158 resultados para hole expansion


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In this work it was performed energetic and exergetic analyses of three thermal plants to assessment a cogeneration system in expansion of a sugar-alcohol factory. The initial configuration considered is constituted by a low pressure steam generator, single stage steam turbines for electricity generation and crusher, shredder and mills with mechanical driving. In the intermediary configuration, the low pressure steam generator was substituted by another which generates steam at higher pressure and higher temperature, the steam turbines for electricity generation were substituted by a multiple stages extraction-condensation turbine and the other steam turbines were maintained. The final configuration consists in the substitution of these last turbines by electrical motors. Thermodynamic analyses were performed to evaluate the equipment and the overall plants efficiencies to permit a comparison among the plants. Besides of this, some important parameters of the sugar-alcohol factories were calculated.

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Statement of problem. There are few studies on titanium casting shrinkage, and phosphate-bonded investments for titanium casting have not produced appropriate marginal fit.Purpose. The purpose of this study was to determine the thermal shrinkage of titanium and the setting and thermal expansion of 3 phosphate-bonded investments.Material and methods. The thermal shrinkage between the melting temperature and room temperature was calculated using a titanium thermal expansion coefficient. The thermal and setting expansion were measured for 3 phosphate bonded investments: Rematitan Plus (RP) specific for titanium, Rema Exakt (RE), and Castorit Super C (CA), using different special liquid concentrations (100%, 75%, and 50%). Setting expansion was measured for cylindrical specimens 50 mm long x 8 mm in diameter with a transducer. The heating and cooling curves were obtained with a dilatometer (DIL 402 PC). The total expansion curve was drawn using software, and temperatures to obtain expansion equivalent to titanium casting shrinkage were determined (n=5). In addition, the total expansion of the control group (RP at 430 degrees C) was measured, as well as the temperatures at which the other groups achieved equivalent total expansion (n=5). Data were analyzed by 1-way ANOVA and the Tukey HSD test (alpha=.05).Results. Titanium casting shrinkage was estimated as 1.55%. RP did not achieve this expansion. RE achieved expansion of 1.55% only with a special liquid concentration of 100% at 594 degrees C. CA with all special liquid concentrations attained this expansion (351 degrees C to 572 degrees C). Total expansion of the control group was 0.86%, and the other groups reached that expansion within the range of 70 degrees C to 360 degrees C.Conclusions. Only RE and CA demonstrated sufficient expansion to compensate for titanium casting shrinkage. All groups reached total expansion equivalent to that of the control group at significantly lower temperatures.

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We study the 1/N expansion of field theories in the stochastic quantization method of Parisi and Wu using the supersymmetric functional approach. This formulation provides a systematic procedure to implement the 1/N expansion which resembles the ones used in the equilibrium. The 1/N perturbation theory for the nonlinear sigma-model in two dimensions is worked out as an example.

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We have investigated and extensively tested three families of non-convex optimization approaches for solving the transmission network expansion planning problem: simulated annealing (SA), genetic algorithms (GA), and tabu search algorithms (TS). The paper compares the main features of the three approaches and presents an integrated view of these methodologies. A hybrid approach is then proposed which presents performances which are far better than the ones obtained with any of these approaches individually. Results obtained in tests performed with large scale real-life networks are summarized.

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The simulated annealing optimization technique has been successfully applied to a number of electrical engineering problems, including transmission system expansion planning. The method is general in the sense that it does not assume any particular property of the problem being solved, such as linearity or convexity. Moreover, it has the ability to provide solutions arbitrarily close to an optimum (i.e. it is asymptotically convergent) as the cooling process slows down. The drawback of the approach is the computational burden: finding optimal solutions may be extremely expensive in some cases. This paper presents a Parallel Simulated Annealing, PSA, algorithm for solving the long term transmission network expansion planning problem. A strategy that does not affect the basic convergence properties of the Sequential Simulated Annealing algorithm have been implementeded and tested. The paper investigates the conditions under which the parallel algorithm is most efficient. The parallel implementations have been tested on three example networks: a small 6-bus network, and two complex real-life networks. Excellent results are reported in the test section of the paper: in addition to reductions in computing times, the Parallel Simulated Annealing algorithm proposed in the paper has shown significant improvements in solution quality for the largest of the test networks.

