34 resultados para Local productive system


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We explore the application of pseudo time marching schemes, involving either deterministic integration or stochastic filtering, to solve the inverse problem of parameter identification of large dimensional structural systems from partial and noisy measurements of strictly static response. Solutions of such non-linear inverse problems could provide useful local stiffness variations and do not have to confront modeling uncertainties in damping, an important, yet inadequately understood, aspect in dynamic system identification problems. The usual method of least-square solution is through a regularized Gauss-Newton method (GNM) whose results are known to be sensitively dependent on the regularization parameter and data noise intensity. Finite time, recursive integration of the pseudo-dynamical GNM (PD-GNM) update equation addresses the major numerical difficulty associated with the near-zero singular values of the linearized operator and gives results that are not sensitive to the time step of integration. Therefore, we also propose a pseudo-dynamic stochastic filtering approach for the same problem using a parsimonious representation of states and specifically solve the linearized filtering equations through apseudo-dynamic ensemble Kalman filter (PD-EnKF). For multiple sets ofmeasurements involving various load cases, we expedite the speed of the PD-EnKF by proposing an inner iteration within every time step. Results using the pseudo-dynamic strategy obtained through PD-EnKF and recursive integration are compared with those from the conventional GNM, which prove that the PD-EnKF is the best performer showing little sensitivity to process noise covariance and yielding reconstructions with less artifacts even when the ensemble size is small. Copyright (C) 2009 John Wiley & Sons, Ltd.

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We report numerical results for the phase diagram in the density-disorder plane of a hard-sphere system in the presence of quenched, random, pinning disorder. Local minima of a discretized version of the Ramakrishnan-Yussouff free energy functional are located numerically and their relative stability is studied as a function of the density and the strength of disorder. Regions in the phase diagram corresponding to liquid, glassy, and nearly crystalline states are mapped out, and the nature of the transitions is determined. The liquid to glass transition changes from first to second order as the strength of the disorder is increased. For weak disorder, the system undergoes a first-order crystallization transition as the density is increased. Beyond a critical value of the disorder strength, this transition is replaced by a continuous glass transition. Our numerical results are compared with those of analytical work on the same system. Implications of our results for the field-temperature phase diagram of type-II superconductors are discussed.

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Local heating is an important parameter in compaction of thermally sensitive solids since local hot spots could conceivably raise the temperature of the system by several hundred degrees. To understand the importance of local hot spots, 20 g of ammonium perchlorate (AP) and potassium perchlorate (KP) were pressed together at 1500 kg cm−2 for 5 min. The surface structural examination of the compact revealed a secondary phase at the interfaces between the grains in the compositions ranging from 50% AP-50% KP to 10% AP-90% KP. The observation of the secondary phase only at the interfaces has been attributed to the short life times of temperature pulses present during the compaction. An interesting aspect of the investigation is the formation of a series of solid solutions of AP-KP.

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Local texture and microstructure was investigated to study the deformation mechanisms during equal channel angular extrusion of a high purity nickel single crystal of initial cube orientation. A detailed texture and microstructure analysis by various diffraction techniques revealed the complexity of the deformation patterns in different locations of the billet. A modeling approach, taking into account slip system activity, was used to interpret the development of this heterogeneous deformation.

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Time scales associated with activated transitions between glassy metastable states of a free-energy functional appropriate for a dense hard-sphere system are calculated by using a new Monte Carlo method for the local density variables. In particular, we calculate the time the system, initially placed in a shallow glassy minimum of the free-energy, spends in the neighborhood of this minimum before making a transition to the basin of attraction of another free-energy minimum. This time scale is found to increase as the average density is increased. We find a crossover density near which this time scale increases very sharply and becomes longer than the longest times accessible in our simulation. This time scale does not show any evidence of increasing with sample size

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We report here the role of remote sensing (RS) and geographical information system (GIS) in the identification of geomorphic records and understanding of the local controls on the retreat of glaciers of the Baspa Valley, Himachal Pradesh, India. The geomorphic records mapped are accumulation zone, exposed ablation zone, moraine-covered ablation zone, snout, deglaciated valley, lateral moraine, medial moraine, terminal moraine and hanging glacier. Details of these features and stages of deglaciation have been extracted from RS data and mapped in a GIS environment. Glacial geomorphic data have been generated for 22 glaciers of the Baspa Valley. The retreat of glaciers has been estimated using the glacial maxima observed on satellite images. On the basis of percentage of retreat and the critical analysis of glacial geomorphic data for 22 glaciers of the Baspa Valley, they are classified into seven categories of very low to very very high retreat. From the analysis of the above 22 glaciers, it has been found that other than global warming, the retreat of glaciers of the Baspa Valley is inversely proportional to the size of the accumulation zone and the ratio of the moraine covered ablation/exposed ablation zone.

