Made available in DSpace on 2017-07-10T17:40:44Z (GMT). No. of bitstreams: 1 Gilberto_Alves_Fereira.pdf: 2149647 bytes, checksum: cf5d015f2b3d6a66b8343e8244e8da51 (MD5) Previous issue date: 2013-08-22 / The use of forage species in production systems such as integrated crop livestock can be key to improving fertility and increasing productivity of pastures and crops. The objective this study was to evaluate the effects height of grazing of Brachiaria ruziziensis on straw production, on the physical properties of the soil, in levels and stocks of carbon and nitrogen of the soil and in the soybean yield in crop livestock integration system. The experiment was conducted in the Experimental Farm of the Agronomic Institute of Paraná (IAPAR), located in the municipality of Xambrê-PR, in september 2010 to april 2012, during the agricultural year 2010/2011 and 2011/2012. The experimental design used was randomized in blocks, split plot in time (sampling time), with five treatments (grazing height of 10, 20, 30 and 40 cm and an area with no grazing) and three repetitions. Were determined the dry matter the mass of the aerial part of Brachiaria ruziziensis, vegetable residue dry matter and mass of total dry matter. The layers of 0-10, 10-20 and 20-30 cm were studied the density, macroporosity, microporosity, total porosity, gravimetric water, levels and stocks of total organic carbon, particulate carbon and carbon associated with minerals and the levels and stocks of mineral nitrogen and total of the soil. In culture of soy were evaluated the number of plants per meter, height of plants and grain productivity. The dry matter mass of the aerial part of Brachiaria ruziziensis and the total dry matter mass were significant (P<0,05) in the two seasons of evaluation, with higher production in the ungrazed compared to grazed area (P<0,05). The variable dry matter of plant residue was not significant (P>0,05) for the first time and significant in second season (P<0,05). The density, macroporosity, microporosity, total porosity and gravimetric soil moisture were not altered by grazing height and area not grazed at all depths evaluated (P>0,05). Density reduction occurred, increase macroporosity and total porosity in the 0-10 cm layer of soil, at the end of the experiment (P<0,05). There was a higher microporosity after brachiaria in relation to the time after the soybean crop (P <0,05). The levels and stocks of total organic carbon of the soil and its fractions, besides levels and stocks of mineral and total nitrogen of the soil were not altered by grazing heights and the area not grazed (P>0,05). However, there was an increase in levels and stocks of total organic carbon and carbon associated with minerals and a reduction of the particulate carbon of the soil in the final experiment (P<0,05). There was an increase of mineral nitrogen after harvest soybeans for all soil layers (P<0,05), however, the increase of total nitrogen and stocks of the soil occurred only in the 0-10 cm depth, in the last evaluation. The number of plants per meter, plant height and yield of soybean were not affected by the different Heights and the absence of grazing (P>0,05) / O emprego de espécies forrageiras em sistemas de produção como a integração lavoura pecuária pode ser determinante para a melhoria da fertilidade e incremento de produtividade das pastagens e das culturas. O objetivo deste trabalho foi avaliar os efeitos da altura de pastejo de Brachiaria ruziziensis na produção de palhada, nas propriedades físicas do solo, nos teores e estoques de carbono e nitrogênio do solo e na produtividade da soja em sistema de integração lavoura pecuária. O experimento foi conduzido em área da Fazenda Experimental do Instituto Agronômico do Paraná (IAPAR), localizada no município de Xambrê-PR, no período de setembro de 2010 a abril de 2012, durante os anos agrícolas de 2010/2011 e 2011/2012. O delineamento experimental utilizado foi em blocos ao acaso, em parcelas subdivididas no tempo (época de amostragem), com cinco tratamentos (altura de pastejo de 10, 20, 30 e 40 cm e uma área sem pastejo) e três repetições. Foram determinadas a massa de matéria seca da parte aérea de Brachiaria ruziziensis, matéria seca de resíduo vegetal e massa de matéria seca total. Nas camadas de 0-10, 10-20 e 20-30 cm foram estudadas a densidade, macroporosidade, microporosidade, porosidade total, água gravimétrica, teores e estoques de carbono orgânico total, carbono particulado e carbono associados aos minerais do solo e os teores e estoque de nitrogênio mineral e total do solo. Na cultura da soja foram avaliadas o número de plantas por metro, altura das plantas e produtividade de grãos. A massa de matéria seca da parte aérea de Brachiaria ruziziensis e a massa de matéria seca total foram significativas (P<0,05) nas duas épocas de avaliação, com maior produção na área sem pastejo em relação às áreas pastejadas (P<0,05). Já a variável matéria seca de resíduo vegetal não foi significativa (P>0,05) para a primeira época e significativo na segunda época (P<0,05). A densidade, macroporosidade, microporosidade, porosidade total e umidade gravimétrica do solo não foram alteradas pelas alturas de pastejo e área não pastejada em todas as profundidades avaliadas (P>0,05). Ocorreu redução da densidade, aumento da macroporosidade e da porosidade total na camada 0-10 cm do solo, ao final do experimento (P<0,05). Houve maior microporosidade após a braquiária em relação à época após a cultura da soja (P<0,05). Os teores e estoques de carbono orgânico total do solo e suas respectivas frações, além dos teores e estoques de nitrogênio mineral e total do solo não foram alteradas pelas alturas de pastejo e a área não pastejada (P>0,05). Todavia, ocorreu aumento dos teores e estoques de carbono orgânico total e carbono associado aos minerais e redução do carbono particulado do solo ao final do experimento (P<0,05). Houve aumento do nitrogênio mineral após a colheita da soja para todas as camadas do solo (P<0,05), porém, o aumento do nitrogênio total do solo e seus estoques ocorreram apenas na profundidade 0-10 cm, na última avaliação. O número de plantas por metro, a altura das plantas e a produtividade da cultura da soja não foram influenciados pelas diferentes alturas e pela ausência do pastejo (P>0,05)

Preparation of thermoplastics composites using engineering thermoplastics and plant fibers or fillers is a technical challenge because the processing temperature of the thermoplastics is generally above the temperature of degradation of plant fibers of fillers. There have been numerous attempts for processing high melting point engineering thermoplastics like Nylon-6 with plant natural fibers and fillers. Low temperature processing methods, fiber modification or addition of additives which drops polymer melting point are some of proposed solutions for this problem. The objective of this thesis was to develop a formulation using wheat straw (WS) as a reinforcing fiber for Nylon-6. The concentration of WS was 15 wt-%. The thermoplastic composites were prepared by mixing grinded wheat straw and Nylon-6 using a laboratory scale twin-screw extruder; follow by preparation of samples using injection moulding. The strategy investigated in this thesis was utilization of additives to lower the melting point or to decrease the viscosity of Nylon-6. Lithium chloride salt (LiCl) and N-Butyl benzene Sulfon amide plasticizer (N-BBSA) were used as process additives to decrease melting point and to reduce the processing temperature and time. The addition of the wheat straw (15 wt-%) to the Nylon-6 increased modulus by 26.9 % but decreased the strength by 9.9 %. Effect of different level of these two additives on mechanical, thermal, physical properties and processability of the composite runs were studied. Addition of 4 wt-% LiCl was found to decrease the melting point from 222 °C to 191 °C, to increase modulus by 14 % in comparison to Nylon-6/wheat straw (15 wt-%). However, it decreased the processability and strength by 12.7 %. Plasticizer was investigated to easing processability and decreasing the degradation by reducing the residence time in the extruder, it does not affect the melting point of Nylon-6. The addition of 4 wt-% of plasticizer (N-BBSA) increased modulus and strength only by 2.6 % and 3 %, respectively, in comparison to Nylon-6/wheat straw (15 wt-%) composites. The results of mechanical properties were used as a benchmark for comparisons among samples with different formulations (levels of additives) to find out levels of LiCl and N-BBSA for the best mechanical properties. It was found that samples with 2 wt-% LiCl and 2 wt-% of N-BBSA had 29.3 % higher tensile modulus than neat Nylon-6, while its strength was almost same as neat Nylon-6 and 6.3 % higher than Nylon-6/WS (15 wt-%). These results were used to correlate the mechanical properties as a function of percentage of salt and plasticizer in the formulation. Differential scanning calorimetry (DSC) was used to evaluate the percentage of crystallinity and the melting point of the thermoplastic phase and thermal gravimetric analysis (TGA) was used to measure the thermal stability of different formulation. The kinetics of crystallization and degradation were evaluated using results from DSC and TGA, respectively. The activation energy for thermal degradation and the percentage of crystallinity of the thermoplastic composites were correlated to mechanical properties using linear regression. It was found that fiber degradation had a significant effect on strength but the effects of percentage of crystallinity on composites strength were insignificant. On the other hand, the percentage of crystallinity affects stiffness and impact strength. The ductility was a function of both crystallinity and thermal stability.

