Orientador: Ronei Jesus Poppi / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Química / Made available in DSpace on 2018-08-19T18:06:58Z (GMT). No. of bitstreams: 1 Alves_JulioCesarLaurentino_D.pdf: 19282542 bytes, checksum: 78d1bf16d9d133c488adb4bedf593b06 (MD5) Previous issue date: 2012 / Resumo: Modelos lineares de regressão e classificação por vezes proporcionam um desempenho insatisfatório no tratamento de dados de espectroscopia no infravermelho próximo de produtos derivados de petróleo. A máquina de vetores de suporte (SVM), baseada na teoria do aprendizado estatístico, possibilita o desenvolvimento de modelos de regressão e classificação não lineares que podem proporcionar uma melhor modelagem dos referidos dados, porém ainda é pouco explorada para resolução de problemas em química analítica. Nesse trabalho demonstra-se a utilização do SVM para o tratamento de dados de espectroscopia na região do infravermelho próximo de combustíveis e lubrificantes. O SVM foi utilizado para a solução de problemas de regressão e classificação e seus resultados comparados com os algoritmos de referência PLS e SIMCA. Foram abordados os seguintes problemas analíticos relacionados a controle de processos e controle de qualidade: (i) determinação de parâmetros de qualidade do óleo diesel utilizados para otimização do processo de mistura em linha na produção desse combustível; (ii) determinação de parâmetros de qualidade do óleo diesel que é carga do processo de HDT, para controle e otimização das condições de processo dessa unidade; (iii) determinação do teor de biodiesel na mistura com o óleo diesel; (iv) classificação das diferentes correntes que compõem o pool de óleo diesel na refinaria, permitindo a identificação de adulterações e controle de qualidade; (v) classificação de lubrificantes quanto ao teor de óleo naftênico e/ou presença de óleo vegetal. Demonstram-se o melhor desempenho do SVM em relação aos modelos desenvolvidos com os métodos quimiométricos de referência (métodos lineares). O desenvolvimento de métodos analíticos rápidos e de baixo custo para solução de problemas em controle de processos e controle de qualidade, com a utilização de modelos de regressão e classificação mais exatos, proporcionam o monitoramento da qualidade de forma mais eficaz e eficiente, contribuindo para o aumento das rentabilidades nas atividades econômicas de produção e comercialização dos derivados do petróleo estudados / Abstract: Linear regression and classification models can produce a poor performance in processing near-infrared spectroscopy data of petroleum products. Support vectors machine (SVM), based on statistical learning theory, provides the development of models for nonlinear regression and classification that can result in better modeling of these data but it is still little explored for solving problems in analytical chemistry. This work demonstrates the use of the SVM for treatment of near-infrared spectroscopy data of fuels and lubricants. The SVM was used to solve regression and classification problems and its results were compared with the reference algorithms PLS and SIMCA. The following analytical problems related to process control and quality control were studied: (i) quality parameters determination of diesel oil, used for optimization of in line blending process; (ii) quality parameters determination of diesel oil which is feed-stock of HDT unit for optimization of process control; (iii) quantification of biodiesel blended with diesel oil; (iv) classification of different streams that make up the pool of diesel oil in the refinery, enabling identification of adulteration and quality control; (v) classification of lubricants based on the content of naphthenic oil and/or the presence of vegetable oil. It is shown the best performance of the SVM compared to models developed with the reference algorithms. The development of fast and low cost analytical methods used in process control and quality control, with the use of more accurate regression and classification models, allows monitoring quality parameters in more effectiveness and efficient manner, making possible an increase in profitability of economic activities of production and business of petroleum derivatives studied / Doutorado / Quimica Analitica / Doutor em Ciências

