Formulação de novos combustíveis base diesel: avaliação de desempenho e emissões

The industry, over the years, has been working to improve the efficiency of diesel engines. More recently, it was observed the need to reduce pollutant emissions to conform to the stringent environmental regulations. This has attached a great interest to develop researches in order to replace the petroleum-based fuels by several types of less polluting fuels, such as blends of diesel oil with vegetable oil esters and diesel fuel with vegetable oils and alcohol, emulsions, and also microemulsions. The main objective of this work was the development of microemulsion systems using nonionic surfactants that belong to the Nonylphenols ethoxylated group and Lauric ethoxylated alcohol group, ethanol/diesel blends, and diesel/biodiesel blends for use in diesel engines. First, in order to select the microemulsion systems, ternary phase diagrams of the used blends were obtained. The systems were composed by: nonionic surfactants, water as polar phase, and diesel fuel or diesel/biodiesel blends as apolar phase. The microemulsion systems and blends, which represent the studied fuels, were characterized by density, viscosity, cetane number and flash point. It was also evaluated the effect of temperature in the stability of microemulsion systems, the performance of the engine, and the emissions of carbon monoxide, nitrogen oxides, unburned hydrocarbons, and smoke for all studied blends. Tests of specific fuel consumption as a function of engine power were accomplished in a cycle diesel engine on a dynamometer bench and the emissions were evaluated using a GreenLine 8000 analyzer. The obtained results showed a slight increase in fuel consumption when microemulsion systems and diesel/biodiesel blends were burned, but it was observed a reduction in the emission of nitrogen oxides, unburned hydrocarbons, smoke index and f sulfur oxides

Craqueamento termocatalítico de óleo de girassol na presença da peneira molecular SAPO-5

The catalytic cracking of triglycerides presents itself as a possible alternative to the production of biofuels with low emission of pollutants. In this work were synthesized the SAPO-5, the catalysts for the cracking reaction of soybean oil is presented. The solids were powder X-ray diffraction (XRD), thermogravimetric analysis (TG/DTG) and infrared spectroscopy (FTIR). The analyses indicated that the synthesis method has employed to obtain materials with high surface area and high acid. The soybean oil thermal and thermal catalytic cracking, realized from the room temperature to 450 ºC in a simple distillation system, has allowed obtaining two liquid fractions, each consisting of two phases, one aqueous and another organic, organic liquid (OL). The OL obtained from first fractions has shown high acid index, even in the thermal catalytic process. The products obtained in the cracking of soybean oil were analyzed by distillation, acid number, infra-red spectroscopy, density, viscosity, carbon residue, cetane number determination and characterization. The analysis of the products obtained in the presence and in the absence of the SAPO-5 permitted to conclude that all the solids tested presented catalytic activity in the deoxygenation of final products only at the second step of the cracking process

Avaliação da aplicabilidade de correlações matemáticas e redes neurais na predição de parâmetros de especificação do diesel

Diesel fuel is one of leading petroleum products marketed in Brazil, and has its quality monitored by specialized laboratories linked to the National Agency of Petroleum, Natural Gas and Biofuels - ANP. The main trial evaluating physicochemical properties of diesel are listed in the resolutions ANP Nº 65 of December 9th, 2011 and Nº 45 of December 20th, 2012 that determine the specification limits for each parameter and methodologies of analysis that should be adopted. However the methods used although quite consolidated, require dedicated equipment with high cost of acquisition and maintenance, as well as technical expertise for completion of these trials. Studies for development of more rapid alternative methods and lower cost have been the focus of many researchers. In this same perspective, this work conducted an assessment of the applicability of existing specialized literature on mathematical equations and artificial neural networks (ANN) for the determination of parameters of specification diesel fuel. 162 samples of diesel with a maximum sulfur content of 50, 500 and 1800 ppm, which were analyzed in a specialized laboratory using ASTM methods recommended by the ANP, with a total of 810 trials were used for this study. Experimental results atmospheric distillation (ASTM D86), and density (ASTM D4052) of diesel samples were used as basic input variables to the equations evaluated. The RNAs were applied to predict the flash point, cetane number and sulfur content (S50, S500, S1800), in which were tested network architectures feed-forward backpropagation and generalized regression varying the parameters of the matrix input in order to determine the set of variables and the best type of network for the prediction of variables of interest. The results obtained by the equations and RNAs were compared with experimental results using the nonparametric Wilcoxon test and Student's t test, at a significance level of 5%, as well as the coefficient of determination and percentage error, an error which was obtained 27, 61% for the flash point using a specific equation. The cetane number was obtained by three equations, and both showed good correlation coefficients, especially equation based on aniline point, with the lowest error of 0,816%. ANNs for predicting the flash point and the index cetane showed quite superior results to those observed with the mathematical equations, respectively, with errors of 2,55% and 0,23%. Among the samples with different sulfur contents, the RNAs were better able to predict the S1800 with error of 1,557%. Generally, networks of the type feedforward proved superior to generalized regression.