19 resultados para Montreal CMA


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A comparative study has been carried out of R-12, 22, 125, 134a, 152a, 218, 245, 500, 502, 507 and 717 as working fluids in a vapour-compression refrigeration system. Two performance parameters were defined, which are expressed in reduced quantities for a corresponding-states comparison of these refrigerants in the temperature range -20 to 50-degrees-C. One is based on the product of temperature drop to pressure penalty ratio and the available volumetric heat of vaporisation at the evaporator; the other considers the effect of isentropic compression in the ideal gas state. It was shown that R-125, 507 and 218 could be better alternatives to R-12 than R-134a. Among these, R-218 has a lower maximum cycle pressure.

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This article examines, through a molecular perspective, the 'ozone-friendly' refrigerants R-134a and R-123 vis-à-vis R-12 and R-11, which are targeted to be phased out under the Montreal Protocol on Substances that Deplete the Ozone Layer, Final Act (1987). It appears that the molecular weight, size parameter, and dipole moment, of R-134a and R-123, may induce a pronounced effect on the chemical equilibrium of ice particles in the polar stratospheric clouds and subsequently influence the photochemical reactions therein. Non-polar, high-molecular-weight perfluoropropane (R-218), could be a better substitute for R-12, while R-134, which is a non-polar HFC of the ethane family, could also be a candidate although its molecular weight is lower than that of R-12. The search for a good substitute for R-11, however, must continue.

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Four hybrid algorithms has been developed for the solution of the unit commitment problem. They use simulated annealing as one of the constituent techniques, and produce lower cost schedules; two of them have less overhead than other soft computing techniques. They are also more robust to the choice of parameters. A special technique avoids the generating of infeasible schedules, and thus reduces computation time.

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Variation of switching frequency over the entire operating speed range of an induction motor (M drive is the major problem associated with conventional two-level three-phase hysteresis controller as well as the space phasor based PWM hysteresis controller. This paper describes a simple hysteresis current controller for controlling the switching frequency variation in the two-level PWM inverter fed IM drives for various operating speeds. A novel concept of continuously variable hysteresis boundary of current error space phasor with the varying speed of the IM drive is proposed in the present work. The variable parabolic boundary for the current error space phasor is suggested for the first time in this paper for getting the switching frequency pattern with the hysteresis controller, similar to that of the constant switching frequency voltage-controlled space vector PWM (VC-SVPWM) based inverter fed IM drive. A generalized algorithm is also developed to determine parabolic boundary for controlling the switching frequency variation, for any IM load. Only the adjacent inverter voltage vectors forming a triangular sector, in which tip of the machine voltage vector ties, are switched to keep current error space vector within the parabolic boundary. The controller uses a self-adaptive sector identification logic, which provides smooth transition between the sectors and is capable of taldng the inverter up to six-step mode of operation, if demanded by drive system. The proposed scheme is simulated and experimentally verified on a 3.7 kW IM drive.

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An attempt has been made to study the effect of time and test procedure on the behaviour of partial discharge (PD) pulses causing failure of oil-pressboard system under power frequency voltages using circular disc shaped samples and uniform field electrodes. Weibull statistics have been used to handle the large amount of PD data. The PD phenomena has been found to be stress and time dependent. On the basis of stress level, three different regions are identified and in one of the regions, the rate of deterioration of the sample is at a maximum. The work presents some interesting features of Weibull parameters as related to the condition of insulation studied in addition to its usual PD characteristics

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Stress wave characteristics are drastically altered by joints and other inhomogenities. This paper addresses the effect of an open joint on stress wave transmission. An elastodynamic analysis is developed to supplement and explain some recent observations by Fourney and Dick(1995) on open as well as filled joints. The analytical model developed here assuming spherical symmetry can be extended to filled joints between dissimilar media, but results are presented only for open joints separating identical materials. As a special case, stress wave transmission across a joint with no gap is also addressed.

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This paper presents an artificial feed forward neural network (FFNN) approach for the assessment of power system voltage stability. A novel approach based on the input-output relation between real and reactive power, as well as voltage vectors for generators and load buses is used to train the neural net (NN). The input properties of the feed forward network are generated from offline training data with various simulated loading conditions using a conventional voltage stability algorithm based on the L-index. The neural network is trained for the L-index output as the target vector for each of the system loads. Two separate trained NN, corresponding to normal loading and contingency, are investigated on the 367 node practical power system network. The performance of the trained artificial neural network (ANN) is also investigated on the system under various voltage stability assessment conditions. As compared to the computationally intensive benchmark conventional software, near accurate results in the value of L-index and thus the voltage profile were obtained. Proposed algorithm is fast, robust and accurate and can be used online for predicting the L-indices of all the power system buses. The proposed ANN approach is also shown to be effective and computationally feasible in voltage stability assessment as well as potential enhancements within an overall energy management system in order to determining local and global stability indices

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This paper presents a singular edge-based smoothed finite element method (sES-FEM) for mechanics problems with singular stress fields of arbitrary order. The sES-FEM uses a basic mesh of three-noded linear triangular (T3) elements and a special layer of five-noded singular triangular elements (sT5) connected to the singular-point of the stress field. The sT5 element has an additional node on each of the two edges connected to the singular-point. It allows us to represent simple and efficient enrichment with desired terms for the displacement field near the singular-point with the satisfaction of partition-of-unity property. The stiffness matrix of the discretized system is then obtained using the assumed displacement values (not the derivatives) over smoothing domains associated with the edges of elements. An adaptive procedure for the sES-FEM is proposed to enhance the quality of the solution with minimized number of nodes. Several numerical examples are provided to validate the reliability of the present sES-FEM method. (C) 2012 Elsevier B.V. All rights reserved.

