67 resultados para Radial diffuser


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Extensive field testes were conducted using the UCD single wheel tester employing three large radial ply tractor tires in two different soils, four different soil conditions, two axle load levels, and three levels of tire inflation pressures in order to quantify the benefits of using low/correct inflation pressures. During these tests slip, net traction, gross traction, and dynamic axle load were recorded. Furthermore, soil moisture content, cone index, and dry bulk density data were obtained at test locations. The results of the analysis showed a significant increase in net traction and traction efficiency when low/correct inflation was used. Benefits of using low/correct pressure was higher in tilled soil conditions.

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Unsteady flow of oil and refrigerant gas through radial clearance in rolling piston compressors has been modeled as a heterogeneous mixture, where the properties are determined from the species conservation transport equation coupled with momentum and energy equations. Time variations of pressure, tangential velocity of the rolling piston and radial clearance due to pump setting have been included in the mixture flow model. Those variables have been obtained by modeling the compression process, rolling piston dynamics and by using geometric characteristics of the pump, respectively. An important conclusion concerning this work is the large variation of refrigerant concentration in the oil-filled radial clearance during the compression cycle. That is particularly true for large values of mass flow rates, and for those cases the flow mixture cannot be considered as having uniform concentration. In presence of low mass flow rates homogeneous flow prevail and the mixture tend to have a uniform concentration. In general, it was observed that for calculating the refrigerant mass flow rate using the difference in refrigerant concentration between compression and suction chambers, a time average value for the gas concentration should be used at the clearance inlet.

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This paper describes a analog implementation of radial basis neural networks (RBNN) in BiCMOS technology. The RBNN uses a gaussian function obtained through the characteristic of the bipolar differential pair. The gaussian parameters (gain, center and width) is changed with programmable current source. Results obtained with PSPICE software is showed.

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The main objective involved with this paper consists of presenting the results obtained from the application of artificial neural networks and statistical tools in the automatic identification and classification process of faults in electric power distribution systems. The developed techniques to treat the proposed problem have used, in an integrated way, several approaches that can contribute to the successful detection process of faults, aiming that it is carried out in a reliable and safe way. The compilations of the results obtained from practical experiments accomplished in a pilot radial distribution feeder have demonstrated that the developed techniques provide accurate results, identifying and classifying efficiently the several occurrences of faults observed in the feeder.

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The capacitor placement problem for radial distribution networks aims to determine capacitor types, sizes, locations and control scheme. This is a combinatorial problem that can be formulated as a mixed integer nonlinear program. The paper presents an algorithm inspired in artificial immune systems and developed for this specific problem. A good performance was obtained through experimental tests applied to known systems. © 2006 IEEE.

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An analog circuit that implements a radial basis function network is presented. The proposed circuit allows the adjustment of all shape parameters of the radial functions, i.e., amplitude, center and width. The implemented network was applied to the linearization of a nonlinear circuit, a voltage controlled oscillator (VCO). This application can be classified as an open-loop control in which the network plays the role of the controller. Experimental results have proved the linearization capability of the proposed circuit. Its performance can be improved by using a network with more basis functions. Copyright 2007 ACM.

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A RBFN implemented with quantized parameters is proposed and the relative or limited approximation property is presented. Simulation results for sinusoidal function approximation with various quantization levels are shown. The results indicate that the network presents good approximation capability even with severe quantization. The parameter quantization decreases the memory size and circuit complexity required to store the network parameters leading to compact mixed-signal circuits proper for low-power applications. ©2008 IEEE.

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In this paper, we propose new circuits for the implementation of Radial Basis Functions (RBF). These RBFs are obtained by the subtraction of two differential pair output currents in a folded cascode configuration. We also propose a multidimensional version based on the unidimensional circuits. SPICE simulation and experimental results indicate good functionality. These circuits are intended to be applied in the implementation of radial basis function networks. Possible applications of these networks include transducer signal conditioning and processing in onboard telemetry systems for aircraft and spacecraft vehicles. © 2010 IEEE.

