122 resultados para Multi-phase structures

em Indian Institute of Science - Bangalore - Índia


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For hybrid electric vehicles the batteries and the drive dc-link may be at different voltages. The batteries are at low voltage to obtain higher volumetric efficiencies and the dc-link is at higher voltage to have higher efficiency on the motor side. Therefore a power interface between the batteries and the drive's dc-link is essential. This power interface should handle power flow from battery to motor, motor to battery, external genset to battery and grid to battery. This paper proposes a multi power port topology which is capable of handling multiple power sources and still maintains simplicity and features like obtaining any gain, wide load variations, lower output current ripple and capability of parallel battery energy due to the modular structure. The development and testing of a bi-directional fly-back DC-DC converter for hybrid electric vehicle is described in this paper. Simple hysteresis voltage control is used for DC link voltage regulation. The experimental results are presented to show the working of the proposed converter.

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A multi phase, delay-locked loop (DLL) based frequency synthesizer is designed for harmonic rejection mixing in reconfigurable radios. This frequency synthesizer uses a 1 GHz input reference frequency, and achieves <= 20ns settling time by utilizing a wide loop bandwidth. The circuit has been designed in 0.13-mu m CMOS technology. It is designed for a frequency range of 500 MHz to 3 GHz with stuck/harmonic lock removal assist. Index Terms-stuck lock, harmonic lock, delay-locked loops, multi phase, phase detector, frequency synthesis

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For maximizing influence spread in a social network, given a certain budget on the number of seed nodes, we investigate the effects of selecting and activating the seed nodes in multiple phases. In particular, we formulate an appropriate objective function for two-phase influence maximization under the independent cascade model, investigate its properties, and propose algorithms for determining the seed nodes in the two phases. We also study the problem of determining an optimal budget-split and delay between the two phases.

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As computational Grids are increasingly used for executing long running multi-phase parallel applications, it is important to develop efficient rescheduling frameworks that adapt application execution in response to resource and application dynamics. In this paper, three strategies or algorithms have been developed for deciding when and where to reschedule parallel applications that execute on multi-cluster Grids. The algorithms derive rescheduling plans that consist of potential points in application execution for rescheduling and schedules of resources for application execution between two consecutive rescheduling points. Using large number of simulations, it is shown that the rescheduling plans developed by the algorithms can lead to large decrease in application execution times when compared to executions without rescheduling on dynamic Grid resources. The rescheduling plans generated by the algorithms are also shown to be competitive when compared to the near-optimal plans generated by brute-force methods. Of the algorithms, genetic algorithm yielded the most efficient rescheduling plans with 9-12% smaller average execution times than the other algorithms.

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Eutectic growth is an interesting example for exploring the topic of pattern-formation in multi-phase systems, where the growth of the phases is coupled with the diffusive transport of one or more components in the melt. While in the case of binary alloys, the number of possibilities are limited (lamellae, rods, labyrinth etc.), their number rapidly increases with the number of components and phases. In this paper, we will investigate pattern formation during three-phase eutectic solidification using a state-of-the art phase-field method based on the grand-canonical density formulation. The major aim of the study is to highlight the role of two properties, which are the volume fraction of the solid phases and the solid-liquid interfacial energies, in the self-organization of the solid phases during directional growth. Thereafter, we will show representative phase-field simulations of a micro-structure in a real alloy (Ag-Al-Cu) using an asymmetric phase diagram as well as interfacial properties.

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We report Extended X-ray Absorption Fine Structure and anelastic spectroscopy measurements on on hole doped manganese oxides La1-xCaxMnO3 which present the colossal magnetoresistance effect. EXAFS measurements were realized both in the absence and presence of an applied magnetic field of 1.1 Tesla, in a wide temperature range (between 330 and 77 K) and at various dopings (x = 0.25 and x = 0.33). The magnetic field orders the magnetic moments so favouring the electron mobility and the reduction of Mn-O octahedra distortions. We observe the presence of four short and two long Mn-O distances (1.93 and 2.05 Angstrom respectively) above and also below the metal-insulator phase transition. The overall distortion decreases but does not completely disappear in the metallic phase suggesting the possible coexistence of metallic and insulating regions at low temperatures. The magnetic field reduces the lattice distortions showing evidence of a microscopic counterpart of the macroscopic colossal magnetoresistance. We also present preliminary anelastic relaxation spectra in a wide temperature range from 900 K to 1 K on a sample with x = 0.40, in order to study the structural phase transitions and the lattice dynamics. A double peak has been observed at the metal-insulator transition in the imaginary part of Young's modulus. This double peak indicates that the metal-insulator transition could be a more complex phenomenon than a simple second order phase transition. In particular the peak at lower temperatures can be connected with the possible presence of inhomogeneous phase structures. Another intense dissipation peak has been observed corresponding to the structural orthorhombic-trigonal transition around 750 K.

