999 resultados para Aerospace engineering|Electrical engineering


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An approximate dynamic programming (ADP)-based suboptimal neurocontroller to obtain desired temperature for a high-speed aerospace vehicle is synthesized in this paper. A I-D distributed parameter model of a fin is developed from basic thermal physics principles. "Snapshot" solutions of the dynamics are generated with a simple dynamic inversion-based feedback controller. Empirical basis functions are designed using the "proper orthogonal decomposition" (POD) technique and the snapshot solutions. A low-order nonlinear lumped parameter system to characterize the infinite dimensional system is obtained by carrying out a Galerkin projection. An ADP-based neurocontroller with a dual heuristic programming (DHP) formulation is obtained with a single-network-adaptive-critic (SNAC) controller for this approximate nonlinear model. Actual control in the original domain is calculated with the same POD basis functions through a reverse mapping. Further contribution of this paper includes development of an online robust neurocontroller to account for unmodeled dynamics and parametric uncertainties inherent in such a complex dynamic system. A neural network (NN) weight update rule that guarantees boundedness of the weights and relaxes the need for persistence of excitation (PE) condition is presented. Simulation studies show that in a fairly extensive but compact domain, any desired temperature profile can be achieved starting from any initial temperature profile. Therefore, the ADP and NN-based controllers appear to have the potential to become controller synthesis tools for nonlinear distributed parameter systems.

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Computer simulations have shown a novel geodesic splitting on the paraboloid of revolution leading to a multiplicity of surface ray paths. Such a phenomenon would have wide ramifications for wave propagation problems in general, besides applications in target-detection problems and the computational requirements of ray-theoretic formulations such as the UTD, in computing the antenna characteristics in the high-frequency domain.

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Closed form solutions for a simultaneously AM and high-harmonic FM mode locked laser system is presented. Analytical expressions for the pulsewidth and pulsewidth-bandwidth products are derived in terms of the system parameters. The analysis predicts production of 17 ps duration pulses in a Nd:YAG laser mode locked with AM and FM modulators driven at 80 MHz and 1.76 GHz for 1 W modulator input power. The predicted values of the pulsewidth-bandwidth product lie between the values corresponding to the pure AM and FM mode locking values.

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The effect of various parameters on the velocity of the induced jet produced by a dielectric barrier discharge (DBD) plasma was studied experimentally. The glow discharge was created at atmospheric conditions by using a high voltage RF power supply. Flow visualization and photographic studies of the plasma were performed. The parametric investigation of the characteristics of the plasma show that the width of the plasma in the uniform glow discharge regime was an indication of the velocity induced under stagnant conditions. It was observed that the spanwise overlap of the two electrodes, dielectric thickness, voltage and frequency of the applied voltage are the major parameters that govern the velocity and the extent of plasma in the streamwise direction.

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Acoustic Emission (AE) signals, which are electrical version of acoustic emissions, are usually analysed using a set of signal parameters. The major objective of signal analysis is to study the characteristics of the sources of emissions. Peak amplitude (P-a) and rise time (R-t) are two such parameters used for source characterization. In this paper, we theoretically investigate the efficiency of P-a and R-t to classify and characterize AE sources by modelling the input stress pulse and transducer. Analytical expressions obtained for P-a and R-t clearly indicate their use and efficiency for source characterization. It is believed that these results may be of use to investigators in areas like control systems and signal processing also.

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Application of piezoceramic materials in actuation and sensing of vibration is of current interest. Potential and more popular applications of piezoceramics are probably in the field of active vibration control. However, the objective of this work is to investigate the effect of shunted piezoceramics as passive vibration control devices when bonded to a host structure. Resistive shunting of a piezoceramic bonded to a cantilevered duralumin beam has been investigated. The piezoceramic is connected in parallel to an electrical network comprising of resistors and inductors. The piezoceramic is a capacitor that stores and discharges electrical energy that is transformed from the mechanical motion of the structure to which it is bonded. A resistor across the piezoceramic would be termed as a resistively shunted piezoceramic. Similarly, an inductor across the piezoceramic is termed as a resonantly shunted piezoceramic. In this study, the effect of resistive shunting on the nature of damping enhancement to the host structure has been investigated. Analytical studies are presented along with experimental results.

