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Study of the Apparent Kinetics of Biomass Gasification Using High-Temperature SteamAlevanau, Aliaksandr January 2010 (has links)
Among the latest achievements in gasification technology, one may list the development of a method to preheat gasification agents using switched ceramic honey combs. The best output from this technology is achieved with use of water steam as a gasification agent, which is heated up to 1600 °C. The application of these temperatures with steam as a gasification agent provides a cleaner syngas (no nitrogen from air, cracked tars) and the ash melts into easily utilised glass-like sludge. High hydrogen content in output gas is also favourable for end-user applications.Among the other advantages of this technology is the presumable application of fixed-bed-type reactors fed by separately produced and preheated steam. This construction assumes relatively high steam flow rates to deliver the heat needed for endothermic reactions involving biomass. The biomass is to be heated uniformly and evenly in the volume of the whole reactor, providing easier and simpler control and operation in comparison to other types of reactors. To provide potential constructors and exploiters of these reactors with the kinetic data needed for the calculations of vital parameters for both reactor construction and exploitation, basic experimental research of high-temperature steam gasification of four types of industrially produced biomass has been conducted.Kinetic data have been obtained for straw and wood pellets, wood-chip charcoal and compressed charcoal of mixed origin. Experiments were conducted using two experimental facilities at the Energy and Furnace Division of the Department of Material Science and Engineering (MSE) at the School of Industrial Engineering and Management (ITM) of the Royal Institute of Technology (KTH) and at the Combustion Laboratory of the Mechanical Engineering Department of the University of Maryland (UMD), USA. The experimental facility at the Energy and Furnace Division has been improved with the addition of several constructive elements, providing better possibilities for thermo-gravimetric measurements.The obtained thermo-gravimetric data were analysed and approximated using several models described in the literature. In addition, appropriate software based on the Scilab package was developed. The implementation of the isothermal method based on optimisation algorithms has been developed and tested on the data obtained under the conditions of a slow decrease of temperature in experiments with the char gasification in small-scale experimental facilities in the Energy and Furnace Division.The composition of the gases generated during the gasification of straw and wood pellets by high-temperature steam has been recorded and analysed for different experimental conditions. / <p>QC 20101124</p> / Study of ignition and kinetics of biomass/solid waste thermal conversion with high-temperature air/steam
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Uso de redes neurais na estimativa volumétrica de clones de Eucalyptus spp no Pólo Gesseiro do Araripe, PernambucoSOUZA, Syntia Regina Rodrigues de 31 July 2015 (has links)
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Previous issue date: 2015-07-31 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / The Araripe Gypsum Pole in Pernambuco is responsible of 97% of national production of plaster. The main source of energy for the gypsum calcination process, raw material for plaster production is the wood from the natural vegetation of Caatinga. Due to the high costs of other energy sources, increasing the gypsum production implies more deforestation of the Caatinga. An economic and environmental solution for that problem is the implementation and the sustainable management of native species or the reforestation with fast growing forest species. Among the fast growing forest the genues Eucalyptus stands out for it productivity and adaptation of the Northeast semi-arid region. The objective of this study was to estimate the volume of the Eucalyptus spp clones in Gypsum Araripe Pole employing the methodology of Artificial Neural Networks (ANN) comparing it with the volumetric models of Schumacher and Hall and Spurr. Data came from an experiment implanted in the Experimental Station of the Agronomic Institute of Pernambuco, where was tested 15 clones of Eucalyptus spp planted in 2002, with final cut in 2009.The function of interest estimated was the volume of the tree in function of the diameter at the breast height (DBH), total height (Ht) and the clone type. It was also valued the adjustment of the best models for sample size. The results were evaluated with the
adjusted coefficient of determination (R2aj), square root of the percentual mean error
(RMSE%), standard error estimate (Syx%) and an analysis graphic of the residues. The obtained results confirmed the expectation showing efficiency of adjustments independent of the sample size. / O Pólo Gesseiro do Araripe em Pernambuco é responsável por 97% da produção nacional de gesso e a principal fonte de energia para o processo de calcinação da gipsita, matéria prima para produção de gesso, é a lenha proveniente da Caatinga, vegetação natural da região. Devido aos altos custos de outras fontes de energia elevar a produção de gesso implica em aumentar o desmatamento da Caatinga. Uma solução econômica e ambiental para esse problema é a implantação e o manejo sustentado de povoamento de espécies nativas ou o reflorestamento com espécies florestais de rápido crescimento. Dentre as florestas de rápido crescimento, o gênero Eucalyptus se destaca por sua alta produção e adaptabilidade ao semiárido nordestino. O objetivo deste trabalho é estimar o volume de clones de Eucalyptus spp no Pólo Gesseiro do Araripe empregando a metodologia de Redes Neurais Artificiais (RNAs) comparando-a com os modelos volumétricos de Schumacher e Hall e Spurr. Os dados são referentes a um experimento implantado na Estação Experimental do Instituto Agronômico de Pernambuco, onde foram testados 15 clones de Eucalyptus spp plantados em 2002 e com o corte final em 2009. A função de interesse estimada foi o volume da árvore (V) em relação do diâmetro a altura do peito (DAP), altura total d árvore (Ht) e tipo de clone. Também foi avaliado o ajuste dos melhores modelos por tamanho de amostra. Os resultados foram avaliados com o coeficiente de determinação ajustado (R2aj), raiz quadrada do erro médio percentual (RMSE%), o erro padrão da estimativa (Syx%) e analise dos gráficos de dispersão do resíduo. Os resultados obtidos no trabalho confirmaram a expectativa mostrando a eficiência dos ajustes independe do tamanho da amostra.
