationarity whereas Johansen Cointegration test is used in testing the long-run relationship. Johansen co-integration test exhibits that there at least 5 co-integrating pairs out of 6 except crude oil. Moreover, the result of Granger Causality supports the fact that if two or more than two time series tend to be co-integrated there exists either uni-directional or bi-directional relationship. However, our results reveled that although there exists the co-integration between the variable, one might not granger causes another .VAR model is also used to measure the proportion of effects. These findings will help the derivative market and arbitragers in developing the strategies to gain the maximum profit in the financial market.

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The report presents the results of the commercialization project called the Container logistic services for forest bioenergy. The project promotes new business that is emerging around overall container logistic services in the bioenergy sector. The results assess the European markets of the container logistics for biomass, enablers for new business creation and required service bundles for the concept. We also demonstrate the customer value of the container logistic services for different market segments. The concept analysis is based on concept mapping, quality function deployment process (QFD) and business network analysis. The business network analysis assesses key shareholders and their mutual connections. The performance of the roadside chipping chain is analysed by the logistic cost simulation, RFID system demonstration and freezing tests. The EU has set the renewable energy target to 20 % in 2020 of which Biomass could account for two-thirds. In the Europe, the production of wood fuels was 132.9 million solid-m3 in 2012 and production of wood chips and particles was 69.0 million solidm3. The wood-based chips and particle flows are suitable for container transportation providing market of 180.6 million loose- m3 which mean 4.5 million container loads per year. The intermodal logistics of trucks and trains are promising for the composite containers because the biomass does not freeze onto the inner surfaces in the unloading situations. The overall service concept includes several packages: container rental, container maintenance, terminal services, RFID-tracking service, and simulation and ERP-integration service. The container rental and maintenance would provide transportation entrepreneurs a way to increase the capacity without high investment costs. The RFID-concept would lead to better work planning improving profitability throughout the logistic chain and simulation supports fuel supply optimization.

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This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.

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Air pollution has been associated with health effects on different age groups. The present study was designed to assess the impact of daily changes in air pollutants (NO2, SO2, CO, O3, and particle matter (PM10)) on total number of daily neonatal deaths (those that occur between the first and the 28th days of life) in São Paulo, from January 1998 to December 2000, since adverse outcomes such as neonatal deaths associated with air pollution in Brazil have not been evaluated before. Generalized additive Poisson regression models were used and nonparametric smooth functions (loess) were adopted to control long-term trend, temperature, humidity, and short-term trends. A linear term was used for holidays. The association between air pollutants and neonatal deaths showed a short time lag. Interquartile range increases in PM10 (23.3 µg/m³) and SO2 (9.2 µg/m³) were associated with increases of 4% (95% CI, 2-6) and 6% (95% CI, 4-8), respectively. Instead of adopting a two-pollutant model we created an index to represent PM10 and SO2 effects. For an interquartile range increase in the index an increase of 6.3% (95% CI, 6.1-6.5) in neonatal deaths was observed. These results agree with previous studies performed by our group showing the deleterious effects of air pollutants during the perinatal period. The method reported here represents an alternative approach to analyze the relationship between highly correlated pollutants and public health problems, reinforcing the idea of the synergic effects of air pollutants in public health.

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The arterial partial pressure (P CO2) of carbon dioxide is virtually constant because of the close match between the metabolic production of this gas and its excretion via breathing. Blood gas homeostasis does not rely solely on changes in lung ventilation, but also to a considerable extent on circulatory adjustments that regulate the transport of CO2 from its sites of production to the lungs. The neural mechanisms that coordinate circulatory and ventilatory changes to achieve blood gas homeostasis are the subject of this review. Emphasis will be placed on the control of sympathetic outflow by central chemoreceptors. High levels of CO2 exert an excitatory effect on sympathetic outflow that is mediated by specialized chemoreceptors such as the neurons located in the retrotrapezoid region. In addition, high CO2 causes an aversive awareness in conscious animals, activating wake-promoting pathways such as the noradrenergic neurons. These neuronal groups, which may also be directly activated by brain acidification, have projections that contribute to the CO2-induced rise in breathing and sympathetic outflow. However, since the level of activity of the retrotrapezoid nucleus is regulated by converging inputs from wake-promoting systems, behavior-specific inputs from higher centers and by chemical drive, the main focus of the present manuscript is to review the contribution of central chemoreceptors to the control of autonomic and respiratory mechanisms.

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Crystal properties, product quality and particle size are determined by the operating conditions in the crystallization process. Thus, in order to obtain desired end-products, the crystallization process should be effectively controlled based on reliable kinetic information, which can be provided by powerful analytical tools such as Raman spectrometry and thermal analysis. The present research work studied various crystallization processes such as reactive crystallization, precipitation with anti-solvent and evaporation crystallization. The goal of the work was to understand more comprehensively the fundamentals, phenomena and utilizations of crystallization, and establish proper methods to control particle size distribution, especially for three phase gas-liquid-solid crystallization systems. As a part of the solid-liquid equilibrium studies in this work, prediction of KCl solubility in a MgCl2-KCl-H2O system was studied theoretically. Additionally, a solubility prediction model by Pitzer thermodynamic model was investigated based on solubility measurements of potassium dihydrogen phosphate with the presence of non-electronic organic substances in aqueous solutions. The prediction model helps to extend literature data and offers an easy and economical way to choose solvent for anti-solvent precipitation. Using experimental and modern analytical methods, precipitation kinetics and mass transfer in reactive crystallization of magnesium carbonate hydrates with magnesium hydroxide slurry and CO2 gas were systematically investigated. The obtained results gave deeper insight into gas-liquid-solid interactions and the mechanisms of this heterogeneous crystallization process. The research approach developed can provide theoretical guidance and act as a useful reference to promote development of gas-liquid reactive crystallization. Gas-liquid mass transfer of absorption in the presence of solid particles in a stirred tank was investigated in order to gain understanding of how different-sized particles interact with gas bubbles. Based on obtained volumetric mass transfer coefficient values, it was found that the influence of the presence of small particles on gas-liquid mass transfer cannot be ignored since there are interactions between bubbles and particles. Raman spectrometry was successfully applied for liquid and solids analysis in semi-batch anti-solvent precipitation and evaporation crystallization. Real-time information such as supersaturation, formation of precipitates and identification of crystal polymorphs could be obtained by Raman spectrometry. The solubility prediction models, monitoring methods for precipitation and empirical model for absorption developed in this study together with the methodologies used gives valuable information for aspects of industrial crystallization. Furthermore, Raman analysis was seen to be a potential controlling method for various crystallization processes.

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This thesis is done as a part of the NEOCARBON project. The aim of NEOCARBON project is to study a fully renewable energy system utilizing Power-to-Gas or Power-to-Liquid technology for energy storage. Power-to-Gas consists of two main operations: Hydrogen production via electrolysis and methane production via methanation. Methanation requires carbon dioxide and hydrogen as a raw material. This thesis studies the potential carbon dioxide sources within Finland. The different sources are ranked using the cost and energy penalty of the carbon capture, carbon biogenity and compatibility with Power-to-Gas. It can be concluded that in Finland there exists enough CO2 point sources to provide national PtG system with sufficient amounts of carbon. Pulp and paper industry is single largest producer of biogenic CO2 in Finland. It is possible to obtain single unit capable of grid balancing operations and energy transformations via Power-to-Gas and Gas-to-Power by coupling biogas plants with biomethanation and CHP units.