Allyl methacrylate, AMA was polymerized by chemical initiator and by &amp / #947 / -radiation under different conditions. The polymer obtained is mostly gel type with some soluble fractions at lower conversions. Arrhenius activation energy is 82.3 kJ/mol for chemical initiated polymerization. The polymer was characterized by FT-IR, NMR, DSC, TGA, XPS, XRD, DLS, and MS methods. It was found that about 98-99% of allyl side groups retained as pendant even after completion of the polymerization, while 1-2% may give crosslinking and/or cyclization that yields lactones and anhydrides. The spectroscopic and thermal results of the work showed that the reaction is not cyclopolymerization, but may have end group cyclization. Molecular weight of 1.1x106 was measured by DLS. Therefore, insolubility is due to the high molecular weight of polymer, even in the early stage of polymerization rather than crosslinking. The Tg of PAMA was observed as 94&ordm / C before curing, upon curing at 150-200&ordm / C, Tg increased to 211&ordm / C as measured by DSC. The thermal treatment of polymer at about 350&ordm / C gave anhydride by linkage type degradation, following side group cyclization. The XPS analysis showed the presence of radical fragments of AIBN and CCl4 associated with oligomers. The MS and TGA thermograms showed two or three stage degradations depending on solubility. The first stage was mostly linkage type degradation for the fragmentation of pendant allyl groups at 225-350&ordm / C. In the second stage, at 395-515&ordm / C, the degradation is random scission and depolymerization.

This thesis reports design and implementation of a MEMS based gravimetric resonator for cytometry applications. There are mainly two objectives of this thesis / to enable in-flow analysis and to perform closed loop operation that does not require any additional processing or equipment. A novel MEMS based resonator with in-flow capabilities is proposed for detection of agents inside micro channels. High resolution of mass detection inside micro channels is planned to be succeeded with lateral motion in the micro channel floor. The idea embedding lateral resonators emerges from decreasing squeeze film damping during the motion of the resonator. Lateral motion is supported by hydrophobic parylene coating to decrease the damping. Theory and design of the gravimetric resonators are explained and the fabrication flow is constructed and performed successfully by combining SOI, SOG and polymer micro fabrication techniques. Problems during the fabrication are overcome and optimized flow is presented. The devices have a foot print area of 1.5 x 0.5 cm2 which is mainly composed of reservoirs for fluidic connections. Ten types of devices are designed according to their mass sensitivities and compliances. Trade offs between frequency, injected current, and compliance are analyzed successfully by taking also the performance parameters of the interface electronics in to account. Test results reveal that single latex bead with 3 &micro / m diameter and 14.127 pg mass can be sensed successfully and mass sensitivity is measured to be 5.91 fg/Hz for this type of device.