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Multilevel inverters with hexagonal and dodecagonal voltage space vector structures have improved harmonic profile compared to two level inverters. Further improvement in the quality of the waveform is possible using multilevel octadecagonal (18 sided polygon) voltage space vectors. This paper proposes an inverter circuit topology capable of generating multilevel octadecagonal voltage space vectors, by cascading two asymmetric three level inverters. By proper selection of DC link voltages and the resultant switching states for the inverters, voltage space vectors, whose tips lie on three concentric octadecagons, are obtained. The advantages of octadecagonal voltage space vector based PWM techniques are the complete elimination of fifth, seventh, eleventh and thirteenth harmonics in phase voltages and the extension of linear modulation range. In this paper, a simple PWM timing calculation method is also proposed. Matlab simulation results and experimental results have been presented in this paper to validate the proposed concept.

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The paper presents a new controller inspired by the human experience based, voluntary body action control (dubbed motor control) learning mechanism. The controller is called Experience Mapping based Prediction Controller (EMPC). EMPC is designed with auto-learning features without the need for the plant model. The core of the controller is formed around the motor action prediction-control mechanism of humans based on past experiential learning with the ability to adapt to environmental changes intelligently. EMPC is utilized for high precision position control of DC motors. The simulation results are presented to show that accurate position control is achieved using EMPC for step and dynamic demands. The performance of EMPC is compared with conventional PD controller and MRAC based position controller under different system conditions. Position Control using EMPC is practically implemented and the results are presented.

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Impact angle constrained guidance laws are important in many applications such as guidance of torpedoes, anti-ballistic missiles and reentry vehicles. In this paper, we design a guidance law which is capable of achieving a wide range of impact angles. Biased proportional navigation guidance uses a bias term in addition to the basic PN command to satisfy additional constraints. Angle constrained BPNG (ACBPNG) uses small angle approximations to derive the bias term for impact angle requirement. We design a modified ACBPNG (MACBPNG) where the required bias term is derived in a closed form considering non-linear equations of motion. Simulations are carried out for a wide range of impact angle requirements. We also analyze capturability from different initial positions and also the launch angles possible at each initial position. The performance of the proposed law is compared with an existing law.

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A guidance law derived by modifying state dependent Riccati equation technique, to enable the imposition of a predetermined terminal intercept angle to a maneuvering target, is presented in this paper. The interceptor is assumed to have no knowledge about the type of maneuver the target is executing. The problem is cast in a non-cooperative game theoretic form. The guidance law obtained is dependent on the LOS angular rotational rate and on the impact angle error. Theoretical conditions which guarantee existence of solutions under this method have been derived. It is shown that imposing the impact angle constraint calls for an increase in the gains of the guidance law considerably, subsequently requiring a higher maneuverability advantage of the interceptor. The performance of the proposed guidance law is studied using a non-linear two dimensional simulation of the relative kinematics, assuming first order dynamics for the interceptor and target.

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In several systems, the physical parameters of the system vary over time or operating points. A popular way of representing such plants with structured or parametric uncertainties is by means of interval polynomials. However, ensuring the stability of such systems is a robust control problem. Fortunately, Kharitonov's theorem enables the analysis of such interval plants and also provides tools for design of robust controllers in such cases. The present paper considers one such case, where the interval plant is connected with a timeinvariant, static, odd, sector type nonlinearity in its feedback path. This paper provides necessary conditions for the existence of self sustaining periodic oscillations in such interval plants, and indicates a possible design algorithm to avoid such periodic solutions or limit cycles. The describing function technique is used to approximate the nonlinearity and subsequently arrive at the results. Furthermore, the value set approach, along with Mikhailov conditions, are resorted to in providing graphical techniques for the derivation of the conditions and subsequent design algorithm of the controller.

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In this paper we propose a framework for optimum steering input determination of all-wheel steer vehicles (AWSV) on rough terrains. The framework computes the steering input which minimizes the tracking error for a given trajectory. Unlike previous methodologies of computing steering inputs of car-like vehicles, the proposed methodology depends explicitly on the vehicle dynamics and can be extended to vehicle having arbitrary number of steering inputs. A fully generic framework has been used to derive the vehicle dynamics and a non-linear programming based constrained optimization approach has been used to compute the steering input considering the instantaneous vehicle dynamics, no-slip and contact constraints of the vehicle. All Wheel steer Vehicles have a special parallel steering ability where the instantaneous centre of rotation (ICR) is at infinity. The proposed framework automatically enables the vehicle to choose between parallel steer and normal operation depending on the error with respect to the desired trajectory. The efficacy of the proposed framework is proved by extensive uneven terrain simulations, for trajectories with continuous or discontinuous velocity profile.

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This paper addresses the problem of localizing the sources of contaminants spread in the environment, and mapping the boundary of the affected region using an innovative swarm intelligence based technique. Unlike most work in this area the algorithm is capable of localizing multiple sources simultaneously while also mapping the boundary of the contaminant spread. At the same time the algorithm is suitable for implementation using a mobile robotic sensor network. Two types of agents, called the source localization agents (or S-agents) and boundary mapping agents (or B-agents) are used for this purpose. The paper uses the basic glowworm swarm optimization (GSO) algorithm, which has been used only for multiple signal source localization, and modifies it considerably to make it suitable for both these tasks. This requires the definition of new behaviour patterns for the agents based on their terminal performance as well as interactions between them that helps the swarm to split into subgroups easily and identify contaminant sources as well as spread along the boundary to map its full length. Simulations results are given to demonstrate the efficacy of the algorithm.