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This paper proposes a derivative-free two-stage extended Kalman filter (2-EKF) especially suited for state and parameter identification of mechanical oscillators under Gaussian white noise. Two sources of modeling uncertainties are considered: (1) errors in linearization, and (2) an inadequate system model. The state vector is presently composed of the original dynamical/parameter states plus the so-called bias states accounting for the unmodeled dynamics. An extended Kalman estimation concept is applied within a framework predicated on explicit and derivative-free local linearizations (DLL) of nonlinear drift terms in the governing stochastic differential equations (SDEs). The original and bias states are estimated by two separate filters; the bias filter improves the estimates of the original states. Measurements are artificially generated by corrupting the numerical solutions of the SDEs with noise through an implicit form of a higher-order linearization. Numerical illustrations are provided for a few single- and multidegree-of-freedom nonlinear oscillators, demonstrating the remarkable promise that 2-EKF holds over its more conventional EKF-based counterparts. DOI: 10.1061/(ASCE)EM.1943-7889.0000255. (C) 2011 American Society of Civil Engineers.

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Seismic hazard and microzonation of cities enable to characterize the potential seismic areas that need to be taken into account when designing new structures or retrofitting the existing ones. Study of seismic hazard and preparation of geotechnical microzonation maps has been attempted using Geographical Information System (GIS). GIS will provide an effective solution for integrating different layers of information thus providing a useful input for city planning and in particular input to earthquake resistant design of structures in an area. Seismic hazard is the study of expected earthquake ground motions at any point on the earth. Microzonation is the process of sub division of region in to number of zones based on the earthquake effects in the local scale. Seismic microzonation is the process of estimating response of soil layers under earthquake excitation and thus the variation of ground motion characteristic on the ground surface. For the seismic microzonation, geotechnical site characterization need to be assessed at local scale (micro level), which is further used to assess of the site response and liquefaction susceptibility of the sites. Seismotectonic atlas of the area having a radius of 350km around Bangalore has been prepared with all the seismogenic sources and historic earthquake events (a catalogue of about 1400 events since 1906). We have attempted to carryout the site characterization of Bangalore by collating conventional geotechnical boreholes data (about 900 borehole data with depth) and integrated in GIS. 3-D subsurface model of Bangalore prepared using GIS is shown in Figure 1.Further, Shear wave velocity survey based on geophysical method at about 60 locations in the city has been carried out in 220 square Kms area. Site response and local site effects have been evaluated using 1-dimensional ground response analysis. Spatial variability of soil overburden depths, ground surface Peak Ground Acceleration’s(PGA), spectral acceleration for different frequencies, liquefaction susceptibility have been mapped in the 220 sq km area using GIS.ArcInfo software has been used for this purpose. These maps can be used for the city planning and risk & vulnerability studies. Figure 2 shows a map of peak ground acceleration at rock level for Bangalore city. Microtremor experiments were jointly carried out with NGRI scientists at about 55 locations in the city and the predominant frequency of the overburden soil columns were evaluated.

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Spatial Decision Support System (SDSS) assist in strategic decision-making activities considering spatial and temporal variables, which help in Regional planning. WEPA is a SDSS designed for assessment of wind potential spatially. A wind energy system transforms the kinetic energy of the wind into mechanical or electrical energy that can be harnessed for practical use. Wind energy can diversify the economies of rural communities, adding to the tax base and providing new types of income. Wind turbines can add a new source of property value in rural areas that have a hard time attracting new industry. Wind speed is extremely important parameter for assessing the amount of energy a wind turbine can convert to electricity: The energy content of the wind varies with the cube (the third power) of the average wind speed. Estimation of the wind power potential for a site is the most important requirement for selecting a site for the installation of a wind electric generator and evaluating projects in economic terms. It is based on data of the wind frequency distribution at the site, which are collected from a meteorological mast consisting of wind anemometer and a wind vane and spatial parameters (like area available for setting up wind farm, landscape, etc.). The wind resource is governed by the climatology of the region concerned and has large variability with reference to space (spatial expanse) and time (season) at any fixed location. Hence the need to conduct wind resource surveys and spatial analysis constitute vital components in programs for exploiting wind energy. SDSS for assessing wind potential of a region / location is designed with user friendly GUI’s (Graphic User Interface) using VB as front end with MS Access database (backend). Validation and pilot testing of WEPA SDSS has been done with the data collected for 45 locations in Karnataka based on primary data at selected locations and data collected from the meteorological observatories of the India Meteorological Department (IMD). Wind energy and its characteristics have been analysed for these locations to generate user-friendly reports and spatial maps. Energy Pattern Factor (EPF) and Power Densities are computed for sites with hourly wind data. With the knowledge of EPF and mean wind speed, mean power density is computed for the locations with only monthly data. Wind energy conversion systems would be most effective in these locations during May to August. The analyses show that coastal and dry arid zones in Karnataka have good wind potential, which if exploited would help local industries, coconut and areca plantations, and agriculture. Pre-monsoon availability of wind energy would help in irrigating these orchards, making wind energy a desirable alternative.

