286 resultados para Dynamic Meniscus Profile


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In this paper, we have proposed a centralized multicast authentication protocol (MAP) for dynamic multicast groups in wireless networks. In our protocol, a multicast group is defined only at the time of the multicasting. The authentication server (AS) in the network generates a session key and authenticates it to each of the members of a multicast group using the computationally inexpensive least common multiple (LCM) method. In addition, a pseudo random function (PRF) is used to bind the secret keys of the network members with their identities. By doing this, the AS is relieved from storing per member secrets in its memory, making the scheme completely storage scalable. The protocol minimizes the load on the network members by shifting the computational tasks towards the AS node as far as possible. The protocol possesses a membership revocation mechanism and is protected against replay attack and brute force attack. Analytical and simulation results confirm the effectiveness of the proposed protocol.

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This paper presents an advanced single network adaptive critic (SNAC) aided nonlinear dynamic inversion (NDI) approach for simultaneous attitude control and trajectory tracking of a micro-quadrotor. Control of micro-quadrotors is a challenging problem due to its small size, strong coupling in pitch-yaw-roll and aerodynamic effects that often need to be ignored in the control design process to avoid mathematical complexities. In the proposed SNAC aided NDI approach, the gains of the dynamic inversion design are selected in such a way that the resulting controller behaves closely to a pre-synthesized SNAC controller for the output regulation problem. However, since SNAC is based on optimal control theory, it makes the dynamic inversion controller to operate near optimal and enhances its robustness property as well. More important, it retains two major benefits of dynamic inversion: (i) closed form expression of the controller and (ii) easy scalability to command tracking application even without any apriori knowledge of the reference command. Effectiveness of the proposed controller is demonstrated from six degree-of-freedom simulation studies of a micro-quadrotor. It has also been observed that the proposed SNAC aided NDI approach is more robust to modeling inaccuracies, as compared to the NDI controller designed independently from time domain specifications.

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Impoverishment of particles, i.e. the discretely simulated sample paths of the process dynamics, poses a major obstacle in employing the particle filters for large dimensional nonlinear system identification. A known route of alleviating this impoverishment, i.e. of using an exponentially increasing ensemble size vis-a-vis the system dimension, remains computationally infeasible in most cases of practical importance. In this work, we explore the possibility of unscented transformation on Gaussian random variables, as incorporated within a scaled Gaussian sum stochastic filter, as a means of applying the nonlinear stochastic filtering theory to higher dimensional structural system identification problems. As an additional strategy to reconcile the evolving process dynamics with the observation history, the proposed filtering scheme also modifies the process model via the incorporation of gain-weighted innovation terms. The reported numerical work on the identification of structural dynamic models of dimension up to 100 is indicative of the potential of the proposed filter in realizing the stated aim of successfully treating relatively larger dimensional filtering problems. (C) 2013 Elsevier Ltd. All rights reserved.

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We investigate the evolution of polymer structure and its influence on uniaxial anisotropic stress under time-varying uniaxial strain, and the role of external control variables such as temperature, strain rate, chain length, and density, using molecular dynamics simulation. At temperatures higher than glass transition, stress anisotropy in the system is reduced even though the bond stretch is greater at higher temperatures. There is a significant increase in the stress level with increasing density. At higher densities, the uncoiling of the chains is suppressed and the major contribution to the deformation is by internal deformation of the chains. At faster rates of loading stress anisotropy increases. The deformation mechanism is mostly due to bond stretch and bond bending rather than overall shape and size. Stress levels increase with longer chain length. There is a critical value of the functionality of the cross-linkers beyond which the uniaxial stress developed increases caused primarily by bond stretching due to increased constraint on the motion of the monomers. Stacking of the chains in the system also plays a dominant role in the behaviour in terms of excluded volume interactions. Low density, high temperature, low values of functionality of cross-linkers, and short chain length facilitate chain uncoiling and chain slipping in cross-linked polymers.

