Efficient coupled polynomial interpolation scheme for out-of-plane free vibration analysis of curved beams

The performance of two curved beam finite element models based on coupled polynomial displacement fields is investigated for out-of-plane vibration of arches. These two-noded beam models employ curvilinear strain definitions and have three degrees of freedom per node namely, out-of-plane translation (v), out-of-plane bending rotation (theta(z)) and torsion rotation (theta(s)). The coupled polynomial interpolation fields are derived independently for Timoshenko and Euler-Bernoulli beam elements using the force-moment equilibrium equations. Numerical performance of these elements for constrained and unconstrained arches is compared with the conventional curved beam models which are based on independent polynomial fields. The formulation is shown to be free from any spurious constraints in the limit of `flexureless torsion' and `torsionless flexure' and hence devoid of flexure and torsion locking. The resulting stiffness and consistent mass matrices generated from the coupled displacement models show excellent convergence of natural frequencies in locking regimes. The accuracy of the shear flexibility added to the elements is also demonstrated. The coupled polynomial models are shown to perform consistently over a wide range of flexure-to-shear (EI/GA) and flexure-to-torsion (EI/GJ) stiffness ratios and are inherently devoid of flexure, torsion and shear locking phenomena. (C) 2015 Elsevier B.V. All rights reserved.

Edge states, spin transport, and impurity-induced local density of states in spin-orbit coupled graphene

We study graphene, which has both spin-orbit coupling (SOC), taken to be of the Kane-Mele form, and a Zeeman field induced due to proximity to a ferromagnetic material. We show that a zigzag interface of graphene having SOC with its pristine counterpart hosts robust chiral edge modes in spite of the gapless nature of the pristine graphene; such modes do not occur for armchair interfaces. Next we study the change in the local density of states (LDOS) due to the presence of an impurity in graphene with SOC and Zeeman field, and demonstrate that the Fourier transform of the LDOS close to the Dirac points can act as a measure of the strength of the spin-orbit coupling; in addition, for a specific distribution of impurity atoms, the LDOS is controlled by a destructive interference effect of graphene electrons which is a direct consequence of their Dirac nature. Finally, we study transport across junctions, which separates spin-orbit coupled graphene with Kane-Mele and Rashba terms from pristine graphene both in the presence and absence of a Zeeman field. We demonstrate that such junctions are generally spin active, namely, they can rotate the spin so that an incident electron that is spin polarized along some direction has a finite probability of being transmitted with the opposite spin. This leads to a finite, electrically controllable, spin current in such graphene junctions. We discuss possible experiments that can probe our theoretical predictions.

A coupled discriminative dictionary and transformation learning approach with applications to cross domain matching

Cross domain and cross-modal matching has many applications in the field of computer vision and pattern recognition. A few examples are heterogeneous face recognition, cross view action recognition, etc. This is a very challenging task since the data in two domains can differ significantly. In this work, we propose a coupled dictionary and transformation learning approach that models the relationship between the data in both domains. The approach learns a pair of transformation matrices that map the data in the two domains in such a manner that they share common sparse representations with respect to their own dictionaries in the transformed space. The dictionaries for the two domains are learnt in a coupled manner with an additional discriminative term to ensure improved recognition performance. The dictionaries and the transformation matrices are jointly updated in an iterative manner. The applicability of the proposed approach is illustrated by evaluating its performance on different challenging tasks: face recognition across pose, illumination and resolution, heterogeneous face recognition and cross view action recognition. Extensive experiments on five datasets namely, CMU-PIE, Multi-PIE, ChokePoint, HFB and IXMAS datasets and comparisons with several state-of-the-art approaches show the effectiveness of the proposed approach. (C) 2015 Elsevier B.V. All rights reserved.

