199,769 research outputs found

    Design of a smart turning tool with application to in-process cutting force measurement in ultraprecision and micro cutting

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    In modern micromachining, there is a need to measure and monitor certain machining process parameters in process so as to detect tool wear in real time, to optimize the process parameters setup, and to render the machining process some level of smartness and intelligence. This paper presents the innovative design of a smart turning tool using two pieces of piezoelectric films to measure cutting and feed force in real time. The tool was tested on its performance through the calibration and cutting trials against the commercial dynamometer. The results show the smart turning tool has achieved the performance as designed

    Negative Refraction and Subwavelength Lensing in a Polaritonic Crystal

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    We show that a two-dimensional polaritonic crystal, made of metallic rods that support well defined plasmon oscillations, can act in a narrow frequency range as a medium in which a negative refraction and subwavelength lensing can occur. We show that surface modes are excited on the surface of the lens, and that they facilitate restoration of the evanescent waves, which carry the subwavelength image information. We demonstrate that this can occur in the visible frequency range, for a wide range of materials, including silver and aluminum rods, and carbon nanotubes. This flexibility should allow for an experimental demonstration of this phenomenon in the visible frequency range.Comment: 14 pages; 4 figure

    Bidirectional optimization of the melting spinning process

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    This is the author's accepted manuscript (under the provisional title "Bi-directional optimization of the melting spinning process with an immune-enhanced neural network"). The final published article is available from the link below. Copyright 2014 @ IEEE.A bidirectional optimizing approach for the melting spinning process based on an immune-enhanced neural network is proposed. The proposed bidirectional model can not only reveal the internal nonlinear relationship between the process configuration and the quality indices of the fibers as final product, but also provide a tool for engineers to develop new fiber products with expected quality specifications. A neural network is taken as the basis for the bidirectional model, and an immune component is introduced to enlarge the searching scope of the solution field so that the neural network has a larger possibility to find the appropriate and reasonable solution, and the error of prediction can therefore be eliminated. The proposed intelligent model can also help to determine what kind of process configuration should be made in order to produce satisfactory fiber products. To make the proposed model practical to the manufacturing, a software platform is developed. Simulation results show that the proposed model can eliminate the approximation error raised by the neural network-based optimizing model, which is due to the extension of focusing scope by the artificial immune mechanism. Meanwhile, the proposed model with the corresponding software can conduct optimization in two directions, namely, the process optimization and category development, and the corresponding results outperform those with an ordinary neural network-based intelligent model. It is also proved that the proposed model has the potential to act as a valuable tool from which the engineers and decision makers of the spinning process could benefit.National Nature Science Foundation of China, Ministry of Education of China, the Shanghai Committee of Science and Technology), and the Fundamental Research Funds for the Central Universities

    Bianchi Type III String Cosmological Models with Time Dependent Bulk Viscosity

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    Bianchi type III string cosmological models with bulk viscous fluid for massive string are investigated. To get the determinate model of the universe, we have assumed that the coefficient of bulk viscosity (ξ\xi) is inversely proportional to the expansion (θ\theta) in the model and expansion (θ\theta) in the model is proportional to the shear (σ\sigma). This leads to B=ℓCnB = \ell C^{n}, ℓ\ell and nn are constants. The behaviour of the model in presence and absence of bulk viscosity, is discussed. The physical implications of the models are also discussed in detail.Comment: 11 pages, no figur

    Thermal and ground-state entanglement in Heisenberg XX qubit rings

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    We study the entanglement of thermal and ground states in Heisernberg XXXX qubit rings with a magnetic field. A general result is found that for even-number rings pairwise entanglement between nearest-neighbor qubits is independent on both the sign of exchange interaction constants and the sign of magnetic fields. As an example we study the entanglement in the four-qubit model and find that the ground state of this model without magnetic fields is shown to be a four-body maximally entangled state measured by the NN-tangle.Comment: Four pages and one figure, small change
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