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This research is focused on understanding the role of microstructural variables and processing parameters in obtaining optimised dual phase structures in medium carbon low alloy steels. Tempered Martensite structures produced at 300, 500, and 650 degrees C, were cold rolled to varied degrees ranging from 20 to 80% deformation. Intercritical annealing was then performed at 740, 760, and 780 degrees C for various time duration ranging from 60 seconds to 60 minutes before quenching in water. The transformation behaviour was studied with the aid of optical microscopy and hardness curves. From the results, it is observed that microstructural condition, deformation, and intercritical temperatures influenced the chronological order of the competing stress relaxation and decomposition phase reactions which interfered with the rate of the expected alpha -> gamma transformation. The three unique transformation trends observed are systematically analyzed. It was also observed that the 300 and 500 degrees C tempered initial microstructures were unsuitable for the production of dual structures with optimized strength characteristics.

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DNA is the chemotherapeutic target for treating diseases of genetic origin. Besides well-known double-helical structures (A, B, Z, parallel stranded-DNA etc.), DNA is capable of forming several multi-stranded structures (triplex, tetraplex, i-motif etc.) which have unique biological significance. The G-rich 3'-ends of chromosomes, called telomeres, are synthesized by telomerase, a ribonucleoprotein, and over-expression of telomerase is associated with cancer. The activity of telomerase is suppressed if the G-rich region is folded into the four stranded structures, called G-quadruplexes (G4-DNAs) using small synthetic ligands. Thus design and synthesis of new G4-DNA ligands is an attractive strategy to combat cancer. G4-DNA forming sequences are also prevalent in other genomic regions of biological significance including promoter regions of several oncogenes. Effective gene regulation may be achieved by inducing a G4-DNA structure within the G-rich promoter sequences. To date, several G4-DNA stabilizing ligands are known. DNA groove binders interact with the duplex B-DNA through the grooves (major and minor groove) in a sequence-specific manner. Some of the groove binders are known to stabilize the G4-DNA. However, this is a relatively under explored field of research. In this review, we focus on the recent advances in the understanding of the G4-DNA structures, particularly made from the human telomeric DNA stretches. We summarize the results of various investigations of the interaction of various organic ligands with the G4-DNA while highlighting the importance of groove binder-G4-DNA interactions.

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The use of copolymer and polymer blends widened the possibility of creating materials with multilayered architectures. Hierarchical polymer systems with a wide array of micro and nanostructures are generated by thermally induced phase separation (TIPS) in partially miscible polymer blends. Various parameters like the interaction between the polymers, concentration, solvent/non-solvent ratio, and quenching temperature have to be optimized to obtain these micro/nanophase structures. Alternatively, the addition of nanoparticles is another strategy to design materials with desired hetero-phase structures. The dynamics of the polymer nanocomposite depends on the statistical ordering of polymers around the nanoparticle, which is dependent on the shape of the nanoparticle. The entropic loss due to deformation of polymer chains, like the repulsive interactions due to coiling and the attractive interactions in the case of swelling has been highlighted in this perspective article. The dissipative particle dynamics has been discussed and is correlated with the molecular dynamics simulation in the case of polymer blends. The Cahn Hillard Cook model on variedly shaped immobile fillers has shown difference in the propagation of the composition wave. The nanoparticle shape has a contributing effect on the polymer particle interaction, which can change the miscibility window in the case of these phase separating polymer blends. Quantitative information on the effect of spherical particles on the demixing temperature is well established and further modified to explain the percolation of rod shaped particles in the polymer blends. These models correlate well with the experimental observations in context to the dynamics induced by the nanoparticle in the demixing behavior of the polymer blend. The miscibility of the LCST polymer blend depends on the enthalpic factors like the specific interaction between the components, and the solubility product and the entropic losses occurring due to the formation of any favorable interactions. Hence, it is essential to assess the entropic and enthalpic interactions induced by the nanoparticles independently. The addition of nanoparticles creates heterogeneity in the polymer phase it is localized. This can be observed as an alteration in the relaxation behavior of the polymer. This changes the demixing behavior and the interaction parameter between the polymers. The compositional changes induced due to the incorporation of nanoparticles are also attributed as a reason for the altered demixing temperature. The particle shape anisotropy causes a direction dependent depletion, which changes the phase behavior of the blend. The polymer-grafted nanoparticles with varying grafting density show tremendous variation in the miscibility of the blend. The stretching of the polymer chains grafted on the nanoparticles causes an entropy penalty in the polymer blend. A comparative study on the different shaped particles is not available up to date for understanding these aspects. Hence, we have juxtaposed the various computational studies on nanoparticle dynamics, the shape effect of NPs on homopolymers and also the cases of various polymer blends without nanoparticles to sketch a complete picture on the effect of various particles on the miscibility of LCST blends.

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The detailed electronic structure of the n-v addition compound H2O·BF3 has been investigated for the first time by a combined use of electron energy loss spectroscopy (EELS) and UV photoelectron spectroscopy (UPS) augmented by MO calculations. The calculated molecular orbital energies of H2O·BF3 agree well with the UPS results and have been used to assign the electronic transitions obtained from EELS and to construct an orbital correlation diagram. The Journal of Chemical Physics is copyrighted by The American Institute of Physics.