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Surface-functionalized multiwall carbon nanotubes (MWCNTs) are incorporated in poly(methyl methacrylate)/styrene acrylonitrile (PMMA/SAN) blends and the pretransitional regime is monitored in situ by melt rheology and dielectric spectroscopy. As the blends exhibit weak dynamic asymmetry, the obvious transitions in the melt rheology due to thermal concentration fluctuations are weak. This is further supported by the weak temperature dependence of the correlation length ( approximate to 10-12 angstrom) in the vicinity of demixing. Hence, various rheological techniques in both the temperature and frequency domains are adopted to evaluate the demixing temperature. The spinodal decomposition temperature is manifested in an increase in the miscibility gap in the presence of MWCNTs. Furthermore, MWCNTs lead to a significant slowdown of the segmental dynamics in the blends. Thermally induced phase separation in the PMMA/SAN blends lead to selective localization of MWCNTs in the PMMA phase. This further manifests itself in a significant increase in the melt conductivity.

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Since Brutsaert and Neiber (1977), recession curves are widely used to analyse subsurface systems of river basins by expressing -dQ/dt as a function of Q, which typically take a power law form: -dQ/dt=kQ, where Q is the discharge at a basin outlet at time t. Traditionally recession flows are modelled by single reservoir models that assume a unique relationship between -dQ/dt and Q for a basin. However, recent observations indicate that -dQ/dt-Q relationship of a basin varies greatly across recession events, indicating the limitation of such models. In this study, the dynamic relationship between -dQ/dt and Q of a basin is investigated through the geomorphological recession flow model which models recession flows by considering the temporal evolution of its active drainage network (the part of the stream network of the basin draining water at time t). Two primary factors responsible for the dynamic relationship are identified: (i) degree of aquifer recharge (ii) spatial variation of rainfall. Degree of aquifer recharge, which is likely to be controlled by (effective) rainfall patterns, influences the power law coefficient, k. It is found that k has correlation with past average streamflow, which confirms the notion that dynamic -dQ/dt-Q relationship is caused by the degree of aquifer recharge. Spatial variation of rainfall is found to have control on both the exponent, , and the power law coefficient, k. It is noticed that that even with same and k, recession curves can be different, possibly due to their different (recession) peak values. This may also happen due to spatial variation of rainfall. Copyright (c) 2012 John Wiley & Sons, Ltd.

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We propose a novel form of nonlinear stochastic filtering based on an iterative evaluation of a Kalman-like gain matrix computed within a Monte Carlo scheme as suggested by the form of the parent equation of nonlinear filtering (Kushner-Stratonovich equation) and retains the simplicity of implementation of an ensemble Kalman filter (EnKF). The numerical results, presently obtained via EnKF-like simulations with or without a reduced-rank unscented transformation, clearly indicate remarkably superior filter convergence and accuracy vis-a-vis most available filtering schemes and eminent applicability of the methods to higher dimensional dynamic system identification problems of engineering interest. (C) 2013 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

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A paradigm shift from hard to flexible, organic-based optoelectronics requires fast and reversible mechanical response from actuating materials that are used for conversion of heat or light into mechanical motion. As the limits in the response times of polymer-based actuating materials are reached, which are inherent to the less-than-optimal coupling between the light/heat and mechanical energy in them, 1 a conceptually new approach to mechanical actuation is required to leapfrog the performance of organic actuators. Herein, we explore single crystals of 1,2,4,5-tetrabromobenzene (TBB) as actuating elements and establish relations between their kinematic profile and mechanical properties. Centimeter-size acicular crystals of TBB are the only naturally twinned crystals out of about a dozen known materials that exhibit the thermosalient effect-an extremely rare and visually impressive crystal locomotion. When taken over a phase transition, crystals of this material store mechanical strain and are rapidly self-actuated to sudden jumps to release the internal strain, leaping up to several centimeters. To establish the structural basis for this colossal crystal motility, we investigated the mechanical profile of the crystals from macroscale, in response to externally induced deformation under microscope, to nanoscale, by using nanoindentation. Kinematic analysis based on high-speed recordings of over 200 twinned TBB crystals exposed to directional or nondirectional heating unraveled that the crystal locomotion is a kinematically complex phenomenon that includes at least six kinematic effects. The nanoscale tests confirm the highly elastic nature, with an elastic deformation recovery (60%) that is far superior to those of molecular crystals reported earlier. This property appears to be critical for accumulation of stress required for crystal jumping. Twinned crystals of TBB exposed to moderate directional heating behave as all-organic analogue of a bimetallic `strip, where the lattice misfit between the two crystal components drives reveriible deformation of the crystal.

