124 resultados para variational techniques


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Novel switching sequences have been proposed recently for a neutral-point-clamped three-level inverter, controlled effectively as an equivalent two-level inverter. It is shown that the four novel sequences can be grouped into two pairs of sequences. Using each pair of sequences, a hybrid pulsewidth modulation (PWM) technique is proposed, which deploys the two sequences in appropriate spatial regions to reduce the current ripple. Further, a third hybrid PWM technique is proposed which uses all the five sequences (including the conventional sequence) in appropriate spatial regions. Each proposed hybrid PWM is shown, both analytically and experimentally, to outperform its constituent PWM methods in terms of harmonic distortion. In particular, the third proposed hybrid PWM reduces the total harmonic distortion considerably at low- and high-speed ranges of a constant volts-per-hertz induction motor drive, compared to centered space vector PWM.

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In this article, we aim at reducing the error rate of the online Tamil symbol recognition system by employing multiple experts to reevaluate certain decisions of the primary support vector machine classifier. Motivated by the relatively high percentage of occurrence of base consonants in the script, a reevaluation technique has been proposed to correct any ambiguities arising in the base consonants. Secondly, a dynamic time-warping method is proposed to automatically extract the discriminative regions for each set of confused characters. Class-specific features derived from these regions aid in reducing the degree of confusion. Thirdly, statistics of specific features are proposed for resolving any confusions in vowel modifiers. The reevaluation approaches are tested on two databases (a) the isolated Tamil symbols in the IWFHR test set, and (b) the symbols segmented from a set of 10,000 Tamil words. The recognition rate of the isolated test symbols of the IWFHR database improves by 1.9 %. For the word database, the incorporation of the reevaluation step improves the symbol recognition rate by 3.5 % (from 88.4 to 91.9 %). This, in turn, boosts the word recognition rate by 11.9 % (from 65.0 to 76.9 %). The reduction in the word error rate has been achieved using a generic approach, without the incorporation of language models.

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The realization of optical lattices of cold atoms has opened up the possibility of engineering interacting lattice systems of bosons and fermions, stimulating a frenzy of research over the last decade. More recently, experimental techniques have been developed to apply synthetic gauge fields to these optical lattices. As a result, it has become possible to study quantum Hall physics and the effects of frustration in lattices of cold atoms. In this article we describe the combined effect of frustration and interactions on the superfluidity of bosons. By focussing on a frustrated ladder of interacting bosons, we show that the effect of frustration is for ``chiral'' order to develop, which manifests itself as an alternating pattern of circulating supercurrents. Remarkably, this order persists even when superfluidity is lost and the system enters a Mott phase giving rise to a novel chiral Mott insulator. We describe the combined physics of frustration and interactions by studying a fully frustrated one dimensional model of interacting bosons. The model is studied using mean-field theory, a direct quantum simulation and a higher dimensional classical theory in order to offer a full description of the different quantum phases contained in it and transitions between the different phases. In addition, we provide physical descriptions of the chiral Mott insulator as a vortex-anitvortex super solid and indirect excitonic condensate in addition to obtaining a variational wavefunction for it. We also briefly describe the chiral Mott states arising in other microscopic models.

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In GaAs-based pseudomorphic high-electron mobility transistor device structures, strain and composition of the InxGa1 (-) As-x channel layer are very important as they influence the electronic properties of these devices. In this context, transmission electron microscopy techniques such as (002) dark-field imaging, high-resolution transmission electron microscopy (HRTEM) imaging, scanning transmission electron microscopy-high angle annular dark field (STEM-HAADF) imaging and selected area diffraction, are useful. A quantitative comparative study using these techniques is relevant for assessing the merits and limitations of the respective techniques. In this article, we have investigated strain and composition of the InxGa1 (-) As-x layer with the mentioned techniques and compared the results. The HRTEM images were investigated with strain state analysis. The indium content in this layer was quantified by HAADF imaging and correlated with STEM simulations. The studies showed that the InxGa1 (-) As-x channel layer was pseudomorphically grown leading to tetragonal strain along the 001] growth direction and that the average indium content (x) in the epilayer is similar to 0.12. We found consistency in the results obtained using various methods of analysis.

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Carbon Fiber Reinforced Plastic composites were fabricated through vacuum resin infusion technology by adopting two different processing conditions, viz., vacuum only in the first and vacuum plus external pressure in the next, in order to generate two levels of void-bearing samples. They were relatively graded as higher and lower void-bearing ones, respectively. Microscopy and C-scan techniques were utilized to describe the presence of voids arising from the two different processing parameters. Further, to determine the influence of voids on impact behavior, the fabricated +45 degrees/90 degrees/-45 degrees composite samples were subjected to low velocity impacts. The tests show impact properties like peak load and energy to peak load registering higher values for the lower void-bearing case where as the total energy, energy for propagation and ductility indexes were higher for the higher void-bearing ones. Fractographic analysis showed that higher void-bearing samples display lower number of separation of layers in the laminate. These and other results are described and discussed in this report.