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We present a new, generic method/model for multi-objective design optimization of laminated composite components using a novel multi-objective optimization algorithm developed on the basis of the Quantum behaved Particle Swarm Optimization (QPSO) paradigm. QPSO is a co-variant of the popular Particle Swarm Optimization (PSO) and has been developed and implemented successfully for the multi-objective design optimization of composites. The problem is formulated with multiple objectives of minimizing weight and the total cost of the composite component to achieve a specified strength. The primary optimization variables are - the number of layers, its stacking sequence (the orientation of the layers) and thickness of each layer. The classical lamination theory is utilized to determine the stresses in the component and the design is evaluated based on three failure criteria; Failure Mechanism based Failure criteria, Maximum stress failure criteria and the Tsai-Wu Failure criteria. The optimization method is validated for a number of different loading configurations - uniaxial, biaxial and bending loads. The design optimization has been carried for both variable stacking sequences as well as fixed standard stacking schemes and a comparative study of the different design configurations evolved has been presented. Also, the performance of QPSO is compared with the conventional PSO.

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We present a generic method/model for multi-objective design optimization of laminated composite components, based on vector evaluated particle swarm optimization (VEPSO) algorithm. VEPSO is a novel, co-evolutionary multi-objective variant of the popular particle swarm optimization algorithm (PSO). In the current work a modified version of VEPSO algorithm for discrete variables has been developed and implemented successfully for the, multi-objective design optimization of composites. The problem is formulated with multiple objectives of minimizing weight and the total cost of the composite component to achieve a specified strength. The primary optimization variables are - the number of layers, its stacking sequence (the orientation of the layers) and thickness of each layer. The classical lamination theory is utilized to determine the stresses in the component and the design is evaluated based on three failure criteria; failure mechanism based failure criteria, Maximum stress failure criteria and the Tsai-Wu failure criteria. The optimization method is validated for a number of different loading configurations - uniaxial, biaxial and bending loads. The design optimization has been carried for both variable stacking sequences, as well fixed standard stacking schemes and a comparative study of the different design configurations evolved has been presented. (C) 2007 Elsevier Ltd. All rights reserved.

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A novel stress induced martenistic phase transformation is reported in an initial B2-CuZr nanowire of cross-sectional dimensions in the range of 19.44 x 19.44-38.88 x 38.88 angstrom(2) and temperature in the range of 10-400 K under both tensile and compressive loading. Extensive Molecular Dynamic simulations are performed using an inter-atomic potential of type Finnis and Sinclair. The nanowire shows a phase transformation from an initial B2 phase to BCT (body-centered-tetragonal) phase with failure strain of similar to 40% in tension, whereas in compression, comparatively a small B2 -> BCT phase transformation is observed with failure strain of similar to 25%. Size and temperature dependent deformation mechanisms which control ultimately the B2 -> BCT phase transformation are found to be completely different for tensile and compressive loadings. Under tensile loading, small cross-sectional nanowire shows a single step phase transformation, i.e. B2 -> BCT via twinning along {100} plane, whereas nanowires with larger cross-sectional area show a two step phase transformation, i.e. B2 -> R phase -> BCT along with intermediate hardening. In the first step, nanowire shows phase transformation from B2 -> R phase via twinning along {100} plane, afterwards the nanowire deforms via twinning along {110} plane which cause further transformation from R phase -> BCT phase. Under compressive loading, the nanowire shows crushing along {100} plane after a single step phase transformation from B2 -> BCT. Proper tailoring of such size and temperature dependent phase transformation can be useful in designing nanowire for high strength applications with corrosion and fatigue resistance. (C) 2009 Elsevier Ltd. All rights reserved.

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In this paper, we present a generic method/model for multi-objective design optimization of laminated composite components, based on Vector Evaluated Artificial Bee Colony (VEABC) algorithm. VEABC is a parallel vector evaluated type, swarm intelligence multi-objective variant of the Artificial Bee Colony algorithm (ABC). In the current work a modified version of VEABC algorithm for discrete variables has been developed and implemented successfully for the multi-objective design optimization of composites. The problem is formulated with multiple objectives of minimizing weight and the total cost of the composite component to achieve a specified strength. The primary optimization variables are the number of layers, its stacking sequence (the orientation of the layers) and thickness of each layer. The classical lamination theory is utilized to determine the stresses in the component and the design is evaluated based on three failure criteria: failure mechanism based failure criteria, maximum stress failure criteria and the tsai-wu failure criteria. The optimization method is validated for a number of different loading configurations-uniaxial, biaxial and bending loads. The design optimization has been carried for both variable stacking sequences, as well fixed standard stacking schemes and a comparative study of the different design configurations evolved has been presented. Finally the performance is evaluated in comparison with other nature inspired techniques which includes Particle Swarm Optimization (PSO), Artificial Immune System (AIS) and Genetic Algorithm (GA). The performance of ABC is at par with that of PSO, AIS and GA for all the loading configurations. (C) 2009 Elsevier B.V. All rights reserved.