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The nano ZnFe2O4 compound was prepared by eco-friendly hydrothermal method. The characterization of the sample for its structure, morphology and composition were done by powder X-ray diffraction (PXRD), scanning electron microscopy (SEM), dynamic light scattering, Fourier transform infrared spectroscopy, zeta surface profiler and UV-Visible spectroscopy studies. The PXRD measurement reveals that the compound shows spinel cubic phase belong Fd (3) over barm (227) space group. Morphology of the compound from SEM and surface profile shows nearly spherical agglomerated particles with well defined grains and grain boundaries. The material shows the semiconducting behavior with E-g of 2.3 eV at room temperature (RT). The variation in the magnetic ordering was observed for wide range of temperature. The compound behaves like a soft magnetic material with ferrimagnetic at various temperatures except at RT. Both magnetic and EPR studies supports the superparamagnetic behavior of the the sample. The DC conductivity, dielectric and AC conductivity behavior of the 1000 degrees C pellets sintered for 2 h shows good frequency dependent transport properties. The present study facilitate in selecting the suitable materials for the nanoelectronics and spintronic applications. (C) 2013 Elsevier B.V. All rights reserved.

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The basic requirement for an autopilot is fast response and minimum steady state error for better guidance performance. The highly nonlinear nature of the missile dynamics due to the severe kinematic and inertial coupling of the missile airframe as well as the aerodynamics has been a challenge for an autopilot that is required to have satisfactory performance for all flight conditions in probable engagements. Dynamic inversion is very popular nonlinear controller for this kind of scenario. But the drawback of this controller is that it is sensitive to parameter perturbation. To overcome this problem, neural network has been used to capture the parameter uncertainty on line. The choice of basis function plays the major role in capturing the unknown dynamics. Here in this paper, many basis function has been studied for approximation of unknown dynamics. Cosine basis function has yield the best response compared to any other basis function for capturing the unknown dynamics. Neural network with Cosine basis function has improved the autopilot performance as well as robustness compared to Dynamic inversion without Neural network.

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Detection of QRS serves as a first step in many automated ECG analysis techniques. Motivated by the strong similarities between the signal structures of an ECG signal and the integrated linear prediction residual (ILPR) of voiced speech, an algorithm proposed earlier for epoch detection from ILPR is extended to the problem of QRS detection. The ECG signal is pre-processed by high-pass filtering to remove the baseline wandering and by half-wave rectification to reduce the ambiguities. The initial estimates of the QRS are iteratively obtained using a non-linear temporal feature, named the dynamic plosion index suitable for detection of transients in a signal. These estimates are further refined to obtain a higher temporal accuracy. Unlike most of the high performance algorithms, this technique does not make use of any threshold or differencing operation. The proposed algorithm is validated on the MIT-BIH database using the standard metrics and its performance is found to be comparable to the state-of-the-art algorithms, despite its threshold independence and simple decision logic.

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Thermo-mechanically processed Ti-6Al-4V alloy, with (0.1 wt.%) and without boron addition, has been subjected to tensile test under superplastic deformation conditions (Temperature, T = 850 degrees C and initial strain rate, (epsilon) over dot = 3 x 10(-4) s(-1)). The boron added alloy exhibited higher elongation (similar to 430%) in comparison to the base alloy without boron (similar to 365%). Superior ductility of the boron added alloy has been attributed to an enhanced alpha/beta interfacial boundary sliding. This was caused by riotous dynamic globularization leading to the abundant presence of equiaxed primary alpha grains with refined sizes and narrow distribution in the deforming microstructure. Cavities do occur around TiB particles during deformation; the cavities are, however, extremely localized and do not cause macroscopic cracking. (C) 2014 Elsevier Ltd. All rights reserved.