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Rekonstrukce 3D geometrie na základě diskrétních volumetrických dat / 3D Geometry Reconstruction from Discrete Volumetric DataSvěchovský, Radek January 2013 (has links)
Conversion of discrete volumetric data to boundary representation is quite common operation. Standard approach to resolve this problem is to use well-known Marching cubes algorithm, which although simple and robust, generates low-quality output that requires subsequent post-processing. This master's thesis deals with uncommon algorithms used for isosurface extraction from volumes. The reader will be acquainted with fundamental principles of Hierarchical Iso-Surface Extraction method, that was independently implemented and tested in this work.
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Investigating the parameters that influence the behaviour of natural iron ores during the iron production processMuwanguzi, Abraham Judah Bumalirivu January 2013 (has links)
In the iron production processes, sinters and pellets are mostly used as raw materials due to their consistency with respect to physical and chemical properties. However, natural iron ores, as mined, are rarely used directly as a feed material for iron processing. This is mainly due to the fact that they have small contents of iron and high concentration of impurities. Moreover, they swell and disintegrate during the descent in the furnace as well as due to low melting and softening temperatures. This work involves an investigation of the parameters that influence the use of natural iron ores as a direct feed material for iron production. Furthermore, it points out ways in which these can be mitigated so as to increase their direct use in iron production. Natural iron ore from Muko deposits in south-western Uganda was used in this study. Initially, characterisation of the physical and chemical properties was performed, to understand the natural composition of the ore. In addition, investigations were done to study the low temperature strength of the ore and its behaviour in the direct reduction zone. Also, simulations were performed with three models using the experimental data from the direct reduction experiments in order to determine the best model for predicting the direct reduction kinetics of natural iron ores. Chemical analyses showed that the Muko ore represents a high grade of hematite with an Fe content of 68% on average. The gangue content (SiO2+Al2O3) in 5 of the 6 investigated iron ore samples was < 4%, which is within the tolerable limits for the dominant iron production processes. The S and P contents were 0001-0.006% and 0.02-0.05% respectively. These can be reduced in the furnace without presenting major processing difficulties. With respect to the mechanical properties, the Muko ore was found to have a Tumble Index value of 88-93 wt%, an Abrasion Index value of 0.5-3.8 wt% and a Shatter Index value of 0.6-2.0 wt%. Therefore, the ore holds its form during the handling and charging processes. Under low temperature investigations, new parameters were discovered that influence the low temperature strength of iron oxides. It was discovered that the positioning of the samples in the reduction furnace together with the original weight (W0) of the samples, have a big influence on the low temperature strength of iron oxide. Higher mechanical degradation (MD) values were obtained in the top furnace reaction zone samples (3-25% at 500oC and 10-21% at 600oC). These were the samples that had the first contact with the reducing gas, as it was flowing through the furnace from top to bottom. Then, the MD values decreased till 5-16% at a 500oC temperature and 6-20% at a 600oC temperature in the middle and bottom reaction zones samples. It was found that the obtained difference between the MD values in the top and other zones can be more than 2 times, particularly at 500oC temperature. Furthermore, the MD values for samples with W0 < 5 g varied from 7-21% well as they decreased to 5-10% on average for samples with W0 ≥ 5 g. Moreover, the MD values for samples taken from the top reaction zone were larger than those from the middle and bottom zones. During direct reduction of the ores in a H2 and CO gas mixture with a ratio of 1.5 and a constant temperature, the reduction degree (RD) increased with a decreased flow rate until an optimum value was established. The RD also increased when the flow rate was kept constant and the temperature increased. An optimum range of 3-4g was found for natural iron ores, within which the highest RD values that are realised for all reduction conditions. In addition, the mechanical stability is greatly enhanced at RD values > 0.7. In the case of microstructure, it was observed that the original microstructure of the samples had no significant impact on the final RD value (only 2-4%). However, it significantly influenced the reduction rate and time of the DR process. The thermo-gravimetric data obtained from the reduction experiments was used to calculate the solid conversion rate. Three models: the Grain Model (GM), the Volumetric Model (VM) and the Random Pore Model (RPM), were used to estimate the reduction kinetics of natural iron ores. The random pore model (RPM) provided the best agreement with the obtained experimental results (r2 = 0.993-0.998). Furthermore, it gave a better prediction of the natural iron oxide conversion and thereby the reduction kinetics. The RPM model was used for the estimation of the effect of original microstructure and porosity of iron ore lumps on the parameters of the reduction process. / <p>QC 20130531</p> / Sustainable Technology Development in the Lake Victoria Region
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