74 resultados para back-tracking deployment (BTD)


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For hybrid electric vehicles the batteries and the drive dc-link may be at different voltages. The batteries are at low voltage to obtain higher volumetric efficiencies and the dc-link is at higher voltage to have higher efficiency on the motor side. Therefore a power interface between the batteries and the drive's dc-link is essential. This power interface should handle power flow from battery to motor, motor to battery, external genset to battery and grid to battery. This paper proposes a multi power port topology which is capable of handling multiple power sources and still maintains simplicity and features like obtaining any gain, wide load variations, lower output current ripple and capability of parallel battery energy due to the modular structure. The development and testing of a bi-directional fly-back DC-DC converter for hybrid electric vehicle is described in this paper. Simple hysteresis voltage control is used for DC link voltage regulation. The experimental results are presented to show the working of the proposed converter.

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We discuss the key issues in the deployment of sparse sensor networks. The network monitors several environment parameters and is deployed in a semi-arid region for the benefit of small and marginal farmers. We begin by discussing the problems of an existing unreliable 1 sq km sparse network deployed in a village. The proposed solutions are implemented in a new cluster. The new cluster is a reliable 5 sq km network. Our contributions are two fold. Firstly, we describe a. novel methodology to deploy a sparse reliable data gathering sensor network and evaluate the ``safe distance'' or ``reliable'' distance between nodes using propagation models. Secondly, we address the problem of transporting data from rural aggregation servers to urban data centres. This paper tracks our steps in deploying a sensor network in a village,in India, trying to provide better diagnosis for better crop management. Keywords - Rural, Agriculture, CTRS, Sparse.

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The stochasticity of domain-wall (DW) motion in magnetic nanowires has been probed by measuring slow fluctuations, or noise, in electrical resistance at small magnetic fields. By controlled injection of DWs into isolated cylindrical nanowires of nickel, we have been able to track the motion of the DWs between the electrical leads by discrete steps in the resistance. Closer inspection of the time dependence of noise reveals a diffusive random walk of the DWs with a universal kinetic exponent. Our experiments outline a method with which electrical resistance is able to detect the kinetic state of the DWs inside the nanowires, which can be useful in DW-based memory designs.

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Back face strain (BFS) measurement is now well-established as an indirect technique to monitor crack length in compact tension (CT) fracture specimens [1,2]. Previous work [2] developed empirical relations between fatigue crack propagation (FCP) parameters. BFS, and number of cycles for CT specimens subjected to constant amplitude fatigue loading. These predictions are experimentally validated in terms of the variations of mean values of BFS and load as a function of crack length. Another issue raised by this study concerns the validity of assigning fixed values for the Paris parameters C and n to describe FCP in realistic materials.

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We consider the problem of tracking an intruder in a plane region by using a wireless sensor network comprising motes equipped with passive infrared (PIR) sensors deployed over the region. An input-output model for the PIR sensor and a method to estimate the angular speed of the target from the sensor output are proposed. With the measurement model so obtained, we study the centralized and decentralized tracking performance using the extended Kalman filter.

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Many physical problems can be modeled by scalar, first-order, nonlinear, hyperbolic, partial differential equations (PDEs). The solutions to these PDEs often contain shock and rarefaction waves, where the solution becomes discontinuous or has a discontinuous derivative. One can encounter difficulties using traditional finite difference methods to solve these equations. In this paper, we introduce a numerical method for solving first-order scalar wave equations. The method involves solving ordinary differential equations (ODEs) to advance the solution along the characteristics and to propagate the characteristics in time. Shocks are created when characteristics cross, and the shocks are then propagated by applying analytical jump conditions. New characteristics are inserted in spreading rarefaction fans. New characteristics are also inserted when values on adjacent characteristics lie on opposite sides of an inflection point of a nonconvex flux function, Solutions along characteristics are propagated using a standard fourth-order Runge-Kutta ODE solver. Shocks waves are kept perfectly sharp. In addition, shock locations and velocities are determined without analyzing smeared profiles or taking numerical derivatives. In order to test the numerical method, we study analytically a particular class of nonlinear hyperbolic PDEs, deriving closed form solutions for certain special initial data. We also find bounded, smooth, self-similar solutions using group theoretic methods. The numerical method is validated against these analytical results. In addition, we compare the errors in our method with those using the Lax-Wendroff method for both convex and nonconvex flux functions. Finally, we apply the method to solve a PDE with a convex flux function describing the development of a thin liquid film on a horizontally rotating disk and a PDE with a nonconvex flux function, arising in a problem concerning flow in an underground reservoir.

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Owing to the increased customer demands for make-to-order products and smaller product life-cycles, today assembly lines are designed to ensure a quick switch-over from one product model to another for companies' survival in market place. The complexity associated with the decisions pertaining to the type of training and number of workers and their exposition to the different tasks especially in the current era of customized production is a serious problem that the managers and the HRD gurus are facing in industry. This paper aims to determine the amount of cross-training and dynamic deployment policy caused by workforce flexibility for a make-to-order assembly. The aforementioned issues have been dealt with by adopting the concept of evolutionary fuzzy system because of the linguistic nature of the attributes associated with product variety and task complexity. A fuzzy system-based methodology is proposed to determine the amount of cross-training and dynamic deployment policy. The proposed methodology is tested on 10 sample products of varying complexities and the results obtained are in line with the conclusions drawn by previous researchers.

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ASTM D2303 standard provides a method for evaluating the tracking and erosion resistance of polymeric insulators under ac voltages. In this paper, the above method has been extended for evaluating the performance of the insulators under dc stresses. Tests were conducted on polymeric silicone rubber (SR) insulators under positive and negative dc stresses. Micron sized Alumina trihydrate (uATH) and nano sized Alumina (nALU) were used as fillers in SR matrix to improve the resistance to tracking and erosion. Results suggest that SR composites perform better under negative dc than under positive dc voltages. Eroded mass and leakage current data support the above result. Samples with low concentration of nano alumina fillers performed on par with the samples with large loadings of uATH.

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