9 resultados para processing effects

em Indian Institute of Science - Bangalore - Índia


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The random direction short Glass Fiber Reinforced Plastics (GFRP) have been prepared by two compression moulding processes, namely the Preform and Sheet Moulding Compound (SMC) processes. Cutting force analysis and surface characterization are conducted on the random direction short GFRPs with varying fiber contents (25 similar to 40%). Edge trimming experiments are preformed using carbide inserts with varing the depth of cut and cutting speed. Machining characteristics of the Preform and SMC processed random direction short GFRPs are evaluated in terms of cutting forces, surface quality, and tool wear. It is found that composite primary processing and fiber contents are major contributing factors influencing the cutting force magnitudes and surface textures. The SMC composites show better surface finish over the Preform composites due to less delamination and fiber pullouts. Moreover, matrix damage and fiber protrusions at the machined edge are reduced by increasing fiber content in the random direction short GFRP composites.

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In the present paper, the size and strain rate effects on ultra-thin < 100 >/{100} Cu nanowires at an initial temperature of 10 K have been discussed. Extensive molecular dynamics (MD) simulations have been performed using Embedded atom method (EAM) to investigate the structural behaviours and properties under high strain rate. Velocity-Verlet algorithm has been used to solve the equation of motions. Two different thermal loading cases have been considered: (i) Isothermal loading, in which Nose-Hoover thermostat is used to maintain the constant system temperature, and (ii) Adiabatic loading, i.e., without any thermostat. Five different wire cross-sections were considered ranging from 0.723 x 0.723 nm(2) to 2.169 x 2.169 nm(2) The strain rates used in the present study were 1 x 10(9) s(-1), 1 x 10(8) s(-1), and 1 x 10(7) s(-1). The effect of strain rate on the mechanical properties of copper nanowires was analysed, which shows that elastic properties are independent of thermal loading for a given strain rate and cross-sectional dimension of nanowire. It showed a decreasing yield stress and yield strain with decreasing strain rate for a given cross- section. Also, a decreasing yield stress and increasing yield strain were observed for a given strain rate with increasing cross-sectional area. Elastic modulus was found to be similar to 100 GPa, which was independent of processing temperature, strain rate, and size for a given initial temperature. Reorientation of < 100 >/{100} square cross-sectional copper nanowire into a series of stable ultra-thin Pentagon copper nanobridge structures with dia of similar to 1 nm at 10 K was observed under high strain rate tensile loading. The effect of isothermal and adiabatic loading on the formation of such pentagonal nanobridge structure has been discussed.

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One of the biggest challenges when considering polymer nanocomposites for electrical insulation applications lies in determining their electrical properties accurately, which in turn depend on several factors, primary being dispersion of particles in the polymer matrix. With this background, this paper reports an experimental study to understand the effects of different processing techniques on the dispersion of filler particles in the polymer matrix and their related effect on the dielectric properties of the composites. Polymer composite and nanocomposite samples for the study were prepared by mixing 10% by weight of commercially available TiO2 particles of two different sizes in epoxy using different processing methods. A considerable effect of the composite processing method could be seen in the dielectric properties of nanocomposites.

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The regular associated solution model for binary systems has been modified by incorporating the size of the complex as an explicit variable. The thermodynamic properties of the liquid alloy and the interactions between theA ?B type of complex and the unassociated atoms in anA-B binary have been evaluated as a function of relative size of the complex using the activity coefficients at infinite dilution and activity data at one other composition in the binary. The computational procedure adopted for determining the concentration of clusters and interaction energies in the associated liquid is similar to that proposed by Lele and Rao. The analysis has been applied to the thermodynamic mixing functions of liquid Al-Ca alloys believed to contain Al2Ca associates. It is found that the size of the cluster significantly affects the interaction energies between the complex and the unassociated atoms, while the equilibrium constant and enthalpy change for the association reaction exhibit only minor variation, when the equations are fitted to experimental data. The interaction energy between unassociated free atoms remains virtually unaltered as the size of the complex is varied between extreme values. Accurate data on free energy, enthalpy, and volume of mixing at the same temperature on alloy systems with compound forming tendency would permit a rigorous test of the proposed model.

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In this article, we consider the single-machine scheduling problem with past-sequence-dependent (p-s-d) setup times and a learning effect. The setup times are proportional to the length of jobs that are already scheduled; i.e. p-s-d setup times. The learning effect reduces the actual processing time of a job because the workers are involved in doing the same job or activity repeatedly. Hence, the processing time of a job depends on its position in the sequence. In this study, we consider the total absolute difference in completion times (TADC) as the objective function. This problem is denoted as 1/LE, (Spsd)/TADC in Kuo and Yang (2007) ('Single Machine Scheduling with Past-sequence-dependent Setup Times and Learning Effects', Information Processing Letters, 102, 22-26). There are two parameters a and b denoting constant learning index and normalising index, respectively. A parametric analysis of b on the 1/LE, (Spsd)/TADC problem for a given value of a is applied in this study. In addition, a computational algorithm is also developed to obtain the number of optimal sequences and the range of b in which each of the sequences is optimal, for a given value of a. We derive two bounds b* for the normalising constant b and a* for the learning index a. We also show that, when a < a* or b > b*, the optimal sequence is obtained by arranging the longest job in the first position and the rest of the jobs in short processing time order.

