44 resultados para Hybrid method


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Nanoporous anatase with a thin interconnected filmlike morphology has been synthesized in a single step by coupling a nonhydrolytic condensation reaction of a Ti precursor with a hybrid sol-gel combustion reaction. The method combines the advantages of a conventional sol-gel method for the formation of porous structures with the high crystallinity of the products obtained by combustion methods to yield highly crystalline, phase-pure nanoporous anatase. The generation of pores is initiated by the formation of reverse micelles in a polymeric polycondensation product, which expand during heating, leading to larger pores. A reaction scheme involving a complex formation and nonhydrolytic polycondensation reaction with ester elimination leads to the formation of ail extended Ti-O-Ti network. The effect of process parameters, such as temperature and relative ratio of cosurfactants, on phase formation has been studied. The possibility of band gap engineering by controlled doping during synthesis and the possibility of attachment of molecular/nanoparticle sensitizers provide opportunities for easy preparation of photoanodes for solar cell applications.

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A generalized technique is proposed for modeling the effects of process variations on dynamic power by directly relating the variations in process parameters to variations in dynamic power of a digital circuit. The dynamic power of a 2-input NAND gate is characterized by mixed-mode simulations, to be used as a library element for 65mn gate length technology. The proposed methodology is demonstrated with a multiplier circuit built using the NAND gate library, by characterizing its dynamic power through Monte Carlo analysis. The statistical technique of Response. Surface Methodology (RSM) using Design of Experiments (DOE) and Least Squares Method (LSM), are employed to generate a "hybrid model" for gate power to account for simultaneous variations in multiple process parameters. We demonstrate that our hybrid model based statistical design approach results in considerable savings in the power budget of low power CMOS designs with an error of less than 1%, with significant reductions in uncertainty by atleast 6X on a normalized basis, against worst case design.

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Classification of large datasets is a challenging task in Data Mining. In the current work, we propose a novel method that compresses the data and classifies the test data directly in its compressed form. The work forms a hybrid learning approach integrating the activities of data abstraction, frequent item generation, compression, classification and use of rough sets.

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Classification of large datasets is a challenging task in Data Mining. In the current work, we propose a novel method that compresses the data and classifies the test data directly in its compressed form. The work forms a hybrid learning approach integrating the activities of data abstraction, frequent item generation, compression, classification and use of rough sets.

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Hybrid elements, which are based on a two-field variational formulation with the displacements and stresses interpolated separately, are known to deliver very high accuracy, and to alleviate to a large extent problems of locking that plague standard displacement-based formulations. The choice of the stress interpolation functions is of course critical in ensuring the high accuracy and robustness of the method. Generally, an attempt is made to keep the stress interpolation to the minimum number of terms that will ensure that the stiffness matrix has no spurious zero-energy modes, since it is known that the stiffness increases with the increase in the number of terms. Although using such a strategy of keeping the number of interpolation terms to a minimum works very well in static problems, it results either in instabilities or fails to converge in transient problems. This is because choosing the stress interpolation functions merely on the basis of removing spurious energy modes can violate some basic principles that interpolation functions should obey. In this work, we address the issue of choosing the interpolation functions based on such basic principles of interpolation theory and mechanics. Although this procedure results in the use of more number of terms than the minimum (and hence in slightly increased stiffness) in many elements, we show that the performance continues to be far superior to displacement-based formulations, and, more importantly, that it also results in considerably increased robustness.

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The element-based piecewise smooth functional approximation in the conventional finite element method (FEM) results in discontinuous first and higher order derivatives across element boundaries Despite the significant advantages of the FEM in modelling complicated geometries, a motivation in developing mesh-free methods has been the ease with which higher order globally smooth shape functions can be derived via the reproduction of polynomials There is thus a case for combining these advantages in a so-called hybrid scheme or a `smooth FEM' that, whilst retaining the popular mesh-based discretization, obtains shape functions with uniform C-p (p >= 1) continuity One such recent attempt, a NURBS based parametric bridging method (Shaw et al 2008b), uses polynomial reproducing, tensor-product non-uniform rational B-splines (NURBS) over a typical FE mesh and relies upon a (possibly piecewise) bijective geometric map between the physical domain and a rectangular (cuboidal) parametric domain The present work aims at a significant extension and improvement of this concept by replacing NURBS with DMS-splines (say, of degree n > 0) that are defined over triangles and provide Cn-1 continuity across the triangle edges This relieves the need for a geometric map that could precipitate ill-conditioning of the discretized equations Delaunay triangulation is used to discretize the physical domain and shape functions are constructed via the polynomial reproduction condition, which quite remarkably relieves the solution of its sensitive dependence on the selected knotsets Derivatives of shape functions are also constructed based on the principle of reproduction of derivatives of polynomials (Shaw and Roy 2008a) Within the present scheme, the triangles also serve as background integration cells in weak formulations thereby overcoming non-conformability issues Numerical examples involving the evaluation of derivatives of targeted functions up to the fourth order and applications of the method to a few boundary value problems of general interest in solid mechanics over (non-simply connected) bounded domains in 2D are presented towards the end of the paper

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A holographic optical element (HOE) based single-mode hybrid fiber optic interferometer for realizing the zero-order fringe is described. The HOE proposed and used integrates the actions of a beam combiner and a lens, and endows the interferometer with high tolerance for repositioning errors. The proposed method is simple and offers advantages such as the elimination of in situ processing for the hologram.

