Evolution of texture during equal channel angular extrusion of commercially pure aluminum: Experiments and simulations

The evolution of crystallographic texture has been comprehensively studied for commercially pure Al as a function of amount of ECAE deformation for the three major routes of ECAE processing. It has been observed that processing through different routes leads to different type of texture, in both qualitative as well as quantitative sense. The results have been analyzed on the basis of existing concepts on ECAE deformation and simulations have been carried out using the simple shear model of ECAE implemented into the Viscoplastic Self Consistent model of polycrystal plasticity. The simulations revealed that non-octahedral slip is needed to reproduce the experimental texture development.

Deformation behaviour of commercially pure titanium at extreme strain rates

The evolution of microstructure and texture during room temperature compression of commercially pure Ti with four different initial orientations were studied under quasi-static and dynamic loading conditions. At a low strain rate (epsilon)over dot = 3 x 10(-4) s(-1) the different initial textures yielded the same end texture, despite different microstructural evolution in terms of twin boundaries. High strain rate deformation at (epsilon)over dot = 1.5 x 10(3) s(-1) was characterized by extensive twinning and evolution of a texture that was similar to that at low strain rate with minor differences. However, there was a significant difference in the strength of the texture for different orientations that was absent for low strain rate deformed samples at high strain rate. A viscoplastic self-consistent model with a secant approach was used to corroborate the experimental results by simulation. (C) 2011 Published by Elsevier Ltd. on behalf of Acta Materialia Inc.

Effects of different modes of hot cross-rolling in 7010 aluminum alloy: part II. mechanical properties anisotropy

The influence of microstructure and texture developed by different modes of hot cross-rolling on in-plane anisotropy (A (IP)) of yield strength, work hardening behavior, and anisotropy of Knoop hardness (KHN) yield locus has been investigated. The A (IP) and work hardening behavior are evaluated by tensile testing at 0 deg, 45 deg, and 90 deg to the rolling direction, while yield loci have been generated by directional KHN measurements. It has been observed that specimens especially in the peak-aged temper, in spite of having a strong, rotated Brass texture, show low A (IP). The results are discussed on the basis of Schmid factor analyses in conjunction with microstructural features, namely grain morphology and precipitation effects. For the specimen having a single-component texture, the yield strength variation as a function of orientation can be rationalized by the Schmid factor analysis of a perfectly textured material behaving as a quasi-single crystal. The work hardening behavior is significantly affected by the presence of solute in the matrix and the state of precipitation rather than texture, while yield loci derived from KHN measurements reiterate the low anisotropy of the materials. Theoretic yield loci calculated from the texture data using the visco-plastic self-consistent model and Hill's anisotropic equation are compared with that obtained experimentally.

Texture Evolution in Nanocrystalline Nickel: Critical Role of Strain Path

The effect of strain path change during rolling on the evolution of deformation texture has been studied for nanocrystalline (nc) nickel. An orthogonal change in strain path, as imparted by alternating rolling and transverse directions, leads to a texture with a strong Bs {110}aOE (c) 112 > component. The microstructural features, after large deformation, show distinct grain morphology for the cross-rolled material. Crystal plasticity simulations, based on viscoplastic self-consistent model, indicate that slip involving partial dislocation plays a vital role in accommodating plastic deformation during the initial stages of rolling. The brass-type texture evolved after cross rolling to large strains is attributed to change in strain path.

Self-tuning minimum-variance control of nonlinear systems of the Hammerstein model

Self-tuning is applied to the control of nonlinear systems represented by the Hammerstein model wherein the nonlinearity is any odd-order polynomial. But control costing is not feasible in general. Initial relay control is employed to contain the deviations.

A self-adaptive migration model genetic algorithm for data mining applications

Data mining involves nontrivial process of extracting knowledge or patterns from large databases. Genetic Algorithms are efficient and robust searching and optimization methods that are used in data mining. In this paper we propose a Self-Adaptive Migration Model GA (SAMGA), where parameters of population size, the number of points of crossover and mutation rate for each population are adaptively fixed. Further, the migration of individuals between populations is decided dynamically. This paper gives a mathematical schema analysis of the method stating and showing that the algorithm exploits previously discovered knowledge for a more focused and concentrated search of heuristically high yielding regions while simultaneously performing a highly explorative search on the other regions of the search space. The effective performance of the algorithm is then shown using standard testbed functions and a set of actual classification datamining problems. Michigan style of classifier was used to build the classifier and the system was tested with machine learning databases of Pima Indian Diabetes database, Wisconsin Breast Cancer database and few others. The performance of our algorithm is better than others.

A Dynamic Migration Model for Self-adaptive Genetic Algorithms

In this paper, we propose a self Adaptive Migration Model for Genetic Algorithms, where parameters of population size, the number of points of crossover and mutation rate for each population are fixed adaptively. Further, the migration of individuals between populations is decided dynamically. This paper gives a mathematical schema analysis of the method stating and showing that the algorithm exploits previously discovered knowledge for a more focused and concentrated search of heuristically high yielding regions while simultaneously performing a highly explorative search on the other regions of the search space. The effective performance of the algorithm is then shown using standard testbed functions, when compared with Island model GA(IGA) and Simple GA(SGA).

