Abstract This study used a predictive controller based on an empirical nonlinear model comprising a three-layer feedforward neural network for temperature control of the suspension polymerization process. In addition to the offline training technique, an algorithm was also analyzed for online adaptation of its parameters. For the offline training, the network was statically trained and the genetic algorithm technique was used in combination with the least squares method. For online training, the network was trained on a recurring basis and only the technique of genetic algorithms was used. In this case, only the weights and bias of the output layer neuron were modified, starting from the parameters obtained from the offline training. From the experimental results obtained in a pilot plant, a good performance was observed for the proposed control system, with superior performance for the control algorithm with online adaptation of the model, particularly with respect to the presence of off-set for the case of the fixed parameters model.

Polyacrylics have been widely used in coatings. However, their application is limited by low corrosion resistance. One way to enhance their properties is the addition of fillers with adequate properties. In this study, composite materials of PMMA and hBN were developed and deposited on steel by dip-coating. The influence of the amount of hBN in the PMMA coating regarding corrosion resistance was investigated. The surface and cross-section of the coatings were characterized by SEM, the porosity was investigated by systematic manual point count and the adhesion was classified according to the tape test standard. The produced coatings were submersed in NaCl and HCl solutions to analyze corrosion resistance. The results showed that the PMMA/hBN composite coatings improved the corrosion resistance in comparison with pure PMMA. Additionally, the coatings are crack free and well bonded to the metallic substrate.

In this work a strategy is presented for the temperature control of the polymerization reaction of styrene in suspension in batch. A three-layer feed forward Artificial Neural Network was trained in an off-line way starting from a removed group of patterns of the experimental system and applied in the recurrent form (RNN) to a Predictive Controller based on a Nonlinear Model (NMPC). This controller presented very superior results to the classic controller PID in the maintenance of the temperature. Still to improve the performance of the model used by NMPC (RNN) that can present differences in relation to the system due to the dead time involved in the control actions, nonlinear characteristic of the system and variable dynamics; an on-line adjustment methodology of the parameters of the exit layer of the Network is implemented, presenting superior results and treating the difficulties satisfactorily in the temperature control. All the presented results are obtained for a real system.

The determination of conversion during suspension polymerization reactions is not an easy task due to the heterogeneity of the reaction medium and the tendency of particles to agglomerate rapidly when stirring is stopped. Usually, bulk polymerization in ampoules is employed to study the kinetics of suspension polymerization reactions. In this work, a comparison of different techniques for the determination of conversion during suspension polymerization reactions is presented. Results showed a good agreement between the conversion obtained by gravimetry during styrene suspension polymerization and on-line conversion monitoring data using fiber-optic based Raman Spectroscopy. Nevertheless, the polymerization rate of styrene bulk polymerization carried out in ampoules was higher than the real reaction rate of styrene suspension polymerization due to slightly higher reaction temperatures. Simulation results using the experimental temperature data in a mathematical model confirmed these results.

Realizou-se o presente estudo com amostras da camada superficial (0-20 cm) de onze solos de várzea de diferentes regiões do estado de Minas Gerais, visando quantificar a adsorção de fósforo em solos de várzeas drenadas, sujeitas a ciclos alternados de umedecimento e secagem, bem como avaliar a influência de alguns atributos do solo sobre esta adsorção. Amostras da fração TFSA (2 g) foram mantidas em contato, mediante agitação por 12 horas, com soluções de CaCl2 0,01 mol L-1 (40 mL), contendo 0, 25, 50, 100 e 200 mg L-1 de P. O fósforo foi analisado posteriormente no sobrenadante para determinação da quantidade adsorvida. Após isto, descartou-se o sobrenadante para mais 12 h de agitação com solução de CaCl2 0,01 mol L-1, visando determinar a quantidade dessorvida. Os valores de adsorção encontrados foram ajustados à isoterma de Langmuir para avaliar a capacidade máxima de adsorção de fósforo (CMAF), tendo sido estimado ainda o índice tampão de P (ITP) a partir do valor do coeficiente b1 das equações de 2º grau ajustadas entre o P adsorvido e o P dessorvido nas diferentes concentrações de P adicionado. Os valores encontrados para a CMAF situaram-se entre 476 e 3.961 mg kg-1 de P no solo, tendo oito solos apresentado capacidade de adsorção de P muito alta (> 1.000 mg kg-1). Os valores de ITP situaram-se entre 4,3 e 129. A CMAF correlacionou-se positivamente com a relação Fe o/Fe d, teor de matéria orgânica e acidez potencial e negativamente com o teor de Fe d e com a saturação por bases do solo. O ITP correlacionou-se positivamente com a acidez potencial e negativamente com a saturação por bases do solo. Os resultados deste estudo revelaram que: (a) solos de várzeas drenadas podem adsorver grandes quantidades de fósforo, dos quais a maioria apresenta capacidade máxima de adsorção de fósforo enquadrada nas classes alta (500 a 1.000 mg kg-1) e muito alta (> 1.000 mg kg-1); (b) solos de várzea com maiores valores de capacidade máxima de adsorção de fósforo e índice tampão de P apresentam menor dessorção percentual desse nutriente para a solução do solo; (c) o atributo que se correlaciona mais diretamente com a capacidade máxima de adsorção e o índice tampão de fósforo dos solos de várzea estudados é a acidez potencial.

Surface-layer samples (0 to 20 cm) of eleven lowland soils from different regions of Minas Gerais, Brazil, were used to quantify phosphorus adsorption in soils of drained lowland areas, originally under alternate wetting and drying cycles, as well as to verify the influence of some soil attributes on this adsorption. Air-dried samples (2 g) of the soil fraction smaller than 2 mm were shaken during 12 hours, with 40 mL of 0.01 mol L-1 CaCl2 solutions containing 0, 25, 50, 100, and 200 mg L-1 of P. Phosphorus was quantified in the supernatant in order to determine phosphorus adsorption. A new period of 12-hour shaking with 0.01 mol L-1 CaCl2 was performed to determine P desorption. The adsorption values were adjusted to the Langmuir isotherm to estimate the maximum phosphorus adsorption capacity (MPAC). The phosphorus buffer index (PBI) was estimated by using the b1 coefficient of the 2nd degree equations adjusted between adsorbed and desorbed P at different concentrations of added P. The observed values for MPAC ranged from 476 to 3,961 mg kg-1 of P soil, and PBI ranged from 4.3 to 129. Eight soils presented very high (> 1.000 mg kg-1) phosphorus adsorption capacity. The values of MPAC were directly correlated with the Fe o/Fe d ratio, soil organic matter, and potential acidity and inversely correlated with Fe d and base saturation. The values of PBI correlated positively with potential acidity and negatively with base saturation. This study showed that: (a) soils of drained lowland areas might exhibit a great phosphorus adsorption capacity, with most of the soils from this experiment presenting a high (500 a 1.000 mg kg-1) and very high (> 1.000 mg kg-1) value of phosphorus maximum adsorption capacity; (b) lowland soils that present high phosphorus maximum adsorption capacity and phosphorus buffer index desorb less P (on a fractional basis) to soil solution; (c) potential soil acidity is the attribute that best correlates with phosphorus maximum adsorption capacity and phosphorus buffer index in the studied lowland soils.