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The problem of modelling the transient response of an elastic-perfectly-plastic cantilever beam, carrying an impulsively loaded tip mass, is,often referred to as the Parkes cantilever problem 25]; The permanent deformation of a cantilever struck transversely at its tip, Proc. R. Soc. A., 288, pp. 462). This paradigm for classical modelling of projectile impact on structures is re-visited and updated using the mesh-free method, smoothed particle hydrodynamics (SPH). The purpose of this study is to investigate further the behaviour of cantilever beams subjected to projectile impact at its tip, by considering especially physically real effects such as plastic shearing close to the projectile, shear deformation, and the variation of the shear strain along the length and across the thickness of the beam. Finally, going beyond macroscopic structural plasticity, a strategy to incorporate physical discontinuity (due to crack formation) in SPH discretization is discussed and explored in the context of tip-severance of the cantilever beam. Consequently, the proposed scheme illustrates the potency for a more refined treatment of penetration mechanics, paramount in the exploration of structural response under ballistic loading. The objective is to contribute to formulating a computational modelling framework within which transient dynamic plasticity and even penetration/failure phenomena for a range of materials, structures and impact conditions can be explored ab initio, this being essential for arriving at suitable tools for the design of armour systems. (C) 2014 Elsevier Ltd. All rights reserved.

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Models of river flow time series are essential in efficient management of a river basin. It helps policy makers in developing efficient water utilization strategies to maximize the utility of scarce water resource. Time series analysis has been used extensively for modeling river flow data. The use of machine learning techniques such as support-vector regression and neural network models is gaining increasing popularity. In this paper we compare the performance of these techniques by applying it to a long-term time-series data of the inflows into the Krishnaraja Sagar reservoir (KRS) from three tributaries of the river Cauvery. In this study flow data over a period of 30 years from three different observation points established in upper Cauvery river sub-basin is analyzed to estimate their contribution to KRS. Specifically, ANN model uses a multi-layer feed forward network trained with a back-propagation algorithm and support vector regression with epsilon intensive-loss function is used. Auto-regressive moving average models are also applied to the same data. The performance of different techniques is compared using performance metrics such as root mean squared error (RMSE), correlation, normalized root mean squared error (NRMSE) and Nash-Sutcliffe Efficiency (NSE).

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The problem addressed in this paper is sound, scalable, demand-driven null-dereference verification for Java programs. Our approach consists conceptually of a base analysis, plus two major extensions for enhanced precision. The base analysis is a dataflow analysis wherein we propagate formulas in the backward direction from a given dereference, and compute a necessary condition at the entry of the program for the dereference to be potentially unsafe. The extensions are motivated by the presence of certain ``difficult'' constructs in real programs, e.g., virtual calls with too many candidate targets, and library method calls, which happen to need excessive analysis time to be analyzed fully. The base analysis is hence configured to skip such a difficult construct when it is encountered by dropping all information that has been tracked so far that could potentially be affected by the construct. Our extensions are essentially more precise ways to account for the effect of these constructs on information that is being tracked, without requiring full analysis of these constructs. The first extension is a novel scheme to transmit formulas along certain kinds of def-use edges, while the second extension is based on using manually constructed backward-direction summary functions of library methods. We have implemented our approach, and applied it on a set of real-life benchmarks. The base analysis is on average able to declare about 84% of dereferences in each benchmark as safe, while the two extensions push this number up to 91%. (C) 2014 Elsevier B.V. All rights reserved.

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Streamflow forecasts at daily time scale are necessary for effective management of water resources systems. Typical applications include flood control, water quality management, water supply to multiple stakeholders, hydropower and irrigation systems. Conventionally physically based conceptual models and data-driven models are used for forecasting streamflows. Conceptual models require detailed understanding of physical processes governing the system being modeled. Major constraints in developing effective conceptual models are sparse hydrometric gauge network and short historical records that limit our understanding of physical processes. On the other hand, data-driven models rely solely on previous hydrological and meteorological data without directly taking into account the underlying physical processes. Among various data driven models Auto Regressive Integrated Moving Average (ARIMA), Artificial Neural Networks (ANNs) are most widely used techniques. The present study assesses performance of ARIMA and ANNs methods in arriving at one-to seven-day ahead forecast of daily streamflows at Basantpur streamgauge site that is situated at upstream of Hirakud Dam in Mahanadi river basin, India. The ANNs considered include Feed-Forward back propagation Neural Network (FFNN) and Radial Basis Neural Network (RBNN). Daily streamflow forecasts at Basantpur site find use in management of water from Hirakud reservoir. (C) 2015 The Authors. Published by Elsevier B.V.