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We show how the zero-temperature result for the heat-kernel asymptotic expansion can be generalized to the finite-temperature one. We observe that this general result depends on the interesting ratio square-root tau/beta, where tau is the regularization parameter and beta = 1/T, so that the zero-temperature limit beta --> infinity corresponds to the cutoff limit tau --> 0. As an example, we discuss some aspects of the axial model at finite temperature.

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The usefulness of the application of heuristic algorithms in the transportation model, first proposed by Garver, is analysed in relation to planning for the expansion of transmission systems. The formulation of the mathematical model and the solution techniques proposed in the specialised literature are analysed in detail. Starting with the constructive heuristic algorithm proposed by Garver, an extension is made to the problem of multistage planning for transmission systems. The quality of the solutions found by heuristic algorithms for the transportation model is analysed, as are applications in problems of planning transmission systems.

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The magnetic order resulting from the indirect exchange in the metallic phase of a (Ga,Mn)As/GaAs double layer structure is studied via Monte Carlo simulation. The polarization of the hole gas is taken into account, establishing a self-consistency between the magnetic order and the electronic structure. The Curie-Weiss temperatures calculated for these low-dimensional systems are in the range of 50-80 K, and the dependence of the transition temperature with the GaAs separation layer is established. (C) 2003 Published by Elsevier B.V.

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The paper presents a constructive heuristic algorithm (CHA) for solving directly the long-term transmission-network-expansion-planning (LTTNEP) problem using the DC model. The LTTNEP is a very complex mixed-integer nonlinear-programming problem and presents a combinatorial growth in the search space. The CHA is used to find a solution for the LTTNEP problem of good quality. A sensitivity index is used in each step of the CHA to add circuits to the system. This sensitivity index is obtained by solving the relaxed problem of LTTNEP, i.e. considering the number of circuits to be added as a continuous variable. The relaxed problem is a large and complex nonlinear-programming problem and was solved through the interior-point method (IPM). Tests were performed using Garver's system, the modified IEEE 24-Bus system and the Southern Brazilian reduced system. The results presented show the good performance of IPM inside the CHA.

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The data of four networks that can be used in carrying out comparative studies with methods for transmission network expansion planning are given. These networks are of various types and different levels of complexity. The main mathematical formulations used in transmission expansion studies-transportation models, hybrid models, DC power flow models, and disjunctive models are also summarised and compared. The main algorithm families are reviewed-both analytical, combinatorial and heuristic approaches. Optimal solutions are not yet known for some of the four networks when more accurate models (e.g. The DC model) are used to represent the power flow equations-the state of the art with regard to this is also summarised. This should serve as a challenge to authors searching for new, more efficient methods.

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A branch and bound (B& B) algorithm using the DC model, to solve the power system transmission expansion planning by incorporating the electrical losses in network modelling problem is presented. This is a mixed integer nonlinear programming (MINLP) problem, and in this approach, the so-called fathoming tests in the B&B algorithm were redefined and a nonlinear programming (NLP) problem is solved in each node of the B& B tree, using an interior-point method. Pseudocosts were used to manage the development of the B&B tree and to decrease its size and the processing time. There is no guarantee of convergence towards global optimisation for the MINLP problem. However, preliminary tests show that the algorithm easily converges towards the best-known solutions or to the optimal solutions for all the tested systems neglecting the electrical losses. When the electrical losses are taken into account, the solution obtained using the Garver system is better than the best one known in the literature.

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

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This paper analyses the impact of choosing good initial populations for genetic algorithms regarding convergence speed and final solution quality. Test problems were taken from complex electricity distribution network expansion planning. Constructive heuristic algorithms were used to generate good initial populations, particularly those used in resolving transmission network expansion planning. The results were compared to those found by a genetic algorithm with random initial populations. The results showed that an efficiently generated initial population led to better solutions being found in less time when applied to low complexity electricity distribution networks and better quality solutions for highly complex networks when compared to a genetic algorithm using random initial populations.