星载激光对水下目标通信可行性研究

The characteristics of media in communication channel are analyzed briefly and the reasonable optical parameters of media are adopted. With certain communication system parameters the temporal and spatial distributions of the received signal from submerged platform are simulated using Monte Carlo method. The upper limit of the ratio of Monte Carlo estimated error to averaged value is about 0.3%. From the simulated results, the optimized sampling timing of receiver and field of view of telescope are obtained. Also the signal-to-noise ratio of the receiver is calculated. Based on this, the error probability of the communication system is deduced from laser pulse position modulation and maximum likelihood detection. The results show that under severe environment robust laser communication from a satellite to a submerged platform can be achieved.

Extended bidirectional reflectance distribution function for polarized light scattering from subsurface defects under a smooth surface

By introducing the scattering probability of a subsurface defect (SSD) and statistical distribution functions of SSD radius, refractive index, and position, we derive an extended bidirectional reflectance distribution function (BRDF) from the Jones scattering matrix. This function is applicable to the calculation for comparison with measurement of polarized light-scattering resulting from a SSD. A numerical calculation of the extended BRDF for the case of p-polarized incident light was performed by means of the Monte Carlo method. Our numerical results indicate that the extended BRDF strongly depends on the light incidence angle, the light scattering angle, and the out-of-plane azimuth angle. We observe a 180 degrees symmetry with respect to the azimuth angle. We further investigate the influence of the SSD density, the substrate refractive index, and the statistical distributions of the SSD radius and refractive index on the extended BRDF. For transparent substrates, we also find the dependence of the extended BRDF on the SSD positions. (c) 2006 Optical Society of America.

The effect of diffusion and overhangs/vacancies on the microstructure of zig-zag thin film

Basing on some growth models of thin film, we have investigated the growth mechanism of glancing angle deposition (GLAD) film. The simulation verifies that the overhangs/vacancies also contribute to the columnar growth as well as the self-shadowing effect for GLAD thin film. Besides, we have studied the effect of the deposition rate, surface and bulk diffusions on the microstructure of thin film using the time-dependent Monte Carlo method. The results show that the surface and bulk diffusions can significantly enhance the packing density of thin film in GLAD growth, and the increase of the deposition rate induce the moderate decrease of the packing density. (c) 2006 Elsevier B.V. All rights reserved.

Probabilistic fault identification using vibration data and neural networks

Bayesian formulated neural networks are implemented using hybrid Monte Carlo method for probabilistic fault identification in cylindrical shells. Each of the 20 nominally identical cylindrical shells is divided into three substructures. Holes of (12±2) mm in diameter are introduced in each of the substructures and vibration data are measured. Modal properties and the Coordinate Modal Assurance Criterion (COMAC) are utilized to train the two modal-property-neural-networks. These COMAC are calculated by taking the natural-frequency-vector to be an additional mode. Modal energies are calculated by determining the integrals of the real and imaginary components of the frequency response functions over bandwidths of 12% of the natural frequencies. The modal energies and the Coordinate Modal Energy Assurance Criterion (COMEAC) are used to train the two frequency-response-function-neural-networks. The averages of the two sets of trained-networks (COMAC and COMEAC as well as modal properties and modal energies) form two committees of networks. The COMEAC and the COMAC are found to be better identification data than using modal properties and modal energies directly. The committee approach is observed to give lower standard deviations than the individual methods. The main advantage of the Bayesian formulation is that it gives identities of damage and their respective confidence intervals.

Bayesian inference of population expansions in domestic bovines

< p > The past population dynamics of four domestic and one wild species of bovine were estimated using Bayesian skyline plots, a coalescent Markov chain Monte Carlo method that does not require an assumed parametric model of demographic history. Four dom

Robust airfoil design with respect to boundary layer transition

In order to disign an airfoil of which maximum lift coefficient (CL max) is not sensitive to location of forced top boundary layer transition. Taking maximizing mean value of CL max and minimizing standard deviation as biobjective, leading edge radius, manximum thickness and its location, maximum camber and its location as deterministic design variables, location of forced top boundary layer transition as stochastic variable, XFOIL as deterministic CFD solver, non-intrusive polynomial chaos as substitute of Monte Carlo method, we completed a robust airfoil design problem. Results demonstrate performance of initial airfoil is enhanced through reducing standard deviation of CL max. Besides, we also know maximum thickness has the most dominating effect on mean value of CL max, location of maximum thickness has the most dominating effect on standard deviation of CL max, maximum camber has a little effect on both mean value and standard deviation, and maximum camber is the only element of which increase can lead increase of mean value and standard deviation at the same time. Copyright © 2009 by the American Institute of Aeronautics and Astronautics, Inc.