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The effect of the test gas on the flow field around a 120degrees apex angle blunt cone has been investigated in a shock tunnel at a nominal Mach number of 5.75. The shock standoff distance around the blunt cone was measured by an electrical discharge technique using both carbon dioxide and air as test gases. The forebody laminar convective heat transfer to the blunt cone was measured with platinum thin-film sensors in both air and carbon dioxide environments. An increase of 10 to 15% in the measured heat transfer values was observed with carbon dioxide as the test gas in comparison to air. The measured thickness of the shock layer along the stagnation streamline was 3.57 +/- 0.17 mm in air and 3.29 +/- 0.26 mm in carbon dioxide. The computed thickness of the shock layer for air and carbon dioxide were 3.98 mm and 3.02 mm, respectively. The observed increase in the measured heat transfer rates in carbon dioxide compared to air was due to the higher density ratio across the bow shock wave and the reduced shock layer thickness.

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A set of finite elements (FEs) is formulated to analyze wave propagation through inhomogeneous material when subjected to mechanical, thermal loading or piezo-electric actuation. Elastic, thermal and electrical properties of the materials axe allowed to vary in length and thickness direction. The elements can act both as sensors and actuators. These elements are used to model wave propagation in functionally graded materials (FGM) and the effect of inhomogeneity in the wave is demonstrated. Further, a surface acoustic wave (SAW) device is modeled and wave propagation due to piezo-electric actuation from interdigital transducers (IDTs) is studied.

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Ionic polymer-metal composites (IPMC), piezoelectric polymer composites and nematic elastomer composites are materials, which exhibit characteristics of both sensors and actuators. Large deformation and curvature are observed in these systems when electric potential is applied. Effects of geometric non-linearity due to the chargeinduced motion in these materials are poorly understood. In this paper, a coupled model for understanding the behavior of an ionic polymer beam undergoing large deformation and large curvature is presented. Maxwell's equations and charge transport equations are considered which couple the distribution of the ion concentration and the pressure gradient along length of a cantilever beam with interdigital electrodes. A nonlinear constitutive model is derived accounting for the visco-elasto-plastic behavior of these polymers and based on the hypothesis that the presence of electrical charge stretches/contracts bonds, which give rise to electrical field dependent softening/hardening. Polymer chain orientation in statistical sense plays a role on such softening or hardening. Elementary beam kinematics with large curvature is considered. A model for understanding the deformation due to electrostatic repulsion between asymmetrical charge distributions across the cross-sections is presented. Experimental evidence that Silver(Ag) nanoparticle coated IPMCs can be used for energy harvesting is reported. An IPMC strip is vibrated in different environments and the electric power against a resistive load is measured. The electrical power generated was observed to vary with the environment with maximum power being generated when the strip is in wet state. IPMC based energy harvesting systems have potential applications in tidal wave energy harvesting, residual environmental energy harvesting to power MEMS and NEMS devices.

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The paper reports the operational experience from a 100 kWe gasification power plant connected to the grid in Karnataka. Biomass Energy for Rural India (BERI) is a program that implemented gasification based power generation with an installed capacity of 0.88 MWe distributed over three locations to meet the electrical energy needs in the district of Tumkur. The operation of one 100 kWe power plant was found unsatisfactory and not meeting the designed performance. The Indian Institute of Science, Bangalore, the technology developer, took the initiative to ensure the system operation, capacity building and prove the designed performance. The power plant connected to the grid consists of the IISc gasification system which includes reactor, cooling, cleaning system, fuel drier and water treatment system to meet the producer gas quality for an engine. The producer gas is used as a fuel in Cummins India Limited, GTA 855 G model, turbo charged engine and the power output is connected to the grid. The system has operated for over 1000 continuous hours, with only about 70 h of grid outages. The total biomass consumption for 1035 h of operation was 111 t at an average of 107 kg/h. Total energy generated was 80.6 MWh reducing over loot of CO(2) emissions. The overall specific fuel consumption was about 1.36 kg/kWh, amounting to an overall efficiency from biomass to electricity of about 18%. The present operations indicate that a maintenance schedule for the plant can be at the end of 1000 h. The results for another 1000 h of operation by the local team are also presented. (C) 2011 International Energy Initiative. Published by Elsevier Inc. All rights reserved.