Preparation of thermoplastics composites using engineering thermoplastics and plant fibers or fillers is a technical challenge because the processing temperature of the thermoplastics is generally above the temperature of degradation of plant fibers of fillers. There have been numerous attempts for processing high melting point engineering thermoplastics like Nylon-6 with plant natural fibers and fillers. Low temperature processing methods, fiber modification or addition of additives which drops polymer melting point are some of proposed solutions for this problem. The objective of this thesis was to develop a formulation using wheat straw (WS) as a reinforcing fiber for Nylon-6. The concentration of WS was 15 wt-%. The thermoplastic composites were prepared by mixing grinded wheat straw and Nylon-6 using a laboratory scale twin-screw extruder; follow by preparation of samples using injection moulding. The strategy investigated in this thesis was utilization of additives to lower the melting point or to decrease the viscosity of Nylon-6. Lithium chloride salt (LiCl) and N-Butyl benzene Sulfon amide plasticizer (N-BBSA) were used as process additives to decrease melting point and to reduce the processing temperature and time. The addition of the wheat straw (15 wt-%) to the Nylon-6 increased modulus by 26.9 % but decreased the strength by 9.9 %. Effect of different level of these two additives on mechanical, thermal, physical properties and processability of the composite runs were studied. Addition of 4 wt-% LiCl was found to decrease the melting point from 222 °C to 191 °C, to increase modulus by 14 % in comparison to Nylon-6/wheat straw (15 wt-%). However, it decreased the processability and strength by 12.7 %. Plasticizer was investigated to easing processability and decreasing the degradation by reducing the residence time in the extruder, it does not affect the melting point of Nylon-6. The addition of 4 wt-% of plasticizer (N-BBSA) increased modulus and strength only by 2.6 % and 3 %, respectively, in comparison to Nylon-6/wheat straw (15 wt-%) composites. The results of mechanical properties were used as a benchmark for comparisons among samples with different formulations (levels of additives) to find out levels of LiCl and N-BBSA for the best mechanical properties. It was found that samples with 2 wt-% LiCl and 2 wt-% of N-BBSA had 29.3 % higher tensile modulus than neat Nylon-6, while its strength was almost same as neat Nylon-6 and 6.3 % higher than Nylon-6/WS (15 wt-%). These results were used to correlate the mechanical properties as a function of percentage of salt and plasticizer in the formulation. Differential scanning calorimetry (DSC) was used to evaluate the percentage of crystallinity and the melting point of the thermoplastic phase and thermal gravimetric analysis (TGA) was used to measure the thermal stability of different formulation. The kinetics of crystallization and degradation were evaluated using results from DSC and TGA, respectively. The activation energy for thermal degradation and the percentage of crystallinity of the thermoplastic composites were correlated to mechanical properties using linear regression. It was found that fiber degradation had a significant effect on strength but the effects of percentage of crystallinity on composites strength were insignificant. On the other hand, the percentage of crystallinity affects stiffness and impact strength. The ductility was a function of both crystallinity and thermal stability.

In the field of chemical and biological sensors, the increased need for better sensitivity, faster response and higher selectivity during an analysis process, requires the development of more and more efficient transducing sensing layers. In this context, and with the aim to detect small non-electroactive molecules, such as atrazine (ATZ), we designed, characterized and developed sensing layers constituted by functionalized Molecularly Imprinted Conducting Polymers (MICP) and we integrated them into electrochemical and gravimetrical sensors. Starting from acetonitrile pre-polymerization media containing ATZ as template molecules in the presence of thiophene-based functional monomers (FM, namely TMA, TAA, EDOT, TMeOH or Th), differently functionalized and structurally different polythiophene-based FM-MICP films were electrosynthesized onto gold substrates and used for ATZ detection. The sensing properties of FM-MICP layers were shown to result from the presence in their backbones of pre-shaped FM-functionalized imprinted cavities which keep the memory of the targets. Nevertheless, non-specific adsorption onto the surface of the sensing layers takes place systematically, which affects the selectivity of the recognition process. Thanks to surface characterization techniques, we highlighted the influence of the thickness and of the structural properties of the layers on the efficiency of the recognition process. Besides, this latter was shown to operate in the bulk of the polymer matrixes thanks to layers porosity. On another hand, electrochemical measurements correlated with semi-empirical calculations demonstrated the influence of the nature of FM on the strength of the ATZ-FM interaction in the pre-polymerization medium, and then on the number of ATZ molecular imprints and on the sensitivity towards ATZ of the FM-MICP layers. We showed that TAA-MICP, which presents a low limit of detection (10-9 mol L-1) and a large dynamic range (10-8 to 10-4 mol L-1), is the best sensing layer since it offers the best compromise between high level of specific detection of ATZ and low level of non-specific adsorption. Finally, TAA-MICP was used as sensitive layer in an original Electrochemical Surface Acoustic Wave sensor (ESAW) which enabled simultaneous coupled gravimetric and electrochemical measurements.