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Carbon nanotubes dispersed in polymer matrix have been aligned in the form of fibers and interconnects and cured electrically and by UV light. Conductivity and effective semiconductor tunneling against reverse to forward bias field have been designed to have differentiable current-voltage response of each of the fiber/channel. The current-voltage response is a function of the strain applied to the fibers along axial direction. Biaxial and shear strains are correlated by differentiating signals from the aligned fibers/channels. Using a small doping of magnetic nanoparticles in these composite fibers, magneto-resistance properties are realized which are strong enough to use the resulting magnetostriction as a state variable for signal processing and computing. Various basic analog signal processing tasks such as addition, convolution and filtering etc. can be performed. These preliminary study shows promising application of the concept in combined analog-digital computation in carbon nanotube based fibers. Various dynamic effects such as relaxation, electric field dependent nonlinearities and hysteresis on the output signals are studied using experimental data and analytical model.

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We address the problem of speech enhancement in real-world noisy scenarios. We propose to solve the problem in two stages, the first comprising a generalized spectral subtraction technique, followed by a sequence of perceptually-motivated post-processing algorithms. The role of the post-processing algorithms is to compensate for the effects of noise as well as to suppress any artifacts created by the first-stage processing. The key post-processing mechanisms are aimed at suppressing musical noise and to enhance the formant structure of voiced speech as well as to denoise the linear-prediction residual. The parameter values in the techniques are fixed optimally by experimentally evaluating the enhancement performance as a function of the parameters. We used the Carnegie-Mellon university Arctic database for our experiments. We considered three real-world noise types: fan noise, car noise, and motorbike noise. The enhancement performance was evaluated by conducting listening experiments on 12 subjects. The listeners reported a clear improvement (MOS improvement of 0.5 on an average) over the noisy signal in the perceived quality (increase in the mean-opinion score (MOS)) for positive signal-to-noise-ratios (SNRs). For negative SNRs, however, the improvement was found to be marginal.

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The current study describes the evolution of microstructure and texture in an Al-Zn-Mg-Cu-Zr-based 7010 aluminum alloy during different modes of hot cross-rolling. Processing of materials involves three different types of cross-rolling. The development of texture in the one-step cross-rolled specimen can be described by a typical beta-fiber having the maximum intensity near Copper (Cu) component. However, for the multi-step cross-rolled specimens, the as-rolled texture is mainly characterized by a strong rotated-Brass (Bs) component and a very weak rotated-cube component. Subsequent heat treatment leads to sharpening of the major texture component (i.e., rotated-Bs). Furthermore, the main texture components in all the specimens appear to be significantly rotated in a complex manner away from their ideal positions because of non-symmetric deformations in the two rolling directions. Detailed microstructural study indicates that dynamic recovery is the dominant restoration mechanism operating during the hot rolling. During subsequent heat treatment, static recovery dominates, while a combination of particle-stimulated nucleation (PSN) and strain-induced grain boundary migration (SIBM) causes partial recrystallization of the grain structure. The aforementioned restoration mechanisms play an important role in the development of texture components. The textural development in the current study could be attributed to the combined effects of (a) cross-rolling and inter-pass annealing that reduce the intensity of Cu component after each successive pass, (b) recrystallization resistance of Bs-oriented grains, (c) stability of Bs texture under cross-rolling, and (d) Zener pinning by Al3Zr dispersoids.

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A comparative study of two bacterial strains namely, Bacillus licheniformis and Bacillus firmus in the production of bioflocculants was made. The highest bioflocculant yield of 16.55 g/L was obtained from B. licheniformis (L) and 10 g/L from B. firmus (F). The bioflocculants obtained from the bacterial species were water soluble and insoluble in organic solvents. FTIR spectral analysis revealed the presence of hydroxyl, carboxyl and sugar derivatives in the bioflocculants. Thermal characterization by differential scanning calorimetry (DSC) showed the crystalline transition and the melting point (T-m) at 90-100 degrees C. Effects of bioflocculant dosage and pH on the flocculation of clay fines were evaluated. Highest bioflocculation efficiency on kaolin clay suspensions was observed at an optimum bioflocculant dosage of 5 g/L. The optimum pH range for the maximum bioflocculation was at pH 7-9. Bioflocculants exhibited high efficiency in dye decolorization. The maximum Cr (VI) removal was found to be 85 % for L (bioflocculant dosage at 2 g/L). This study demonstrates that microbial bioflocculants find potential applications in mineral processing such as selective flocculation of mineral fines, decolorization of dye solutions and in the remediation of toxic metal solutions. (C) 2015 Elsevier B.V. All rights reserved.