A coupled discriminative dictionary and transformation learning approach with applications to cross domain matching

Cross domain and cross-modal matching has many applications in the field of computer vision and pattern recognition. A few examples are heterogeneous face recognition, cross view action recognition, etc. This is a very challenging task since the data in two domains can differ significantly. In this work, we propose a coupled dictionary and transformation learning approach that models the relationship between the data in both domains. The approach learns a pair of transformation matrices that map the data in the two domains in such a manner that they share common sparse representations with respect to their own dictionaries in the transformed space. The dictionaries for the two domains are learnt in a coupled manner with an additional discriminative term to ensure improved recognition performance. The dictionaries and the transformation matrices are jointly updated in an iterative manner. The applicability of the proposed approach is illustrated by evaluating its performance on different challenging tasks: face recognition across pose, illumination and resolution, heterogeneous face recognition and cross view action recognition. Extensive experiments on five datasets namely, CMU-PIE, Multi-PIE, ChokePoint, HFB and IXMAS datasets and comparisons with several state-of-the-art approaches show the effectiveness of the proposed approach. (C) 2015 Elsevier B.V. All rights reserved.

Identification of type and degree of railway ballast fouling using ground coupled GPR antennas

GPR is widely used for ballast fouling identification, however, there are no robust guidelines to find the degree and type of fouling quantitatively. In this study, GPR studies were carried out on model and actual railway tracks using three ground coupled antennas and considering three fouling materials. Three ground coupled antennas viz., 100 MHz, 500 MHz and 800 MHz antennas were used for the initial survey and it was found that the 800 MHz ground coupled antenna is an optimum one to get quality results. Three major fouling materials viz., screened/broken ballast, coal and iron ore were used to construct prototype model sections, which were 1/2 of the actual Indian broad-gauge railway track. A separate model section has been created for each degree and type of fouling and GPR surveys were carried out. GPR study shows that increasing the fouling content results in a decrease in the Electromagnetic Wave (EMW) velocity and an increase in the dielectric constant. EMW velocity of ballast fouled with screened ballast was found to be more than coal fouled ballast and iron ore fouled ballast at any degree of fouling and EMW velocity of iron ore fouled ballast was found to be less than coal and screen ballast fouled ballast. Dielectric constant of iron ore fouled ballast was found to be higher than coal and screen ballast fouled ballast for all degrees of fouling. Average slope of the trend line of screen ballast fouled section is low (25.6 degrees), coal fouled ballast is medium (27.8 degrees) and iron ore fouled ballast is high (47.6 degrees). (C) 2016 Elsevier B.V. All rights reserved.

COUPLED OPTICAL-THERMAL-FLUID MODELING OF A DIRECTLY HEATED TUBULAR SOLAR RECEIVER FOR SUPERCRITICAL CO2 BRAYTON CYCLE

Recent studies have evaluated closed-loop supercritical carbon dioxide (s-CO2) Brayton cycles to be a higher energy density system in comparison to conventional superheated steam Rankine systems. At turbine inlet conditions of 923K and 25 MPa, high thermal efficiency (similar to 50%) can be achieved. Achieving these high efficiencies will make concentrating solar power (CSP) technologies a competitive alternative to current power generation methods. To incorporate a s-CO2 Brayton power cycle in a solar power tower system, the development of a solar receiver capable of providing an outlet temperature of 923 K (at 25 MPa) is necessary. The s-CO2 will need to increase in temperature by similar to 200 K as it passes through the solar receiver to satisfy the temperature requirements of a s-CO2 Brayton cycle with recuperation and recompression. In this study, an optical-thermal-fluid model was developed to design and evaluate a tubular receiver that will receive a heat input similar to 2 MWth from a heliostat field. The ray-tracing tool SolTrace was used to obtain the heat-flux distribution on the surfaces of the receiver. Computational fluid dynamics (CFD) modeling using the Discrete Ordinates (DO) radiation model was used to predict the temperature distribution and the resulting receiver efficiency. The effect of flow parameters, receiver geometry and radiation absorption by s-CO2 were studied. The receiver surface temperatures were found to be within the safe operational limit while exhibiting a receiver efficiency of similar to 85%.

