988 resultados para Density dependence


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Instrumented nanoindentation was employed to study the depth dependence of nanohardness in a CuAlNi single crystal shape memory alloy that exhibits shape memory effect (SME). A Berkovich indenter and a cube comer indenter were used in this study, and the

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Collective damage of short fatigue cracks was analyzed in the light of equilibrium of crack numerical density. With the estimation of crack growth rate and crack nucleation rate, the solution of the equilibrium equation was studied to reveal the distinct feature of saturation distribution for crack numerical density. The critical time that characterized the transition of short and long-crack regimes was estimated, in which the influences of grain size and grain-boundary obstacle effect were investigated. Furthermore, the total number of cracks and the first order of damage moment were discussed.

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We have developed a classical two- and three-body interaction potential to simulate the hydroxylated, natively oxidized Si surface in contact with water solutions, based on the combination and extension of the Stillinger-Weber potential and of a potential originally developed to simulate SiO(2) polymorphs. The potential parameters are chosen to reproduce the structure, charge distribution, tensile surface stress, and interactions with single water molecules of a natively oxidized Si surface model previously obtained by means of accurate density functional theory simulations. We have applied the potential to the case of hydrophilic silicon wafer bonding at room temperature, revealing maximum room temperature work of adhesion values for natively oxidized and amorphous silica surfaces of 97 and 90 mJm(2), respectively, at a water adsorption coverage of approximately 1 ML. The difference arises from the stronger interaction of the natively oxidized surface with liquid water, resulting in a higher heat of immersion (203 vs 166 mJm(2)), and may be explained in terms of the more pronounced water structuring close to the surface in alternating layers of larger and smaller densities with respect to the liquid bulk. The computed force-displacement bonding curves may be a useful input for cohesive zone models where both the topographic details of the surfaces and the dependence of the attractive force on the initial surface separation and wetting can be taken into account.

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A Monte Carlo simulation is performed to study the dependence of collision frequency on interparticle distance for a system composed of two hard-sphere particles. The simulation quantitatively shows that the collision frequency drops down sharply as the distance between two particles increases. This characteristic provides a useful evidence for the collision-reaction dynamics of aggregation process for the two-particle system described in the other reference.

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The stability of Zr41Ti14Cu12.5Ni10Be22.5 bulk metallic glass (BMG) upon isothermal annealing near the glass transition temperature has been investigated by using x-ray diffraction, differential scanning calorimetry, and the pulse echo overlap method. The density, elastic constants, and thermodynamic parameters as well as their annealing time dependence have been determined. The microstructural and properties changes of the annealed BMG were checked by acoustic measurement. Obvious structural and property changes were observed with prolonged annealing of the BMG near the glass transition temperature.

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It has long been known that various ignition criteria of energetic materials have been limited in applicability to small regions. In order to explore the physical nature of ignition, we calculated how much thermal energy per unit mass of energetic materials was absorbed under different external stimuli. Hence, data of several typical sensitivity tests were analyzed by order of magnitude estimation. Then a new concept on critical thermal energy density was formulated. Meanwhile, the chemical nature of ignition was probed into by chemical kinetics.

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We present the Gaussian process density sampler (GPDS), an exchangeable generative model for use in nonparametric Bayesian density estimation. Samples drawn from the GPDS are consistent with exact, independent samples from a distribution defined by a density that is a transformation of a function drawn from a Gaussian process prior. Our formulation allows us to infer an unknown density from data using Markov chain Monte Carlo, which gives samples from the posterior distribution over density functions and from the predictive distribution on data space. We describe two such MCMC methods. Both methods also allow inference of the hyperparameters of the Gaussian process.