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This paper presents the development of a neural network based power system stabilizer (PSS) designed to enhance the damping characteristics of a practical power system network representing a part of Electricity Generating Authority of Thailand (EGAT) system. The proposed PSS consists of a neuro-identifier and a neuro-controller which have been developed based on functional link network (FLN) model. A recursive on-line training algorithm has been utilized to train the two neural networks. Simulation results have been obtained under various operating conditions and severe disturbance cases which show that the proposed neuro-PSS can provide a better damping to the local as well as interarea modes of oscillations as compared to a conventional PSS

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In this Letter, we examine magnetization in double- and zero-quantum reservoirs of an ensemble of spin-1/2 nuclei and describe their role in determining the sensitivity of a class of separated local field NMR experiments based on Hartmann-Hahn cross-polarization. We observe that for the liquid crystal system studied, a large dilute spin-polarization, obtained initially by the use of adiabatic cross-polarization, can enhance the sensitivity of the above experiment. The signal enhancement factors, however, are found to vary and depend on the local dynamics. The experimental results have been utilized to obtain the local order-parameters of the system. (C) 2012 Elsevier B. V. All rights reserved.

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In steel refining process, an increase of interfacial area between the metal and slag through the metal droplets emulsified into the slag, so-called ``metal emulsion'', is one prevailing view for improving the reaction rate. The formation of metal emulsion was experimentally evaluated using Al-Cu alloy as metal phase and chloride salt as slag phase under the bottom bubbling condition. Samples were collected from the center of the salt phase in the container. Large number of metal droplets were separated from the salt by dissolving it into water. The number, surface area, and weight of the droplets increased with the gas flow rate and have local maximum values. The formation and sedimentation rates of metal droplets were estimated using a mathematical model. The formation rate increased with the gas flow rate and has a local maximum value as a function of gas flow rate, while the sedimentation rate is independent of the gas flow rate under the bottom bubbling condition. Three types of formation mode of metal emulsion, which occurred by the rupture of metal film around the bubble, were observed using high speed camera. During the process, an elongated column covered with metal film was observed with the increasing gas flow rate. This elongated column sometimes reached to the top surface of the salt phase. In this case, it is considered that fine droplets were not formed and in consequence, the weight of metal emulsion decreased at higher gas flow rate.

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Linear quadratic stabilizers are well-known for their superior control capabilities when compared to the conventional lead-lag power system stabilizers. However, they have not seen much of practical importance as the state variables are generally not measurable; especially the generator rotor angle measurement is not available in most of the power plants. Full state feedback controllers require feedback of other machine states in a multi-machine power system and necessitate block diagonal structure constraints for decentralized implementation. This paper investigates the design of Linear Quadratic Power System Stabilizers using a recently proposed modified Heffron-Phillip's model. This model is derived by taking the secondary bus voltage of the step-up transformer as reference instead of the infinite bus. The state variables of this model can be obtained by local measurements. This model allows a coordinated linear quadratic control design in multi machine systems. The performance of the proposed controller has been evaluated on two widely used multi-machine power systems, 4 generator 10 bus and 10 generator 39 bus systems. It has been observed that the performance of the proposed controller is superior to that of the conventional Power System Stabilizers (PSS) over a wide range of operating and system conditions.

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Ubiquitous Computing is an emerging paradigm which facilitates user to access preferred services, wherever they are, whenever they want, and the way they need, with zero administration. While moving from one place to another the user does not need to specify and configure their surrounding environment, the system initiates necessary adaptation by itself to cope up with the changing environment. In this paper we propose a system to provide context-aware ubiquitous multimedia services, without user’s intervention. We analyze the context of the user based on weights, identify the UMMS (Ubiquitous Multimedia Service) based on the collected context information and user profile, search for the optimal server to provide the required service, then adapts the service according to user’s local environment and preferences, etc. The experiment conducted several times with different context parameters, their weights and various preferences for a user. The results are quite encouraging.

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In this paper we present an approach to build a prototype. model of a first-responder localization system intended for disaster relief operations. This system is useful to monitor and track the positions of the first-responders in an indoor environment, where GPS is not available. Each member of the first responder team is equipped with two zero-velocity-update-aided inertial navigation systems, one on each foot, a camera mounted on a helmet, and a processing platform strapped around the waist of the first responder, which fuses the data from the different sensors. The fusion algorithm runs real-time on the processing platform. The video is also processed using the DSP core of the computing machine. The processed data consisting of position, velocity, heading information along with video streams is transmitted to the command and control system via a local infrastructure WiFi network. A centralized cooperative localization algorithm, utilizing the information from Ultra Wideband based inter-agent ranging devices combined with the position estimates and uncertainties of each first responder, has also been implemented.