<p>  </p> <p>Part I studies the lubricant sprays and droplets in a rotary compressor. Air conditioning (AC) systems are now widely used in residential and commercial environments, while the compressor is the most important element in the AC system, and rotary compressors are often used in split AC appliances, whose number is estimated to reach 3.7 billion in 2050. In a rotary compressor, the lubricant oil atomizes into small droplets due to the differential pressure in and out of the cylinder. Part of the lubricant oil droplets carried by the refrigerant vapor will ultimately exhaust from the compressor through the discharge pipe. The ratio of the discharged oil volume to the total oil volume is characterized as the Oil Discharge Ratio (ODR). High ODR will reduce the reliability of the compressor and deteriorate the heat transfer of the condenser and the evaporator, resulting in decreased efficiency. Thus, controlling the ODR is a key issue for the design of the rotary compressor.</p> <p>In Part I, rotary compressors were modified to provide optical access into its internal space, i.e., the lower cavity (refers to the space between the cylinder and the motor), above the rotor/stator, and at the discharge tube level. The modified rotary compressors’ operation was supported by a test rig which provided a wide range of operating conditions, e.g., pressure and frequency. Thus, in-situ optical measurements, e.g., shadowgraph and holograph, can be performed to visualize the lubricant sprays and droplets in the rotary compressor. An image processing routine containing the Canny operator and Convolutional Neural-Network was developed to identify droplets from high-resolution shadowgraph images, while Particle Image Velocimetry (PIV) and Optical Flow Velocimetry (OFV) were applied to calculate the spray and droplet’s velocities with time-resolved shadowgraph images. Parallel Four-Step Phase Shifting Holograph (PFSPSH) located the droplets’ positions in a three-dimensional volume under the specific operating condition.</p> <p>Both primary and secondary atomization were observed in the rotary compressor, while primary atomization is the major source of droplet production. The droplet size distributions versus the frequency, vertical direction, radial direction, and pressure are obtained. It is observed that the droplet characteristic mean diameters increase with the frequency and pressure. They also become larger in the outer region above the rotor/stator and keep constant in the radial direction at the discharge tube level. The penetration velocity of the lubricant spray is calculated in the lower cavity. An outward shift of the jet core combined with an outward velocity component was observed. Additionally, horizontal swirling velocity above the rotor/stator and at the discharge tube level and the vertical recirculation velocity above the rotor/stator are characterized. The volume fraction of droplets was also characterized under the specific operating condition. The results provide detailed experimental data to set up the boundary conditions used in CFD. They also show that the droplets in the upper cavity are mostly from the discharge process of the cylinder in the lower cavity. The results support a droplet pathway model in the rotary compressor, which can guide the optimization of future rotary compressors.</p> <p>Evaporation is commonly seen in hydrology, agriculture, combustion, refrigeration, welding, etc. And it always accompanies heat and mass transfer at the liquid-gas interface and is affected by the substance’s properties, the environment’s pressure, temperature, convection, and so on. PFSPSH in Part I aims to retrieve the phase information for holograph reconstruction. Part II further explores the application of the PFSPSH technology in Part I to observe the evaporation process of acetone, where the phase disturbance caused by the vapor is used to reconstruct the vapor concentration in space. The method is called Parallel Four-Step Phase Shifting Interferometer (PFSPSI). The first case studies the evaporation process of the acetone contained in a liquid pool with uniform air flow in a low-speed wind tunnel. The mole fractions of the acetone vapor near the liquid-air interface with different air speeds are characterized. The second case studies the evaporation process of acetone droplets levitated by an ultrasound levitator. The mole fraction of the acetone vapor near the liquid-air interface is characterized by assuming an axisymmetric field and using the analytical solution of the inverse Abel transform. The asymmetric pattern of the acetone vapor field is observed, which is considered due to the drastic sound pressure change at the stand wave location produced by the ultrasound levitator. The mass transfer of the evaporation process by the vapor’s mole fraction is calculated and compared with the mass transfer calculated by the droplet size change. It is observed that the mass transfer by the vapor’s mole fraction is generally smaller than the mass transfer calculated by the droplet size change, which can be explained by the convection process induced by the acoustic streaming.</p>