The Head-On Colliding Process Of Binary Liquid Droplets At Low Velocity: High-Speed Photography Experiments And Modeling

The experimental and theoretical studies are reported in this paper for the head-on collisions of a liquid droplet with another of the same fluid resting on a solid substrate. The droplet on the hydrophobic polydimethylsiloxane (PDMS) substrate remains in a shape of an approximately spherical segment and is isometric to an incoming droplet. The colliding process of the binary droplets was recorded with high-speed photography. Head-on collisions saw four different types of response in our experiments: complete rebound, coalescence, partial rebound With conglutination, and coalescence accompanied by conglutination. For a complete rebound, both droplets exhibited remarkable elasticity and the contact time of the two colliding droplets was found to be in the range of 10-20 ms. With both droplets approximately considered as elastic bodies, Hertz contact theory was introduced to estimate the contact time for the complete rebound case. The estimated result Was found to be on the same order of magnitude as the experimental data, which indicates that the present model is reasonable. (C) 2008 Elsevier Inc. All rights reserved.

Characterization Of Crystal Structure In Binary Mixtures Of Latex Globules

Colloidal crystals formed by two types of polystyrene particles of different sizes (94 and 141 nm) at various number ratios (94:141 nm) are studied. Experiments showed that the formation time of crystals lengthens as the number ratio of the two components approaches 1:1. The dependence of the mean interparticle distance (D-0), crystal structure and alloy structure on the number ratio of the two types of particles was Studied by means of Kossel diffraction technique and reflection spectra. The results showed that as the number ratio decreased, the mean interparticle distance (D-0) became larger. And the colloidal crystal in binary mixtures is more preferably to form the bcc structure. This study found that binary systems form the substitutional solid solution (sss)-type alloy structure in all cases except when the number ratio of two types of particles is 5:1, which results instead in the superlattice structure. (C) 2008 Elsevier Inc. All rights reserved.

High-power laser beam shaping by inseparable two-dimensional binary-phase gratings for surface modification of stamping dies

For surface modification of stamping dies, an inseparable two-dimensional binary-phase gratings is introduced to implement the wavefront transformation of high-power laser beams. The design and fabrication of the gratings are described in detail. Two-dimensional even sampling encoding scheme is adopted to overcome the limitations of conventional Dammann grating in the design of two-dimensional output patterns. High diffractive efficiency (>70%) can be achieved through the transformation of the Gaussian laser beam into several kinds of two-dimensional arrays in focal plan. The application of the binary-phase gratings in the laser surface modification of ductile iron is investigated, and the results show that the hardness and the wear resistance of the sample surface were improved significantly by using the binary-phase gratings. (C) 2008 Elsevier Ltd. All rights reserved.

The vector fields admitting one-parameter spatial symmetry group and their reduction

For a n-dimensional vector fields preserving some n-form, the following conclusion is reached by the method of Lie group. That is, if it admits an one-parameter, n-form preserving symmetry group, a transformation independent of the vector field is constructed explicitly, which can reduce not only dimesion of the vector field by one, but also make the reduced vector field preserve the corresponding ( n - 1)-form. In partic ular, while n = 3, an important result can be directly got which is given by Me,ie and Wiggins in 1994.

An overview of sequential Monte Carlo methods for parameter estimation in general state-space models

Nonlinear non-Gaussian state-space models arise in numerous applications in control and signal processing. Sequential Monte Carlo (SMC) methods, also known as Particle Filters, are numerical techniques based on Importance Sampling for solving the optimal state estimation problem. The task of calibrating the state-space model is an important problem frequently faced by practitioners and the observed data may be used to estimate the parameters of the model. The aim of this paper is to present a comprehensive overview of SMC methods that have been proposed for this task accompanied with a discussion of their advantages and limitations.

Effects of physical parameter range on dimensionless variable sensitivity in water flooding reservoirs

The similarity criterion for water flooding reservoir flows is concerned with in the present paper. When finding out all the dimensionless variables governing this kind of flow, their physical meanings are subsequently elucidated. Then, a numerical approach of sensitivity analysis is adopted to quantify their corresponding dominance degree among the similarity parameters. In this way, we may finally identify major scaling law in different parameter range and demonstrate the respective effects of viscosity, permeability and injection rate.

Effects of physical parameter range on dimensionless variable sensitivity in water flooding reservoirs

The similarity criterion for water flooding reservoir flows is concerned with in the present paper. When finding out all the dimensionless variables governing this kind of flow, their physical meanings are subsequently elucidated. Then, a numerical approach of sensitivity analysis is adopted to quantify their corresponding dominance degree among the similarity parameters. In this way, we may finally identify major scaling law in different parameter range and demonstrate the respective effects of viscosity, permeability and injection rate.

Lattice type of fracture model for concrete

Concrete is usually described as a three-phase material, where matrix, aggregate and interface zones are distinguished. The beam lattice model has been applied widely by many investigators to simulate fracture processes in concrete. Due to the extremely large computational effort, however, the beam lattice model faces practical difficulties. In our investigation, a new lattice called generalized beam (GB) lattice is developed to reduce computational effort. Numerical experiments conducted on a panel subjected to uniaxial tension show that the GB lattice model can reproduce the load-displacement curves and crack patterns in agreement to what are observed in tests. Moreover, the effects of the particle overlay on the fracture process are discussed in detail. (C) 2007 Elsevier Ltd. All rights reserved.

Sequential Monte Carlo computation of the score and observed information matrix in state-space models with application to parameter estimation

Sequential Monte Carlo (SMC) methods are popular computational tools for Bayesian inference in non-linear non-Gaussian state-space models. For this class of models, we propose SMC algorithms to compute the score vector and observed information matrix recursively in time. We propose two different SMC implementations, one with computational complexity $\mathcal{O}(N)$ and the other with complexity $\mathcal{O}(N^{2})$ where $N$ is the number of importance sampling draws. Although cheaper, the performance of the $\mathcal{O}(N)$ method degrades quickly in time as it inherently relies on the SMC approximation of a sequence of probability distributions whose dimension is increasing linearly with time. In particular, even under strong \textit{mixing} assumptions, the variance of the estimates computed with the $\mathcal{O}(N)$ method increases at least quadratically in time. The $\mathcal{O}(N^{2})$ is a non-standard SMC implementation that does not suffer from this rapid degrade. We then show how both methods can be used to perform batch and recursive parameter estimation.