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This paper presents hierarchical clustering algorithms for land cover mapping problem using multi-spectral satellite images. In unsupervised techniques, the automatic generation of number of clusters and its centers for a huge database is not exploited to their full potential. Hence, a hierarchical clustering algorithm that uses splitting and merging techniques is proposed. Initially, the splitting method is used to search for the best possible number of clusters and its centers using Mean Shift Clustering (MSC), Niche Particle Swarm Optimization (NPSO) and Glowworm Swarm Optimization (GSO). Using these clusters and its centers, the merging method is used to group the data points based on a parametric method (k-means algorithm). A performance comparison of the proposed hierarchical clustering algorithms (MSC, NPSO and GSO) is presented using two typical multi-spectral satellite images - Landsat 7 thematic mapper and QuickBird. From the results obtained, we conclude that the proposed GSO based hierarchical clustering algorithm is more accurate and robust.

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This paper presents an improved hierarchical clustering algorithm for land cover mapping problem using quasi-random distribution. Initially, Niche Particle Swarm Optimization (NPSO) with pseudo/quasi-random distribution is used for splitting the data into number of cluster centers by satisfying Bayesian Information Criteria (BIC). Themain objective is to search and locate the best possible number of cluster and its centers. NPSO which highly depends on the initial distribution of particles in search space is not been exploited to its full potential. In this study, we have compared more uniformly distributed quasi-random with pseudo-random distribution with NPSO for splitting data set. Here to generate quasi-random distribution, Faure method has been used. Performance of previously proposed methods namely K-means, Mean Shift Clustering (MSC) and NPSO with pseudo-random is compared with the proposed approach - NPSO with quasi distribution(Faure). These algorithms are used on synthetic data set and multi-spectral satellite image (Landsat 7 thematic mapper). From the result obtained we conclude that use of quasi-random sequence with NPSO for hierarchical clustering algorithm results in a more accurate data classification.

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This brief discusses the convergence analysis of proportional navigation (PN) guidance law in the presence of delayed line-of-sight (LOS) rate information. The delay in the LOS rate is introduced by the missile guidance system that uses a low cost sensor to obtain LOS rate information by image processing techniques. A Lyapunov-like function is used to analyze the convergence of the delay differential equation (DDE) governing the evolution of the LOS rate. The time-to-go until which decreasing behaviour of the Lyapunov-like function can be guaranteed is obtained. Conditions on the delay for finite time convergence of the LOS rate are presented for the linearized engagement equation. It is observed that in the presence of line-of-sight rate delay, increasing the effective navigation constant of the PN guidance law deteriorates its performance. Numerical simulations are presented to validate the results.

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The presence of a large number of spectral bands in the hyperspectral images increases the capability to distinguish between various physical structures. However, they suffer from the high dimensionality of the data. Hence, the processing of hyperspectral images is applied in two stages: dimensionality reduction and unsupervised classification techniques. The high dimensionality of the data has been reduced with the help of Principal Component Analysis (PCA). The selected dimensions are classified using Niche Hierarchical Artificial Immune System (NHAIS). The NHAIS combines the splitting method to search for the optimal cluster centers using niching procedure and the merging method is used to group the data points based on majority voting. Results are presented for two hyperspectral images namely EO-1 Hyperion image and Indian pines image. A performance comparison of this proposed hierarchical clustering algorithm with the earlier three unsupervised algorithms is presented. From the results obtained, we deduce that the NHAIS is efficient.

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A new technique is proposed for multisensor image registration by matching the features using discrete particle swarm optimization (DPSO). The feature points are first extracted from the reference and sensed image using improved Harris corner detector available in the literature. From the extracted corner points, DPSO finds the three corresponding points in the sensed and reference images using multiobjective optimization of distance and angle conditions through objective switching technique. By this, the global best matched points are obtained which are used to evaluate the affine transformation for the sensed image. The performance of the image registration is evaluated and concluded that the proposed approach is efficient.