A Dynamic Migration Model for self-adaptive Genetic Algorithms

In this paper, we propose a self Adaptive Migration Model for Genetic Algorithms, where parameters of population size, the number of points of crossover and mutation rate for each population are fixed adaptively. Further, the migration of individuals between populations is decided dynamically. This paper gives a mathematical schema analysis of the method stating and showing that the algorithm exploits previously discovered knowledge for a more focused and concentrated search of heuristically high yielding regions while simultaneously performing a highly explorative search on the other regions of the search space. The effective performance of the algorithm is then shown using standard testbed functions, when compared with Island model GA(IGA) and Simple GA(SGA).

Design of nonequivalent self-routing networks based on a matrix model

In earlier work, nonisomorphic graphs have been converted into networks to realize Multistage Interconnection networks, which are topologically nonequivalent to the Baseline network. The drawback of this technique is that these nonequivalent networks are not guaranteed to be self-routing, because each node in the graph model can be replaced by a (2 × 2) switch in any one of the four different configurations. Hence, the problem of routing in these networks remains unsolved. Moreover, nonisomorphic graphs were obtained by interconnecting bipartite loops in a heuristic manner; the heuristic nature of this procedure makes it difficult to guarantee full connectivity in large networks. We solve these problems through a direct approach, in which a matrix model for self-routing networks is developed. An example is given to show that this model encompases nonequivalent self-routing networks. This approach has the additional advantage in that the matrix model itself ensures full connectivity.

Spectral moment sum rules for the retarded Green's function and self-energy of the inhomogeneous Bose-Hubbard model in equilibrium and nonequilibrium

We derive exact expressions for the zeroth and the first three spectral moment sum rules for the retarded Green's function and for the zeroth and the first spectral moment sum rules for the retarded self-energy of the inhomogeneous Bose-Hubbard model in nonequilibrium, when the local on-site repulsion and the chemical potential are time-dependent, and in the presence of an external time-dependent electromagnetic field. We also evaluate these expressions for the homogeneous case in equilibrium, where all time dependence and external fields vanish. Unlike similar sum rules for the Fermi-Hubbard model, in the Bose-Hubbard model case, the sum rules often depend on expectation values that cannot be determined simply from parameters in the Hamiltonian like the interaction strength and chemical potential but require knowledge of equal-time many-body expectation values from some other source. We show how one can approximately evaluate these expectation values for the Mott-insulating phase in a systematic strong-coupling expansion in powers of the hopping divided by the interaction. We compare the exact moment relations to the calculated moments of spectral functions determined from a variety of different numerical approximations and use them to benchmark their accuracy. DOI: 10.1103/PhysRevA.87.013628

Dissecting Ubiquitin Folding Using the Self-Organized Polymer Model

Folding of Ubiquitin (Ub), a functionally important protein found in eukaryotic organisms, is investigated at low and neutral pH at different temperatures using simulations of the coarse-grained self-organized-polymer model with side chains (SOP-SC). The melting temperatures (T-m's), identified with the peaks in the heat capacity curves, decrease as pH decreases, in qualitative agreement with experiments. The calculated radius of gyration, showing dramatic variations with pH, is in excellent agreement with scattering experiments. At T-m Ub folds in a two-state manner at low and neutral pH. Clustering analysis of the conformations sampled in equilibrium folding trajectories at T-m with multiple transitions between the folded and unfolded states, shows a network of metastable states connecting the native and unfolded states. At low and neutral pH, Ub folds with high probability through a preferred set of conformations resulting in a pH-dependent dominant folding pathway. Folding kinetics reveal that Ub assembly at low pH occurs by multiple pathways involving a combination of nucleation-collapse and diffusion collision mechanism. The mechanism by which Ub folds is dictated by the stability of the key secondary structural elements responsible for establishing long-range contacts and collapse of Ub. Nucleation collapse mechanism holds if the stability of these elements are marginal, as would be the case at elevated temperatures. If the lifetimes associated with these structured microdomains are on the order of hundreds of microseconds, then Ub folding follows the diffusion collision mechanism with intermediates, many of which coincide with those found in equilibrium. Folding at neutral pH is a sequential process with a populated intermediate resembling that sampled at equilibrium. The transition state structures, obtained using a P-fold analysis, are homogeneous and globular with most of the secondary and tertiary structures being native-like. Many of our findings for both the thermodynamics and kinetics of folding are not only in agreement with experiments but also provide missing details not resolvable in standard experiments. The key prediction that folding mechanism varies dramatically with pH is amenable to experimental tests.

Self-organized criticality in dynamics without branching

We demonstrate the phenomenon of self-organized criticality (SOC) in a simple random walk model described by a random walk of a myopic ant, i.e., a walker who can see only nearest neighbors. The ant acts on the underlying lattice aiming at uniform digging, i.e., reduction of the height profile of the surface but is unaffected by the underlying lattice. In one, two, and three dimensions we have explored this model and have obtained power laws in the time intervals between consecutive events of "digging." Being a simple random walk, the power laws in space translate to power laws in time. We also study the finite size scaling of asymptotic scale invariant process as well as dynamic scaling in this system. This model differs qualitatively from the cascade models of SOC.