O teor de água no solo é um dos fatores determinantes nos processos de transferência entre o solo e a atmosfera, contribuindo nos balanços de água e de energia. Esse teor é influenciado pelas entradas de água na bacia hidrográfica, por características climáticas, topográficas, de cobertura vegetal, práticas de manejo agrícola e propriedades do solo. A grande heterogeneidade desses fatores faz com que a caracterização desse teor seja ainda um grande desafio. Essa pesquisa objetivou desenvolver abordagens baseadas em Redes Neurais Artificiais (RNAs) para determinação da variação espacial e temporal do teor de água no solo, utilizando informações climáticas, propriedade físicas do solo e variáveis topográficas de uma bacia hidrográfica, com área aproximada de 78 km², localizada na Região Sul do Brasil (bacia do Taboão). A RNA adotada é uma rede de duas camadas, com 25 neurônios na camada intermediária, sendo o treinamento realizado por meio do algoritmo retropropagativo, considerando16 iterações iniciais dos pesos sinápticos, e número máximo de ciclos igual a 30.000. No total foram testadas 40 variáveis de entrada, sendo quatro referentes à topografia (altitude, declividade, distância do ponto ao trecho do rio mais próximo e desnível do ponto ao trecho mais próximo do rio); oito relacionadas ao solo (tipo de solo, densidade do solo, resistência à penetração no solo para as camadas de 0 a 20 cm e 20 a 40 cm, tensão da água no solo em apenas um ponto na bacia e percentual de argila, silte e areia), 10 relativas ao clima (clima, evapotranspiração de referência, temperatura do ar máxima e temperatura do ar, umidade relativa do ar máxima e umidade relativa do ar mínima, pressão atmosférica, radiação solar global, velocidade do vento e temperatura na relva), e 18 variáveis de chuva (chuva de 1, 2, 3, 4, 5, 6 e 12h; chuva de 1, 2, 3, 5, 10, 15, 20, 25 e 30 dias; chuva média ponderada horária; chuva média ponderada diária). A saída dos modelos foi comparada com valores de umidade gravimétrica determinados por amostras coletadas em 26 pontos da bacia, distribuídos espacialmente na bacia, no período compreendido entre 15/01 e 10/08/2013. Neste período o teor de água no solo (umidade gravimétrica) variou entre 13,73 e 33,75%. Os resultados demonstram que é possível estimar o teor de água no solo, com distribuição espacial e temporal, com boa eficiência (NSverificação = 0,77), empregando dados topográficos da bacia, propriedades físicas do solo e dados de chuva. As informações climáticas, por outro lado, não afetam significativamente essa estimativa (NSv=0,28), podendo até diminuir a eficiência do modelo (NSv=0,77 para NSv=0,68). O emprego de muitas variáveis não gera necessariamente o melhor desempenho do modelo, pois uma variável pode mascarar a outra e, até mesmo, interferir a eficiência do modelo (NSv=0,70 e NS=0,61 para os modelos onde foram utilizadas 38 variáveis de entrada), além de aumentar o custo e o tempo para aquisição dessas variáveis, e a dificuldade de interpretação dos resultados em relação às várias entradas. Alternativamente, pode-se estimar o teor de água no solo utilizando modelos mais simplificados que empregam dados de chuva monitorados e informações extraídas de mapas (topografia e tipo de solo), mas o desempenho desses modelos é menor (NSv 0,66). A análise de importância das variáveis de entrada delimitou a tensão da água no solo e a chuva como as variáveis mais influentes nos modelos de melhor desempenho, e a densidade do solo como a menos importante. Nos modelos mais simples, a variável menos relevante é a declividade e a mais importante é a chuva. A análise de sensibilidade demonstrou que nem sempre os modelos conseguem reproduzir o que deveria ocorrer no ambiente natural. / The water content in the soil is one of the determining factors in the transfer processes between the soil and the atmosphere, contributing to the balances of water and energy. This content is influenced by inputs to the basin, climate characteristics, topography, land cover characteristics, agricultural practices, and soil properties. These wide heterogeneity factors make the soil water content characterization still a challenge. This research aimed to develop an Artificial Neural Network (ANN) model to determine the spatial and temporal variation of the water content in the soil, using climate data, physical properties of soil, and topographic variables, of a basin with an area of approximately 78 km2, located in Brazil`s southern region (Taboão basin). The model adopted is a double layer feedforward neural network with 25 neurons in the hidden layer. The learning method is the back propagation algorithm, with 16 interactions to avoid local minima, and the maximum number of cycles chosen was 30,000. A total of 40 input variables were tested, including four of topography (altitude, slope, distance from the point to the nearest stretch of river and unevenness of the point closest to