129 resultados para Power Sensitivity Model


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Laminar axial flow of a pseudoplastic fluid food (soursop, juice) in annular ducts has been experimentally investigated. In the first part of the manuscript, the rheological behavior of soursop juice, being essential for the annular flow analysis, was completely determined from 9.3 to 49.4 degrees Brix and temperatures from 0.4 degrees C to 68.8 degrees C, using a rotational rheometer equipped with coaxial cylinders. In order to test the adequacy of the rheology results, pressure loss data in the laminar pipe flow were collected and then experimental and theoretical friction factors were compared, showing excellent agreement, which indicated the reliability of the Power-Law model for describing the soursop juices. In the second part, pressure loss in annular regions was measured and used to estimate friction factors, which were then compared to those resulted from analytical and semi-analytical equations. The principal contributions of this article are to provide a review on the determination of friction factors-Reynolds number of pseudoplastic fluids in annuli, and also supply extensive new experimental data on the rheological properties and pressure loss of an important shear-thinning fluid food, which is of particular interest for the food engineering process design. (c) 2006 Elsevier Ltd. All rights reserved.

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This research studied the effects of the independent variables whey protein concentrate - WPC (3.0; 3.5; 4.0%), skimmed milk powder - SMP (4.0; 5.0; 6.0%), and isolated soy protein - IPS (1.5; 2.0; 2.5%) on the rheological and sensorial characteristics of functional dairy beverages. In all tests 7% of sucrose was added to the ingredients. The rheological parameters were obtained in duplicate at the temperature of 10° C using a cone and plate rheometer, and fitted to the Power law model. The samples revealed a non-Newtonian fluid behavior both in the upward and downward curves, typical of a tixotropic fluid. The dairy beverages were submitted to a sensory analysis by a group of fifty untrained tasters who used a hedonic scale of nine points, the extremes being 1 - disliked extremely and 9 - liked extremely, in order to evaluate the following parameters: general acceptability; appearance and color; consistency; taste and aroma. The dairy beverage produced with 3% WPC, 6% SMP and 1.5% IPS, (treatment 3), was the one that obtained the best average score for those attributes and was preferred by the tasters. The variables SMP and IPS and the interaction between WPC and SMP presented a positive effect on the sensory consistency attributes: the higher amount of those ingredients in the formula the more the tasters liked the consistency.

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One of the critical problems in implementing an intelligent grinding process is the automatic detection of workpiece surface burn. This work uses fuzzy logic as a tool to classify and predict burn levels in the grinding process. Based on acoustic emission signals, cutting power, and the mean-value deviance (MVD), linguistic rules were established for the various burn situations (slight, intermediate, severe) by applying fuzzy logic using the Matlab Toolbox. Three practical fuzzy system models were developed. The first model with two inputs resulted only in a simple analysis process. The second and third models have an additional MVD statistic input, associating information and precision. These two models differ from each other in terms of the rule base developed. The three developed models presented valid responses, proving effective, accurate, reliable and easy to use for the determination of ground workpiece burn. In this analysis, fuzzy logic translates the operator's human experience associated with powerful computational methods.

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The rheological behavior of poly(ethylene glycol) of 1500 g·mol -1(PEG1500) aqueous solutions with various polymer concentrations (w = 0.05, 0.10, 0.15, 0.20 and 0.25) was studied at different temperatures (T = 283.15, 288.15, 293.15, 298.15 and 303.15) K. The analyses were carried out considering shear rates ranging from (20 to 350) s-1, using a cone-and-plate rheometer under controlled stress and temperature. Classical rheological models (Newton, Bingham, Power Law, Casson, and Herschel-Bulkley) were tested. The Power Law model was shown suitable to mathematically represent the rheological behavior of these solutions. Well-adjusted empirical models were derived for consistency index variations in function of temperature (Arrhenius-type model; R2 > 0.96), polymer concentration (exponential model; R2 > 0.99) or the combination of both (R 2 > 0.99). Additionally, linear models were used to represent the variations of behavior index in the functions of temperature (R2 > 0.83) and concentration (R2 > 0.87). © 2013 American Chemical Society.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Ciências da Motricidade - IBRC

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Pós-graduação em Engenharia Elétrica - FEIS

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Pós-graduação em Engenharia Elétrica - FEIS

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Pós-graduação em Engenharia Elétrica - FEIS

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Pós-graduação em Engenharia e Ciência de Alimentos - IBILCE

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This study aimed to evaluate the use of a mixer to determine the rheological properties of fluids. The mixer is comprised of an agitation tank and an anchor type impeller. The tests were performed with honey and fruit juices (orange, guava and peach). The rheological characterization was performed using data from the torque and rotation speed required for the operation of fluid agitation. Tests were also made with a concentric cylinder rotational viscometer with the samples being subjected to various shear rates. The rheological parameters were obtained from the flow curves fitted to the power law model. Analyses of results showed that the mixer can be used, within its limitations, to determine rheological properties.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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This work presents a procedure for transient stability analysis and preventive control of electric power systems, which is formulated by a multilayer feedforward neural network. The neural network training is realized by using the back-propagation algorithm with fuzzy controller and adaptation of the inclination and translation parameters of the nonlinear function. These procedures provide a faster convergence and more precise results, if compared to the traditional back-propagation algorithm. The adaptation of the training rate is effectuated by using the information of the global error and global error variation. After finishing the training, the neural network is capable of estimating the security margin and the sensitivity analysis. Considering this information, it is possible to develop a method for the realization of the security correction (preventive control) for levels considered appropriate to the system, based on generation reallocation and load shedding. An application for a multimachine power system is presented to illustrate the proposed methodology. (c) 2006 Elsevier B.V. All rights reserved.

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The paper presents a method for security control of electric power systems effected by generation reallocation, determined by sensitivity analysis and optimisation. The model is developed considering the dynamic aspects of the network (transient stability). Security control methodology is developed using sensitivity analysis of the security margin in relation to the mechanical power of synchronous machines in the system. The power reallocated to each machine is determined by means of linear programming. To illustrate the proposed methodology, an example is presented which considers a multimachine system composed of 10 synchronous machines, 45 buses, and 72 transmission lines, based on the configuration of a southern Brazilian system.