Turbulent collision of inertial particles: point-particle based, hybrid simulations and beyond

Point-particle based direct numerical simulation (PPDNS) has been a productive research tool for studying both single-particle and particle-pair statistics of inertial particles suspended in a turbulent carrier flow. Here we focus on its use in addressing particle-pair statistics relevant to the quantification of turbulent collision rate of inertial particles. PPDNS is particularly useful as the interaction of particles with small-scale (dissipative) turbulent motion of the carrier flow is mostly relevant. Furthermore, since the particle size may be much smaller than the Kolmogorov length of the background fluid turbulence, a large number of particles are needed to accumulate meaningful pair statistics. Starting from the relative simple Lagrangian tracking of so-called ghost particles, PPDNS has significantly advanced our theoretical understanding of the kinematic formulation of the turbulent geometric collision kernel by providing essential data on dynamic collision kernel, radial relative velocity, and radial distribution function. A recent extension of PPDNS is a hybrid direct numerical simulation (HDNS) approach in which the effect of local hydrodynamic interactions of particles is considered, allowing quantitative assessment of the enhancement of collision efficiency by fluid turbulence. Limitations and open issues in PPDNS and HDNS are discussed. Finally, on-going studies of turbulent collision of inertial particles using large-eddy simulations and particle- resolved simulations are briefly discussed.

An Integrated Evolutionary Algorithm for Expensive Global Optimization

We propose an integrated algorithm named low dimensional simplex evolution extension (LDSEE) for expensive global optimization in which only a very limited number of function evaluations is allowed. The new algorithm accelerates an existing global optimization, low dimensional simplex evolution (LDSE), by using radial basis function (RBF) interpolation and tabu search. Different from other expensive global optimization methods, LDSEE integrates the RBF interpolation and tabu search with the LDSE algorithm rather than just calling existing global optimization algorithms as subroutines. As a result, it can keep a good balance between the model approximation and the global search. Meanwhile it is self-contained. It does not rely on other GO algorithms and is very easy to use. Numerical results show that it is a competitive alternative for expensive global optimization.

Optimal feedback control of two-photon fluorescence based on genetic algorithm

An optimal feedback control of two-photon fluorescence in the ethanol solution of 4-dicyanomethylene-2-methyl-6-p-dimethyl-amiiiostryryl-4H-pyran (DCM) using pulse-shaping technique based on genetic algorithm is demonstrated experimentally. The two-photon fluorescence of the DCM ethanol solution is enhanced in intensity of about 23%. The second harmonic generation frequency-resolved optical gating (SHG-FROG) trace indicates that the effective population transfer arises from the positively chirped pulse. The experimental results appear the potential applications of coherent control to the complicated molecular system.

Optimal feedback control of two-photon fluorescence in Coumarin 515 based on genetic algorithm

An optimal feedback control of two-photon fluorescence in the Coumarin 515 ethanol solution excited by shaping femtosecond laser pulses based on genetic algorithm is demonstrated experimentally. The two-photon fluorescence intensity can be enhanced by similar to 20%. Second harmonic generation frequency-resolved optical gating traces indicate that the optimal laser pulses are positive chirp, which are in favor of the effective population transfer of two-photon transitions. The dependence of the two-photon fluorescence signal on the laser pulse chirp is investigated to validate the theoretical model for the effective population transfer of two-photon transitions. The experimental results appear the potential applications in nonlinear spectroscopy and molecular physics. (c) 2005 Elsevier B.V. All rights reserved.

Copper phthalocyanine based hybrid p-type permeable-base transistor in vertical architecture

We demonstrate the production of copper phthalocyanine (CuPc) based p-type hybrid permeable-base transistors, which operate at low voltages having high common-base current gains. These transistors are prepared by evaporating a thin metal layer (Ag or Al) that acts as base on top of a Si substrate that acts as collector. In the sequence CuPc and Au are thermally sublimated to produce the emitter, constituting a quite simple device production procedure with the additional advantage of allowing higher integration due to its vertical architecture.

High current density tris(8-hydroxyquinoline) aluminum-based hybrid transistor in vertical architecture

We report the construction of hybrid permeable-base transistors, in vertical architecture, using tris(8-hydroxyquinoline) aluminum as emitter, a thin gold layer as base, and n-type silicon as collector. These transistors present high common-base current gain, can be operated at low driving voltages, and allow high current density.

Triangle Evolution-A Hybrid Heuristic for Global Optimization

Abstract This paper presents a hybrid heuristic{triangle evolution (TE) for global optimization. It is a real coded evolutionary algorithm. As in di®erential evolution (DE), TE targets each individual in current population and attempts to replace it by a new better individual. However, the way of generating new individuals is di®erent. TE generates new individuals in a Nelder- Mead way, while the simplices used in TE is 1 or 2 dimensional. The proposed algorithm is very easy to use and e±cient for global optimization problems with continuous variables. Moreover, it requires only one (explicit) control parameter. Numerical results show that the new algorithm is comparable with DE for low dimensional problems but it outperforms DE for high dimensional problems.

Recent progresses of Si-based photonics in chinese main land

Si-based photonic materials and devices, including SiGe/Si quantum structures, SOI and InGaAs bonded on Si, PL of Si nanocrystals, SOI photonic crystal filter, Si based RCE (Resonant Cavity Enhanced) photodiodes, SOI TO (thermai-optical) switch matrix were investigated in Institute of Serniconductors, Chinese Academy of Sciences. The main results in recent years are presented in the paper. The mechanism of PL from Si NCs embedded in SiO2 matrix was studied, a greater contribution of the interface state recombination (PL peak in 850 similar to 900 nm) is associated with larger Si NCs and higher interface state density. Ge dots with density of order of 10(11) cm(-2) were obtained by UHV/CVD growth and 193 nm excimer laser annealing. SOI photonic crystal filter with resonant wavelength of 1598 nm and Q factor of 1140 was designed and made. Si based hybrid InGaAs RCE PD with eta of 34.4% and FWHM of 27 nut were achieved by MOCVD growth and bonding technology between InGaAs epitaxial and Si wafers. A 16x16 SOI optical switch matrix were designed and made. A new current driving circuit was used to improve the response speed of a 4x4 SOI rearrangeable nonblocking TO switch matrix, rising and failing time is 970 and 750 ns, respectively.

Research of Face Location System Based on Human Vision Simulations

In this paper we present a robust face location system based on human vision simulations to automatically locate faces in color static images. Our method is divided into four stages. In the first stage we use a gauss low-pass filter to remove the fine information of images, which is useless in the initial stage of human vision. During the second and the third stages, our technique approximately detects the image regions, which may contain faces. During the fourth stage, the existence of faces in the selected regions is verified. Having combined the advantages of Bottom-Up Feature Based Methods and Appearance-Based Methods, our algorithm performs well in various images, including those with highly complex backgrounds.

基于进化计算的无人飞行器多航迹规划

针对飞行器多航迹规划问题展开研究.在分析多峰值函数优化问题的基础上,提出了一种基于进化计算的飞行器多航迹规划方法.该方法通过使用特定的染色体表示方法和进化算子,可以有效利用各种环境信息,处理各种航迹约束.同时,通过引入聚类算法,将种群中的个体按其空间分布进行聚类,生成若干个不同子种群.在进化过程中,所有个体只在各自的子种群内部进化.当进化结束时,每个子种群将分别生成一条各自的最优航迹,从而为飞行器生成多条不同的可选航迹.仿真结果表明了该方法的有效性.