the stretch of the river), eight of soil related variables (soil type, soil density, soil penetration resistance for layers from 0 to 20 cm and from 20 to 40 cm, soil water tension at a single point in the basin and percentage of clay, silt and sand), 10 climate-related variables (climate, evapotranspiration reference, maximum and minimum air temperature, maximum and minimum air relative humidity, atmospheric pressure, global solar radiation, wind speed and temperature on grass) and 18 variables related to rain (accumulated precipitation in 1, 2, 3, 4, 5, 6 e 12h; accumulated precipitation in 2, 3, 5, 10, 15, 20, 25 and 30 days; weighted hourly accumulated precipitation; weighted daily accumulated precipitation). The outputs of the models were compared with values determined by gravimetric moisture samples collected from 26 points spatially distributed in the basin, in the period between 15/01 and 10/08/2013. During this period the soil water content (gravimetric water content) ranged from 13.73 to 33.75%. The results show that it is possible to estimate the water content of the soil, temporal and spatial distribution, with good efficiency (NSverication = 0.77), using topographic data from the basin, soil physical properties and precipitation data. The weather information, on the other hand, did not significantly affect the estimate (NSv = 0.28) and may even decrease the efficiency (NSv) of the model (from 0.77 to 0.68). The use of many variables not necessarily generates the best performance of the model as a variable may mask another and even disrupt the efficiency of the model (NSv = 0.70 and NSv = 0.61, where 38 input variables were used), besides increasing the cost and the time to acquire these variables, and the difficulty of interpreting the results in relation to the various inputs. Alternatively, one can estimate the water content in soil using more simplified models, employing monitored rainfall data and information extracted from maps (topography and soil type), but the performance of these models is smaller (NSv 0.66). The analysis of the importance of input variables delimited the soil water tension and the rain as the most influential variables in the best models, and the density of the soil as the least important. In the simplest models, the less relevant variable is the slope and the most important is the rain. The sensitivity analysis showed that the models cannot always play what should occur in the natural environment.

O teor de água no solo é um dos fatores determinantes nos processos de transferência entre o solo e a atmosfera, contribuindo nos balanços de água e de energia. Esse teor é influenciado pelas entradas de água na bacia hidrográfica, por características climáticas, topográficas, de cobertura vegetal, práticas de manejo agrícola e propriedades do solo. A grande heterogeneidade desses fatores faz com que a caracterização desse teor seja ainda um grande desafio. Essa pesquisa objetivou desenvolver abordagens baseadas em Redes Neurais Artificiais (RNAs) para determinação da variação espacial e temporal do teor de água no solo, utilizando informações climáticas, propriedade físicas do solo e variáveis topográficas de uma bacia hidrográfica, com área aproximada de 78 km², localizada na Região Sul do Brasil (bacia do Taboão). A RNA adotada é uma rede de duas camadas, com 25 neurônios na camada intermediária, sendo o treinamento realizado por meio do algoritmo retropropagativo, considerando16 iterações iniciais dos pesos sinápticos, e número máximo de ciclos igual a 30.000. No total foram testadas 40 variáveis de entrada, sendo quatro referentes à topografia (altitude, declividade, distância do ponto ao trecho do rio mais próximo e desnível do ponto ao trecho mais próximo do rio); oito relacionadas ao solo (tipo de solo, densidade do solo, resistência à penetração no solo para as camadas de 0 a 20 cm e 20 a 40 cm, tensão da água no solo em apenas um ponto na bacia e percentual de argila, silte e areia), 10 relativas ao clima (clima, evapotranspiração de referência, temperatura do ar máxima e temperatura do ar, umidade relativa do ar máxima e umidade relativa do ar mínima, pressão atmosférica, radiação solar global, velocidade do vento e temperatura na relva), e 18 variáveis de chuva (chuva de 1, 2, 3, 4, 5, 6 e 12h; chuva de 1, 2, 3, 5, 10, 15, 20, 25 e 30 dias; chuva média ponderada horária; chuva média ponderada diária). A saída dos modelos foi comparada com valores de umidade gravimétrica determinados por amostras coletadas em 26 pontos da bacia, distribuídos espacialmente na bacia, no período compreendido entre 15/01 e 10/08/2013. Neste período o teor de água no solo (umidade gravimétrica) variou entre 13,73 e 33,75%. Os resultados demonstram que é possível estimar o teor de água no solo, com distribuição espacial e temporal, com boa eficiência (NSverificação = 0,77), empregando dados topográficos da bacia, propriedades físicas do solo e dados