Karina Gomes Angilelli

Kinetic and thermodynamic parameters of biodiesel oxidation with synthetic antioxidants: simplex centroid mixture design

Temperatures influence on biodiesel oxidation was evaluated by kinetic and thermodynamic data in biofuel from soybean oil and lard with synthetic antioxidants: butylatedhydroxyanisol (BHA), butylatedhydroxytoluene (BHT), tert-butylhydroquinone (TBHQ), and propylgallate (PG) by simplex centroid mixture design. The kinetic parameters ware obtained by Arrhenius equation and showed that addition of antioxidants in all tests increased activation energy (Ea) and that TBHQ and PG were more efficient and presented synergistic effect. BHT and BHA were the least efficient, as well as their mixtures. The thermodynamic activation parameters of the reactions, evaluated by the Eyring equation and based on the theory of the activated complex (ACT), indicated no spontaneous processes (∆G‡ > 0) with positive ∆H‡ values and positive and negative ∆S‡ values. The application of simplex centroid mixture design, using Ea as response, showed the optimised value of 174.46 kJ mol-1 for a mixture containing 33.33 and 66.67% of TBHQ and PG, respectively.

Modelagem Matemática Aplicada a Síntese do Produtos da Reação de Transesterificação a partir de Gordura Animal e Óleo Vegetal

The high availability and low cost of animal fat have promoted industrial interest as a partial substitute for soybean oil for transesterification reaction product of synthesis, to reduce costs and maximize profits. This study aimed to apply experimental design for biodiesel production from a mixture of soybean oil, poultry fat, beef tallow and pork lard in order to obtain predictive equations to model the transesterification reaction yield, cloud point, pour point and oxidative stability, with sodium hydroxide and sodium methoxide as the process variables. The presence of animal fat in the formulations is an interesting factor, because although it did not present good results when isolated, with low oxidative stability (lard) and high cloud and pour points (beef tallow), it showed good performance and can be used as a partial substitute for soybean oil. DOI: 10.5935/1984-6835.20160060

Application of self-organising maps towards segmentation of soybean samples by determination of inorganic compounds content.

BACKGROUND In this study, 20 samples of soybean, both transgenic and conventional cultivars, which were planted in two different regions, Londrina and Ponta Grossa, both located at Paraná, Brazil, were analysed. In order to verify whether the inorganic compound levels in soybeans varied with the region of planting, K, P, Ca, Mg, S, Zn, Mn, Fe, Cu and B contents were analysed by an artificial neural network self-organising map. RESULTS It was observed that with a topology 10 × 10, 8000 epochs, initial learning rate of 0.1 and initial neighbourhood ratio of 4.5, the network was able to differentiate samples according to region of origin. Among all of the variables analysed by the artificial neural network, the elements Zn, Ca and Mn were those which most contributed to the classification of the samples. CONCLUSION The results indicated that samples planted in these two regions differ in their mineral content; however, conventional and transgenic samples grown in the same region show no difference in mineral contents in the grain.

Mathematical modeling of multicomponent NaCl and KCl diffusion process during the salting of pre-cooked champignon mushrooms

Wet salting is an old preservation method however the NaCl has been frequently associated to high blood pressure issues. The KCl has been used as partial replacement without affecting the acceptability of the final product. In this study, the simultaneous diffusion of NaCl and KCl in champignon mushrooms in static brine and brine under agitation was modeled based on the generalization of Ficks second diffusion law and simulated using the finite element method. Main and crossed diffusion coefficients, as well as the Biot number, were determined using the super modified simplex optimization method by means of percentage error minimization. Deviations between the simulated and experimental data were 5.78% for NaCl and 4.78% for KCl in static brine and 4.95% for NaCl and 4.35% for KCl in brine with agitation and, the main diffusion coefficients 2.692 × 10-10 m2s-1 for sodium and 2.953 × 10-10 m2s-1 for potassium were obtained.

Application Self-organizing Map Type in a Study of the Profile of Gasoline C Commercialized in the Eastern and Northern Parana Regions

Artificial neural networks self-organizing map type (SOM) was used to classify samples of automotive gasoline C marketed in the eastern and northern regions of the state of Parana, Brazil. The input order of parameters in the network were the values of temperature of the first drop, the 10, 50 and 90% distilled bulk, the final boiling point, density, residue content and alcohol content. A network with a topology of 25x25 and 5000 training epochs was used. The weight maps of input parameters for the trained network identified that the most important parameters for classifying samples were the temperature of the first drop and the temperature of the 10% and 50% of the distilled fuel. DOI: http://dx.doi.org/10.17807/orbital.v7i2.732