307 resultados para dynamic recrystallization


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The evolution of texture and microstructure during recrystallization is studied for two-phase copper alloy (Cu–40Zn) with a variation of the initial texture and microstructure (hot rolled and solution treated) as well as the mode of rolling (deformation path: uni-directional rolling and cross rolling). The results of bulk texture have been supported by micro-texture and microstructure studies carried out using electron back scatter diffraction (EBSD). The initial microstructural condition as well as the mode of rolling has been found to alter the recrystallization texture and microstructure. The uni-directionally rolled samples showed a strong Goss and BR {236}385 component while a weaker texture similar to that of rolling evolved for the cross-rolled samples in the α phase on recrystallization. The recrystallization texture of the β phase was similar to that of the rolling texture with discontinuous 101 α and {111} γ fiber with high intensity at {111}101. For a given microstructure, the cross-rolled samples showed a higher fraction of coincident site lattice Σ3 twin boundaries in the α phase. The higher fraction of Σ3 boundaries is explained on the basis of the higher propensity of growth accidents during annealing of the cross-rolled samples. The present investigation demonstrates that change in strain path, as introduced during cross-rolling, could be a viable tool for grain boundary engineering of low SFE fcc materials.

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By using bender and extender elements test, the velocities of the primary and shear waves, V(P) and V(s) respectively, were measured for a sandy material by gradually varying the degree of saturation, S(r), between the dry and fully saturated states. The effect on the results of varying the relative density and effective confining pressure was also studied. The measurements clearly reveal that for a certain optimum S(r), which is around 0.7-0.9% for the chosen sand, the value of the shear modulus G reaches a maximum value, whereas the corresponding Poisson's ratio nu attains a minimum value. The values of the shear modulus corresponding to S(r) approximate to 0% and S(r) = 100% tend towards the same value. For values of Skempton's B parameter greater than 0.99, the values of V(P) and nu rise very sharply to those of water. The predictions from Biot's theory with respect to the variation of V(P) with S(r) match well with the measured experimental data.

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The study focuses on probabilistic assessment of the internal seismic stability of reinforced soil structures (RSS) subjected to earthquake loading in the framework of the pseudo-dynamic method. In the literature, the pseudo-static approach has been used to compute reliability indices against the tension and pullout failure modes, and the real dynamic nature of earthquake accelerations cannot be considered. The work presented in this paper makes use of the horizontal and vertical sinusoidal accelerations, amplification of vibrations, shear wave and primary wave velocities and time period. This approach is applied to quantify the influence of the backfill properties, geosynthetic reinforcement and characteristics of earthquake ground motions on reliability indices in relation to the tension and pullout failure modes. Seismic reliability indices at different levels of geosynthetic layers are determined for different magnitudes of seismic acceleration, soil amplification, shear wave and primary wave velocities. The results are compared with the pseudo-static method, and the significance of the present methodology for designing reinforced soil structures is discussed.

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In this paper, we investigate the use of reinforcement learning (RL) techniques to the problem of determining dynamic prices in an electronic retail market. As representative models, we consider a single seller market and a two seller market, and formulate the dynamic pricing problem in a setting that easily generalizes to markets with more than two sellers. We first formulate the single seller dynamic pricing problem in the RL framework and solve the problem using the Q-learning algorithm through simulation. Next we model the two seller dynamic pricing problem as a Markovian game and formulate the problem in the RL framework. We solve this problem using actor-critic algorithms through simulation. We believe our approach to solving these problems is a promising way of setting dynamic prices in multi-agent environments. We illustrate the methodology with two illustrative examples of typical retail markets.

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Many web sites incorporate dynamic web pages to deliver customized contents to their users. However, dynamic pages result in increased user response times due to their construction overheads. In this paper, we consider mechanisms for reducing these overheads by utilizing the excess capacity with which web servers are typically provisioned. Specifically, we present a caching technique that integrates fragment caching with anticipatory page pre-generation in order to deliver dynamic pages faster during normal operating situations. A feedback mechanism is used to tune the page pre-generation process to match the current system load. The experimental results from a detailed simulation study of our technique indicate that, given a fixed cache budget, page construction speedups of more than fifty percent can be consistently achieved as compared to a pure fragment caching approach.