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This paper proposes a hybrid solar cooking system where the solar energy is brought to the kitchen. The energy source is a combination of the solar thermal energy and the Liquefied Petroleum Gas (LPG) that is in common use in kitchens. The solar thermal energy is transferred to the kitchen by means of a circulating fluid. The transfer of solar heat is a twofold process wherein the energy from the collector is transferred first to an intermediate energy storage buffer and the energy is subsequently transferred from the buffer to the cooking load. There are three parameters that are controlled in order to maximize the energy transfer from the collector to the load viz, the fluid flow rate from collector to buffer, fluid flow rate from buffer to load and the diameter of the pipes. This is a complex multi energy domain system comprising energy flow across several domains such as thermal, electrical and hydraulic. The entire system is modeled using the bond graph approach with seamless integration of the power flow in these domains. A method to estimate different parameters of the practical cooking system is also explained. Design and life cycle costing of the system is also discussed. The modeled system is simulated and the results are validated experimentally. (C) 2010 Elsevier Ltd. All rights reserved.

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An angle invariance property based on Hertz's principle of particle dynamics is employed to facilitate the surface-ray tracing on nondevelopable hybrid quadric surfaces of revolution (h-QUASOR's). This property, when used in conjunction with a Geodesic Constant Method, yields analytical expressions for all the ray-parameters required in the UTD formulation. Differential geometrical considerations require that some of the ray-parameters (defined heuristically in the UTD for the canonical convex surfaces) be modified before the UTD can be applied to such hybrid surfaces. Mutual coupling results for finite-dimensional slots have been presented as an example on a satellite launch vehicle modeled by general paraboloid of revolution and right circular cylinder.

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Vibration and buckling of curved plates, made of hybrid laminated composite materials, are studied using first-order shear deformation theory and Reissner's shallow shell theory. For an initial study, only simply-supported boundary conditions are considered. The natural frequencies and critical buckling loads are calculated using the energy method (Lagrangian approach) by assuming a combination of sine and cosine functions in the form of double Fourier series. The effects of curvature, aspect ratio, stacking sequence and ply-orientation are studied. The non-dimensional frequencies and critical buckling load of a hybrid laminate lie in between the values for laminates made of all plies of higher strength and lower strength fibres. Curvature enhances natural frequencies and it is more predominant for a thin panel than a thick one.

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A study of environmental chloride and groundwater balance has been carried out in order to estimate their relative value for measuring average groundwater recharge under a humid climatic environment with a relatively shallow water table. The hybrid water fluctuation method allowed the split of the hydrologic year into two seasons of recharge (wet season) and no recharge (dry season) to appraise specific yield during the dry season and, second, to estimate recharge from the water table rise during the wet season. This well elaborated and suitable method has then been used as a standard to assess the effectiveness of the chloride method under forest humid climatic environment. Effective specific yield of 0.08 was obtained for the study area. It reflects an effective basin-wide process and is insensitive to local heterogeneities in the aquifer system. The hybrid water fluctuation method gives an average recharge value of 87.14 mm/year at the basin scale, which represents 5.7% of the annual rainfall. Recharge value estimated based on the chloride method varies between 16.24 and 236.95 mm/year with an average value of 108.45 mm/year. It represents 7% of the mean annual precipitation. The discrepancy observed between recharge value estimated by the hybrid water fluctuation and the chloride mass balance methods appears to be very important, which could imply the ineffectiveness of the chloride mass balance method for this present humid environment.

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Applications in various domains often lead to very large and frequently high-dimensional data. Successful algorithms must avoid the curse of dimensionality but at the same time should be computationally efficient. Finding useful patterns in large datasets has attracted considerable interest recently. The primary goal of the paper is to implement an efficient Hybrid Tree based clustering method based on CF-Tree and KD-Tree, and combine the clustering methods with KNN-Classification. The implementation of the algorithm involves many issues like good accuracy, less space and less time. We will evaluate the time and space efficiency, data input order sensitivity, and clustering quality through several experiments.

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Combining the newly developed nonlinear model predictive static programming technique with null range direction concept, a novel explicit energy-insensitive guidance design method is presented in this paper for long range flight vehicles, which leads to a closed form solution of the necessary guidance command update. Owing to the closed form nature, it does not lead to computational difficulties and the proposed optimal guidance algorithm can be implemented online. The guidance law is verified in a solid motor propelled long range flight vehicle, for which coming up with an effective guidance law is more difficult as compared to a liquid engine propelled vehicle (mainly because of the absence of thrust cutoff facility). Assuming the starting point of the second stage to be a deterministic point beyond the atmosphere, the scheme guides the vehicle properly so that it completes the mission within a tight error bound. The simulation results demonstrate its ability to intercept the target, even with an uncertainty of greater than 10% in burnout time.

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This letter proposes the combination of a passive muffler and an active noise control system for the control of very high‐level noise in ducts used with large industrial fans and similar equipment. The analysis of such a hybrid system is presented making use of electroacoustic analogies and the transfer matrix method. It turns out that a passive muffler upstream of the input microphone can indeed lower the acoustic pressure and, hence, the power requirement of the auxiliary source. The parameter that needs to be optimized (or maximized) for this purpose is a certain velocity ratio that can readily be evaluated in a closed form, making it more or less straightforward to synthesize the configuration of an effective passive muffler to go with the active noise control system.

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A hybrid simulation technique for identification and steady state optimization of a tubular reactor used in ammonia synthesis is presented. The parameter identification program finds the catalyst activity factor and certain heat transfer coefficients that minimize the sum of squares of deviation from simulated and actual temperature measurements obtained from an operating plant. The optimization program finds the values of three flows to the reactor to maximize the ammonia yield using the estimated parameter values. Powell's direct method of optimization is used in both cases. The results obtained here are compared with the plant data.