67 resultados para Radial Diffuser


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In the present work are presented results from numerical simulations performed with the ANSYS-CFX (R) code. We have studied a radial diffuser flow case, which is the main academic problem used to study the flow behavior on flat plate valves. The radial flow inside the diffuser has important behavior such as the turbulence decay downstream and recirculation regions inside the valve flow channel due to boundary layer detachment. These flow structures are present in compressor reed valve configurations, influencing to a greater extent the compressor efficiency. The main target of the present paper was finding the simulation set-up (computational domain, boundary conditions and turbulence model) that better fits with experimental data published by Tabatabai and Pollard. The local flow turbulence and velocity profiles were investigated using four different turbulence models, two different boundary conditions set-up, two different computational domains and three different flow conditions (Re-in - Reynolds number at the diffuser inlet). We used the Reynolds stress (BSL); the k-epsilon; the RNG k-epsilon; and the shear stress transport (SST) k-omega turbulence models. The performed analysis and comparison of the computational results with experimental data show that the choice of the turbulence model, as well as the choice of the other computational conditions, plays an important role in the results physical quality and accuracy. (c) 2007 Elsevier B.V. All rights reserved.

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

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Pós-graduação em Engenharia Mecânica - FEIS

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The main goal of the present work is to verify the applicability of the Immersed Boundary Method together with the Virtual Physical Model to solve the flow through automatic valves of hermetic compressors. The valve was simplified to a two-dimensional radial diffuser, with diameter ratio of D/d = 1.5, and simulated for a one cycle of opening and closing process with a imposed velocity of 3.0 cm/s for the reed, dimensionless gap between disks in the range of 0.07 < s/d < 0.10, and inlet Reynolds number equal to 1500. The good results obtained showed that the methodology has great potential as project tool for this type of valve systems. © The Authors, 2011.

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Pós-graduação em Engenharia Mecânica - FEIS

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Pós-graduação em Engenharia Mecânica - FEIS

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

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Pós-graduação em Engenharia Mecânica - FEIS

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Spiking neural networks - networks that encode information in the timing of spikes - are arising as a new approach in the artificial neural networks paradigm, emergent from cognitive science. One of these new models is the pulsed neural network with radial basis function, a network able to store information in the axonal propagation delay of neurons. Learning algorithms have been proposed to this model looking for mapping input pulses into output pulses. Recently, a new method was proposed to encode constant data into a temporal sequence of spikes, stimulating deeper studies in order to establish abilities and frontiers of this new approach. However, a well known problem of this kind of network is the high number of free parameters - more that 15 - to be properly configured or tuned in order to allow network convergence. This work presents for the first time a new learning function for this network training that allow the automatic configuration of one of the key network parameters: the synaptic weight decreasing factor.

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The study aimed to evaluate the radial profile and the uniformity of water distribution of sprinkler manufactured by the company NaanDanJain, model 427 1/2 '' M and nozzle with 2.8 mm of internal diameter, operating at pressures of 150, 200, 300 and 400 kPa and five positions of the deflector (0, 20, 50, 80 and 100%). For the determination of the parameters evaluated, the grid method was used and with the help of computer application CATCH 3D, overlapping layers of water depths was calculated with ten spacing. The results show that the deflector adjustment influences the radius of wetness and the distribution profile while the uniformity of water application showed as an important mechanism, since it permits different behavior for the sprinkler, ensuring wide track of utilization of the equipment.

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The present study evaluated the origin, distribution and ramification of the radial nerves were studied in 30 adult domestic cats. The sample included 15 females and 15 males of unknown breed. The specimens were fixed in 10% formaldehyde solution. The radial nerve showed many fascicles from the origin also your ramification in superficial and deep branches. Radial nerves were observed to originate, in 16 cases (26.7%), from the ventral branch of the sixth cervical spinal nerve; in 60 cases (100%), from the ventral branch of the seventh cervical spinal nerve; in 60 cases (100%), from the ventral branch of the eight cervical nerve and in 60 cases (100%), from the ventral branch of the first thoracic nerve. The radial nerves branched out, in all of the animals studied (100.0%), to the tensor fasciae antebrachii, long, accessory, medial and lateral heads of the triceps branchii and anconeus muscles. The radial nerve emits of 14 to 25 nervous branches in this region. However, the branch of the sixth cervical spinal nerve and the nervous fascicles reveal significant differences (p <= 0.05), respectively, in or with relation to sex of the animals and the studied region.

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The study of function approximation is motivated by the human limitation and inability to register and manipulate with exact precision the behavior variations of the physical nature of a phenomenon. These variations are referred to as signals or signal functions. Many real world problem can be formulated as function approximation problems and from the viewpoint of artificial neural networks these can be seen as the problem of searching for a mapping that establishes a relationship from an input space to an output space through a process of network learning. Several paradigms of artificial neural networks (ANN) exist. Here we will be investigated a comparative of the ANN study of RBF with radial Polynomial Power of Sigmoids (PPS) in function approximation problems. Radial PPS are functions generated by linear combination of powers of sigmoids functions. The main objective of this paper is to show the advantages of the use of the radial PPS functions in relationship traditional RBF, through adaptive training and ridge regression techniques.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)