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The realistic estimation of the dynamic characteristics for a known set of loading conditions continues to be difficult despite many contributions in the past. The design of a machine foundation is generally made on the basis of limiting amplitude or resonant frequency. These parameters are in turn dependent on the dynamic characteristics of soil viz., the shear modulus/stiffness and damping. The work reported herein is an attempt to relate statistically the shear modulus of a soil to its resonant amplitude under a known set of static and dynamic loading conditions as well as wide ranging soil conditions. The two parameters have been statistically related with a good correlation coefficient and low standard error of estimate.

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Over the past decade, many powerful data mining techniques have been developed to analyze temporal and sequential data. The time is now fertile for addressing problems of larger scope under the purview of temporal data mining. The fourth SIGKDD workshop on temporal data mining focused on the question: What can we infer about the structure of a complex dynamical system from observed temporal data? The goals of the workshop were to critically evaluate the need in this area by bringing together leading researchers from industry and academia, and to identify promising technologies and methodologies for doing the same. We provide a brief summary of the workshop proceedings and ideas arising out of the discussions.

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Dendritic rnicroenvironments defined by dynamic internal cavities of a dendrimer were probed through geometric isomerization of stilbene and azobenzene. A third-generation poly(alkyl aryl ether) dendrimer with hydrophilic exterior and hydrophobic interior was used as a reaction cavity in aqueous medium. The dynamic inner cavity sizes were varied by utilizing alkyl linkers that connect the branch junctures from ethyl to n-pentyl moiety (C(2)G(3)-C(5)G(3)). Dendrimers constituted with n-pentyl linker were found to afford higher solubilities of stilbene and azobenzene. Direct irradiation of trans-stilbene showed that C(5)G(3) and C(4)G(3) dendrimers afforded considerable phenanthrene formation, in addition to cis-stilbene, whereas C(3)G(3) and C(2)G(3) gave only cis-stilbene. An electron-transfer sensitized trans-cis isomerization, using cresyl violet perchlorate as the sensitizer, also led to similar results. Thermal isomerization of cis-azobenzene to trans-azobenzene within dendritic microenvironments revealed that the activation energy of the cis- to trans-isomer was increasing in the series C(5)G(3) < C(4)G(3) < C(3)G(3)

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A generalized power tracking algorithm that minimizes power consumption of digital circuits by dynamic control of supply voltage and the body bias is proposed. A direct power monitoring scheme is proposed that does not need any replica and hence can sense total power consumed by load circuit across process, voltage, and temperature corners. Design details and performance of power monitor and tracking algorithm are examined by a simulation framework developed using UMC 90-nm CMOS triple well process. The proposed algorithm with direct power monitor achieves a power savings of 42.2% for activity of 0.02 and 22.4% for activity of 0.04. Experimental results from test chip fabricated in AMS 350 nm process shows power savings of 46.3% and 65% for load circuit operating in super threshold and near sub-threshold region, respectively. Measured resolution of power monitor is around 0.25 mV and it has a power overhead of 2.2% of die power. Issues with loop convergence and design tradeoff for power monitor are also discussed in this paper.

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This work focuses on the design of torsional microelectromechanical systems (MEMS) varactors to achieve highdynamic range of capacitances. MEMS varactors fabricated through the polyMUMPS process are characterized at low and high frequencies for their capacitance-voltage characteristics and electrical parasitics. The effect of parasitic capacitances on tuning ratio is studied and an equivalent circuit is developed. Two variants of torsional varactors that help to improve the dynamic range of torsional varactors despite the parasitics are proposed and characterized. A tuning ratio of 1:8, which is the highest reported in literature, has been obtained. We also demonstrate through simulations that much higher tuning ratios can be obtained with the designs proposed. The designs and experimental results presented are relevant to CMOS fabrication processes that use low resistivity substrate. (C) 2012 Society of Photo-Optical Instrumentation Engineers (SPIE). DOI: 10.1117/1.JMM.11.1.013006]