Optimization of dynamic properties and link performance for directly-modulated gain-coupled DFB lasers

This paper demonstrates the respective roles that combined gain- and index-coupling play in the dynamic properties and overall link performance of DFB lasers. It is shown that for datacommunication applications, modest gain-coupling enables optimum transmission at 10Gbit/s.

Enhanced 10-Gbit/s link performance for directly Modulated complex-coupled DFB lasers via resonance frequency, damping rate, and chirp

This paper demonstrates the respective roles that combined index- and gain-coupling play in the overall link performance of distributed feedback (DFB) lasers. Their impacts on both static and dynamic properties such as slope efficiency, resonance frequency, damping rate, and chirp are investigated. Simulation results are compared with experimental data with good agreement. Transmission-oriented optimization is then demonstrated based on a targeted specification. The design tradeoffs are revealed, and it is shown that a modest combination of index- and gain-coupling enables optimum transmission at 10 Gbit/s.

Design and coupled-effect simulations of CMOS micro gas-sensors built on SOI thin membranes

This paper describes coupled-effect simulations of smart micro gas-sensors based on standard BiCMOS technology. The smart sensor features very low power consumption, high sensitivity and potential low fabrication cost achieved through full CMOS integration. For the first time the micro heaters are made of active CMOS elements (i.e. MOSFET transistors) and embedded in a thin SOI membrane consisting of Si and SiO2 thin layers. Micro gas-sensors such as chemoresistive, microcalorimeteric and Pd/polymer gate FET sensors can be made using this technology. Full numerical analyses including 3D electro-thermo-mechanical simulations, in particular stress and deflection studies on the SOI membranes are presented. The transducer circuit design and the post-CMOS fabrication process, which includes single sided back-etching, are also reported.

Enhancing parametric sensitivity using mode localization in electrically coupled mems resonators

We use vibration localization as a sensitive means of detecting small perturbations in stiffness in a pair of weakly coupled micromechanical resonators. For the first time, the variation in the eigenstates is studied by electrostatically coupling nearly identical resonators to allow for stronger localization of vibrational energy due to perturbations in stiffness. Eigenstate variations that are orders of magnitude greater than corresponding shifts in resonant frequency for an induced stiffness perturbation are experimentally demonstrated. Such high, voltagetunable parametric sensitivities together with the added advantage of intrinsic common mode rejection pave the way to a new paradigm of mechanical sensing. ©2009 IEEE.

Controlling magnetic ordering in coupled nanomagnet arrays

We have fabricated using high-resolution electron beam lithography circular magnetic particles (nanomagnets) of diameter 60 nm and thickness 7 nm out of the common magnetic alloy supermalloy. The nanomagnets were arranged on rectangular lattices of different periods. A high-sensitivity magneto-optical method was used to measure the magnetic properties of each lattice. We show experimentally how the magnetic properties of a lattice of nanomagnets can be profoundly changed by the magnetostatic interactions between nanomagnets within the lattice. We find that simply reducing the lattice spacing in one direction from 180 nm down to 80 nm (leaving a gap of only 20 nm between edges) causes the lattice to change from a magnetically disordered state to an ordered state. The change in state is accompanied by a peak in the magnetic susceptibility. We show that this is analogous to the paramagnetic-ferromagnetic phase transition which occurs in conventional magnetic materials, although low-dimensionality and kinetic effects must also be considered.

Synchronous chaos in the coupled system of two logistic maps

Synchronous chaos is investigated in the coupled system of two Logistic maps. Although the diffusive coupling admits all synchronized motions, the stabilities of their configurations are dependent on the transverse Lyapunov exponents while independent of the longitudinal Lyapunov exponents. It is shown that synchronous chaos is structurally stable with respect to the system parameters. The mean motion is the pseudo-orbit of an individual local map so that its dynamics can be described by the local map. (C) 2004 Elsevier Ltd. All rights reserved.