de chuva. As informações climáticas, por outro lado, não afetam significativamente essa estimativa (NSv=0,28), podendo até diminuir a eficiência do modelo (NSv=0,77 para NSv=0,68). O emprego de muitas variáveis não gera necessariamente o melhor desempenho do modelo, pois uma variável pode mascarar a outra e, até mesmo, interferir a eficiência do modelo (NSv=0,70 e NS=0,61 para os modelos onde foram utilizadas 38 variáveis de entrada), além de aumentar o custo e o tempo para aquisição dessas variáveis, e a dificuldade de interpretação dos resultados em relação às várias entradas. Alternativamente, pode-se estimar o teor de água no solo utilizando modelos mais simplificados que empregam dados de chuva monitorados e informações extraídas de mapas (topografia e tipo de solo), mas o desempenho desses modelos é menor (NSv 0,66). A análise de importância das variáveis de entrada delimitou a tensão da água no solo e a chuva como as variáveis mais influentes nos modelos de melhor desempenho, e a densidade do solo como a menos importante. Nos modelos mais simples, a variável menos relevante é a declividade e a mais importante é a chuva. A análise de sensibilidade demonstrou que nem sempre os modelos conseguem reproduzir o que deveria ocorrer no ambiente natural. / The water content in the soil is one of the determining factors in the transfer processes between the soil and the atmosphere, contributing to the balances of water and energy. This content is influenced by inputs to the basin, climate characteristics, topography, land cover characteristics, agricultural practices, and soil properties. These wide heterogeneity factors make the soil water content characterization still a challenge. This research aimed to develop an Artificial Neural Network (ANN) model to determine the spatial and temporal variation of the water content in the soil, using climate data, physical properties of soil, and topographic variables, of a basin with an area of approximately 78 km2, located in Brazil`s southern region (Taboão basin). The model adopted is a double layer feedforward neural network with 25 neurons in the hidden layer. The learning method is the back propagation algorithm, with 16 interactions to avoid local minima, and the maximum number of cycles chosen was 30,000. A total of 40 input variables were tested, including four of topography (altitude, slope, distance from the point to the nearest stretch of river and unevenness of the point closest to the stretch of the river), eight of soil related variables (soil type, soil density, soil penetration resistance for layers from 0 to 20 cm and from 20 to 40 cm, soil water tension at a single point in the basin and percentage of clay, silt and sand), 10 climate-related variables (climate, evapotranspiration reference, maximum and minimum air temperature, maximum and minimum air relative humidity, atmospheric pressure, global solar radiation, wind speed and temperature on grass) and 18 variables related to rain (accumulated precipitation in 1, 2, 3, 4, 5, 6 e 12h; accumulated precipitation in 2, 3, 5, 10, 15, 20, 25 and 30 days; weighted hourly accumulated precipitation; weighted daily accumulated precipitation). The outputs of the models were compared with values determined by gravimetric moisture samples collected from 26 points spatially distributed in the basin, in the period between 15/01 and 10/08/2013. During this period the soil water content (gravimetric water content) ranged from 13.73 to 33.75%. The results show that it is possible to estimate the water content of the soil, temporal and spatial distribution, with good efficiency (NSverication = 0.77), using topographic data from the basin, soil physical properties and precipitation data. The weather information, on the other hand, did not significantly affect the estimate (NSv = 0.28) and may even decrease the efficiency (NSv) of the model (from 0.77 to 0.68). The use of many variables not necessarily generates the best performance of the model as a variable may mask another and even disrupt the efficiency of the model (NSv = 0.70 and NSv = 0.61, where 38 input variables were used), besides increasing the cost and the time to acquire these variables, and the difficulty of interpreting the results in relation to the various inputs. Alternatively, one can estimate the water content in soil using more simplified models, employing monitored rainfall data and information extracted from maps (topography and soil type), but the performance of these models is smaller (NSv 0.66). The analysis of the importance of input variables delimited the soil water tension and the rain as the most influential variables in the best models, and the density of the soil as the least important. In the simplest models, the less relevant variable is the slope and the most important is the rain. The sensitivity analysis showed that the models cannot always play what should occur in the natural environment.