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This paper presents a mixed-integer linear programming approach to solving the optimal fixed/switched capacitors allocation (OCA) problem in radial distribution systems with distributed generation. The use of a mixed-integer linear formulation guarantees convergence to optimality using existing optimization software. The results of one test system and one real distribution system are presented in order to show the accuracy as well as the efficiency of the proposed solution technique. © 2011 IEEE.

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This paper presents a mixed-integer linear programming model to solve the conductor size selection and reconductoring problem in radial distribution systems. In the proposed model, the steady-state operation of the radial distribution system is modeled through linear expressions. The use of a mixed-integer linear model guarantees convergence to optimality using existing optimization software. The proposed model and a heuristic are used to obtain the Pareto front of the conductor size selection and reconductoring problem considering two different objective functions. The results of one test system and two real distribution systems are presented in order to show the accuracy as well as the efficiency of the proposed solution technique. © 1969-2012 IEEE.

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The problem of reconfiguration of distribution systems considering the presence of distributed generation is modeled as a mixed-integer linear programming (MILP) problem in this paper. The demands of the electric distribution system are modeled through linear approximations in terms of real and imaginary parts of the voltage, taking into account typical operating conditions of the electric distribution system. The use of an MILP formulation has the following benefits: (a) a robust mathematical model that is equivalent to the mixed-integer non-linear programming model; (b) an efficient computational behavior with exiting MILP solvers; and (c) guarantees convergence to optimality using classical optimization techniques. Results from one test system and two real systems show the excellent performance of the proposed methodology compared with conventional methods. © 2012 Published by Elsevier B.V. All rights reserved.

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This paper presents a mixed-integer linear programming model to solve the problem of allocating voltage regulators and fixed or switched capacitors (VRCs) in radial distribution systems. The use of a mixed-integer linear model guarantees convergence to optimality using existing optimization software. In the proposed model, the steady-state operation of the radial distribution system is modeled through linear expressions. The results of one test system and one real distribution system are presented in order to show the accuracy as well as the efficiency of the proposed solution technique. An heuristic to obtain the Pareto front for the multiobjective VRCs allocation problem is also presented. © 2012 Elsevier Ltd. All rights reserved.

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This paper presents a mixed-integer linear programming approach to solving the problem of optimal type, size and allocation of distributed generators (DGs) in radial distribution systems. In the proposed formulation, (a) the steady-state operation of the radial distribution system, considering different load levels, is modeled through linear expressions; (b) different types of DGs are represented by their capability curves; (c) the short-circuit current capacity of the circuits is modeled through linear expressions; and (d) different topologies of the radial distribution system are considered. The objective function minimizes the annualized investment and operation costs. The use of a mixed-integer linear formulation guarantees convergence to optimality using existing optimization software. The results of one test system are presented in order to show the accuracy as well as the efficiency of the proposed solution technique.© 2012 Elsevier B.V. All rights reserved.

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In this study, a novel approach for the optimal location and contract pricing of distributed generation (DG) is presented. Such an approach is designed for a market environment in which the distribution company (DisCo) can buy energy either from the wholesale energy market or from the DG units within its network. The location and contract pricing of DG is determined by the interaction between the DisCo and the owner of the distributed generators. The DisCo intends to minimise the payments incurred in meeting the expected demand, whereas the owner of the DG intends to maximise the profits obtained from the energy sold to the DisCo. This two-agent relationship is modelled in a bilevel scheme. The upper-level optimisation is for determining the allocation and contract prices of the DG units, whereas the lower-level optimisation is for modelling the reaction of the DisCo. The bilevel programming problem is turned into an equivalent single-level mixed-integer linear optimisation problem using duality properties, which is then solved using commercially available software. Results show the robustness and efficiency of the proposed model compared with other existing models. As regards to contract pricing, the proposed approach allowed to find better solutions than those reported in previous works. © The Institution of Engineering and Technology 2013.

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Pós-graduação em Engenharia Elétrica - FEIS