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The importance of air bearing design is growing in engineering. As the trend to precision and ultra precision manufacture gains pace and the drive to higher quality and more reliable products continues, the advantages which can be gained from applying aerostatic bearings to machine tools, instrumentation and test rigs is becoming more apparent. The inlet restrictor design is significant for air bearings because it affects the static and dynamic performance of the air bearing. For instance pocketed orifice bearings give higher load capacity as compared to inherently compensated orifice type bearings, however inherently compensated orifices, also known as laminar flow restrictors are known to give highly stable air bearing systems (less prone to pneumatic hammer) as compared to pocketed orifice air bearing systems. However, they are not commonly used because of the difficulties encountered in manufacturing and assembly of the orifice designs. This paper aims to analyse the static and dynamic characteristics of inherently compensated orifice based flat pad air bearing system. Based on Reynolds equation and mass conservation equation for incompressible flow, the steady state characteristics are studied while the dynamic state characteristics are performed in a similar manner however, using the above equations for compressible flow. Steady state experiments were also performed for a single orifice air bearing and the results are compared to that obtained from theoretical studies. A technique to ease the assembly of orifices with the air bearing plate has also been discussed so as to make the manufacturing of the inherently compensated bearings more commercially viable. (c) 2012 Elsevier Inc. All rights reserved.

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Many problems of state estimation in structural dynamics permit a partitioning of system states into nonlinear and conditionally linear substructures. This enables a part of the problem to be solved exactly, using the Kalman filter, and the remainder using Monte Carlo simulations. The present study develops an algorithm that combines sequential importance sampling based particle filtering with Kalman filtering to a fairly general form of process equations and demonstrates the application of a substructuring scheme to problems of hidden state estimation in structures with local nonlinearities, response sensitivity model updating in nonlinear systems, and characterization of residual displacements in instrumented inelastic structures. The paper also theoretically demonstrates that the sampling variance associated with the substructuring scheme used does not exceed the sampling variance corresponding to the Monte Carlo filtering without substructuring. (C) 2012 Elsevier Ltd. All rights reserved.

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Traditional image reconstruction methods in rapid dynamic diffuse optical tomography employ l(2)-norm-based regularization, which is known to remove the high-frequency components in the reconstructed images and make them appear smooth. The contrast recovery in these type of methods is typically dependent on the iterative nature of method employed, where the nonlinear iterative technique is known to perform better in comparison to linear techniques (noniterative) with a caveat that nonlinear techniques are computationally complex. Assuming that there is a linear dependency of solution between successive frames resulted in a linear inverse problem. This new framework with the combination of l(1)-norm based regularization can provide better robustness to noise and provide better contrast recovery compared to conventional l(2)-based techniques. Moreover, it is shown that the proposed l(1)-based technique is computationally efficient compared to its counterpart (l(2)-based one). The proposed framework requires a reasonably close estimate of the actual solution for the initial frame, and any suboptimal estimate leads to erroneous reconstruction results for the subsequent frames.

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Multi-layered materials have been made from Cu-Fe with approximately equal volume fractions using the Accumulated Roll Bonding (ARB) technique with less than 1 μm thickness of the individual layers. The so-obtained multi-layers have been subjected to deformation by cold rolling to 25, 50, 75, 87 and 93% reduction in thickness. A detailed characterization has been carried out using X-ray diffraction (line profile analysis and texture measurement) and electron (scanning and transmission) microscopy. It has been found that Fe layers are disintegrated whereas Cu retains its continuity within a layer. Microstructural Characterization from X-Ray Line profile Analysis (XRDLPA) through Variance Method reveals that large amount of strain is initially carried by Cu layers during deformation. In the Cu-Fe layer, the texture is comparatively weaker in Cu layer and strong in Fe layers. Brass Component increases up to 75% reduction and then decreases, while the ratio of Cu/S and Bs/S remains almost constant through out the deformation. After 50% reduction, dynamic recovery is predominant as indicated by the increase in the amount of low angle grain boundaries and decrease in dislocation density. The presence of R component indicates continuous dynamic recovery and recrystallization (CDRR) at the advanced stage of deformation.