Orientador: Prof. Dr. Antonio Garrido Gallego / Dissertação (mestrado) - Universidade Federal do ABC. Programa de Pós-Graduação em Energia, 2017. / Embora classificada como biomassa, no Brasil, os resíduos sólidos urbanos apresentam-se como um desafio tanto na utilização como fonte energética como também em sua destinação. Desde a promulgação da Lei 12.305 de 02 de agosto de 2010, poucas mudanças foram realizadas principalmente em relação à disposição dos resíduos. Desse montante, 42% dos resíduos gerados não são destinados em aterros sanitários e sim em lixões ou vazadouros, colocando em risco a saúde da população local quanto o meio ambiente. Tecnologias de conversão dos resíduos como fonte energética já existem em vários países do mundo inclusive para minimizar a problemática de armazenamento, e apesar da matriz energética brasileira ser em grande parte renovável, o processo termoquímico de conversão dos resíduos ainda não está implantado para fins comerciais. Neste trabalho pretendeu-se analisar a influência da umidade e da composição gravimétrica dos resíduos sólidos urbanos em específico da cidade de Santo André, em uma planta de gaseificação. Para isso foram efetuadas simulações modificando-se a umidade dos resíduos e sua composição para verificação do rendimento e eficiência da planta. O estudo foi realizado utilizando-se o ciclo Rankine e posteriormente escolhido o Rankine Orgânico para as demais simulações. Como estes resíduos não são em sua maioria homogêneos, poderão ocorrer variações do ciclo ao longo do ano aumentando ou diminuindo sua eficiência global principalmente devido a variação da umidade e do poder calorífico inferior. Foi escolhido o ciclo Rankine Orgânico por apresentar como característica principal a minimização de utilização de água. Com esse estudo pode-se verificar também a eficiência de minimização de gases de efeito estufa em especial a emissão de metano na atmosfera. Dessa forma pode-se concluir que a gaseificação em conjunto com o ciclo Rankine Orgânico se apresenta como tecnologia apropriada para mitigação de vários problemas que envolvem a destinação do RSU e utilização desses recursos. Pode-se observar também que a medida que a umidade e a quantidade de compostos orgânicos diminuem, maior é a eficiência energética da planta. / Although municipal solid waste is classified as biomass in Brazil, it presents a challenge in utilization as energetic source as well as its destination. Since the enactment of law 12,305 of August 02nd , 2010, few changes were made mainly related to waste disposal. Of this amount, 42% of the waste generated are not disposed in controlled landfills but in dumps, posing a risk to population¿s health and the environment. Waste conversion technologies as an energetic source is already exists overseas in order to minimize major issues concerning its disposal; Brazilian energy matrix is in most part renewable, although thermochemical conversion is not available for commercial purposes. The aim of this work is analyze the influence of moisture content and gravimetric composition of MSW in the city of Santo Andre in a gasification plant. Simulation of generation plant was carried out modifying the moisture content of residues and its composition to verify the yield and efficiency of the plant. This study was carried out using Rankine cycle and then Organic Rankine cycle for the remaining simulations. As these residues are not mostly homogeneous, variations of the cycle may occur throughout the year increasing or decreasing their overall efficiency concerning with humidity and low heating value variation. Organic Rankine cycle was chosen due to the main characteristic of this cycle is the minimization of water use. The efficiency related to greenhouse gases emission was also verified concerning methane emission. Thus, gasification and Organic Rankine cycle may present as an appropriate technology despite municipal solid waste destination be still a question. The maximization of the efficiency of the plant is achieved when the humidity and organic compounds decrease.

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