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An asymptotically-exact methodology is presented for obtaining the cross-sectional stiffness matrix of a pre-twisted moderately-thick beam having rectangular cross sections and made of transversely isotropic materials. The anisotropic beam is modeled from 3-D elasticity, without any further assumptions. The beam is allowed to have large displacements and rotations, but small strain is assumed. The strain energy of the beam is computed making use of the constitutive law and the kinematical relations derived with the inclusion of geometrical nonlinearities and initial twist. Large displacements and rotations are allowed, but small strain is assumed. The Variational Asymptotic Method is used to minimize the energy functional, thereby reducing the cross section to a point on the reference line with appropriate properties, yielding a 1-D constitutive law. In this method as applied herein, the 2-D cross-sectional analysis is performed asymptotically by taking advantage of a material small parameter and two geometric small parameters. 3-D strain components are derived using kinematics and arranged as orders of the small parameters. Warping functions are obtained by the minimization of strain energy subject to certain set of constraints that renders the 1-D strain measures well-defined. Closed-form expressions are derived for the 3-D non-linear warping and stress fields. The model is capable of predicting interlaminar and transverse shear stresses accurately up to first order.

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This work deals with the homogenization of an initial- and boundary-value problem for the doubly-nonlinear system D(t)w - del.(z) over right arrow = g(x, t, x/epsilon) (0.1) w is an element of alpha(u, x/epsilon) (0.2) (z) over right arrow is an element of (gamma) over right arrow (del u, x/epsilon) (0.3) Here epsilon is a positive parameter; alpha and (gamma) over right arrow are maximal monotone with respect to the first variable and periodic with respect to the second one. The inclusions (0.2) and (0.3) are here formulated as null-minimization principles, via the theory of Fitzpatrick MR 1009594]. As epsilon -> 0, a two-scale formulation is derived via Nguetseng's notion of two-scale convergence, and a (single-scale) homogenized problem is then retrieved. (C) 2015 Elsevier Ltd. All rights reserved.

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This work deals with the homogenization of an initial- and boundary-value problem for the doubly-nonlinear system D(t)w - del.(z) over right arrow = g(x, t, x/epsilon) (0.1) w is an element of alpha(u, x/epsilon) (0.2) (z) over right arrow is an element of (gamma) over right arrow (del u, x/epsilon) (0.3) Here epsilon is a positive parameter; alpha and (gamma) over right arrow are maximal monotone with respect to the first variable and periodic with respect to the second one. The inclusions (0.2) and (0.3) are here formulated as null-minimization principles, via the theory of Fitzpatrick MR 1009594]. As epsilon -> 0, a two-scale formulation is derived via Nguetseng's notion of two-scale convergence, and a (single-scale) homogenized problem is then retrieved. (C) 2015 Elsevier Ltd. All rights reserved.

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This work presents the development of piezocomposites made up of Macro Fiber Composites (MFCs) for aerospace applications and specifically involves, their computational analysis, material characterization and certain parametric studies. MFC was developed by NASA Langley Research Center in 1996 and currently is being distributed by Smart Material Co. 1] worldwide and finds applications both as an actuator as well as for sensor in various engineering applications. In this work, MFC is being modeled as an actuator and a theoretical formulation based on Variational Asymptotic Method (VAM) 2] is presented to analyse the laminates made up of MFCs. VAM minimizes the total electro-mechanical energy for the MFC laminate and approaches the exact solution asymptotically by making use of certain small parameters inherent to the problem through dimensional reduction. VAM provides closed form solutions for 1D constitutive law, recovery relations of warpings, 3D stress/strain fields and displacements and hence an ideal tool for carrying out parametric and design studies in such applications. VAM is geometrically exact and offers rigorous material characterization through cross-sectional analysis and dimensional reduction.

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The cross-sectional stiffness matrix is derived for a pre-twisted, moderately thick beam made of transversely isotropic materials and having rectangular cross sections. An asymptotically-exact methodology is used to model the anisotropic beam from 3-D elasticity, without any further assumptions. The beam is allowed to have large displacements and rotations, but small strain is assumed. The strain energy is computed making use of the beam constitutive law and kinematical relations derived with the inclusion of geometrical nonlinearities and an initial twist. The energy functional is minimized making use of the Variational Asymptotic Method (VAM), thereby reducing the cross section to a point on the beam reference line with appropriate properties, forming a 1-D constitutive law. VAM is a mathematical technique employed in the current problem to rigorously split the 3-D analysis of beams into two: a 2-D analysis over the beam cross-sectional domain, which provides a compact semi-analytical form of the properties of the cross sections, and a nonlinear 1-D analysis of the beam reference curve. In this method, as applied herein, the cross-sectional analysis is performed asymptotically by taking advantage of a material small parameter and two geometric small parameters. 3-D strain components are derived using kinematics and arranged in orders of the small parameters. Closed-form expressions are derived for the 3-D non-linear warping and stress fields. Warping functions are obtained by the minimization of strain energy subject to certain set of constraints that render the 1-D strain measures well-defined. The zeroth-order 3-D warping field thus yielded is then used to integrate the 3-D strain energy density over the cross section, resulting in the 1-D strain energy density, which in turn helps identify the corresponding cross-sectional stiffness matrix. The model is capable of predicting interlaminar and transverse shear stresses accurately up to first order.