Bayesian interpolation in a dynamic sinusoidal model with application to packet-loss concealment

In this paper, we consider Bayesian interpolation and parameter estimation in a dynamic sinusoidal model. This model is more flexible than the static sinusoidal model since it enables the amplitudes and phases of the sinusoids to be time-varying. For the dynamic sinusoidal model, we derive a Bayesian inference scheme for the missing observations, hidden states and model parameters of the dynamic model. The inference scheme is based on a Markov chain Monte Carlo method known as Gibbs sampler. We illustrate the performance of the inference scheme to the application of packet-loss concealment of lost audio and speech packets. © EURASIP, 2010.

Bayesian parameter identification for vibro-acoustic models with nonparametric uncertainty

Vibration and acoustic analysis at higher frequencies faces two challenges: computing the response without using an excessive number of degrees of freedom, and quantifying its uncertainty due to small spatial variations in geometry, material properties and boundary conditions. Efficient models make use of the observation that when the response of a decoupled vibro-acoustic subsystem is sufficiently sensitive to uncertainty in such spatial variations, the local statistics of its natural frequencies and mode shapes saturate to universal probability distributions. This holds irrespective of the causes that underly these spatial variations and thus leads to a nonparametric description of uncertainty. This work deals with the identification of uncertain parameters in such models by using experimental data. One of the difficulties is that both experimental errors and modeling errors, due to the nonparametric uncertainty that is inherent to the model type, are present. This is tackled by employing a Bayesian inference strategy. The prior probability distribution of the uncertain parameters is constructed using the maximum entropy principle. The likelihood function that is subsequently computed takes the experimental information, the experimental errors and the modeling errors into account. The posterior probability distribution, which is computed with the Markov Chain Monte Carlo method, provides a full uncertainty quantification of the identified parameters, and indicates how well their uncertainty is reduced, with respect to the prior information, by the experimental data. © 2013 Taylor & Francis Group, London.

Single-electron multiple-valued memory using ultra-small floating gate metal-oxide-semiconductor field effect transistor

This paper proposes a novel single-electron multiple-valued memory. It is a metal-oxide-semiconductor field effect transistor (MOS)-type memory with multiple separate control gates and floating gate layer, which consists of nano-crystal grains. The electron can tunnel among the grains (floating gates) and between the floating gate layer and the MOS channel. The memory can realize operations of 'write', 'store' and 'erase' of multiple-valued signals exceeding three values by controlling the single electron tunneling behavior. We use Monte Carlo method to simulate the operation of single-electron four-valued memory. The simulation results show that it can operate well at room temperature.

Quantum-dot growth simulation on periodic stress of substrate

InAs quantum dots (QDs) are grown on the cleaved edge of an InxGa1-xAs/GaAs supperlattice experimentally and a good linear alignment of these QDs on the surface of an InxGa1-xAs layer has been realized. The modulation effects of periodic strain on the substrate are investigated theoretically using a kinetic Monte Carlo method. Our results show that a good alignment of QDs can be achieved when the strain energy reaches 2% of the atomic binding energy. The simulation results are in excellent qualitative agreement with our experiments. (C) 2005 American Institute of Physics.

Transfer property of electron pulse in a femto-second electron diffraction system

An ultra-fast electron diffraction system has been designed. The static and dynamic characters of an electron pulse with 150 fs temporal dispersion are studied during its transmission in the whole ultra-fast electron diffraction system, including the size of the electron spot, temporal dispersion, distribution of azimuths and elevation angles. The initial status of the photoelectrons are put down by Monte Carlo method, both the two dimensional and three dimensional electric fields are calculated by finite difference method and the magnetic flux are. calculated by finite element method.

Effects of convection and solid wall on the diffusion in microscale convection flows

The diffusive transport properties in microscale convection flows are studied by using the direct simulation Monte Carlo method. The effective diffusion coefficient D is computed from the mean square displacements of simulated molecules based on the Einstein diffusion equation D = x2 t /2t. Two typical convection flows, namely, thermal creep convection and Rayleigh– Bénard convection, are investigated. The thermal creep convection in our simulation is in the noncontinuum regime, with the characteristic scale of the vortex varying from 1 to 100 molecular mean free paths. The diffusion is shown to be enhanced only when the vortex scale exceeds a certain critical value, while the diffusion is reduced when the vortex scale is less than the critical value. The reason for phenomenon of diffusion reduction in the noncontinuum regime is that the reduction effect due to solid wall is dominant while the enhancement effect due to convection is negligible. A molecule will lose its memory of macroscopic velocity when it collides with the walls, and thus molecules are hard to diffuse away if they are confined between very close walls. The Rayleigh– Bénard convection in our simulation is in the continuum regime, with the characteristic length of 1000 molecular mean free paths. Under such condition, the effect of solid wall on diffusion is negligible. The diffusion enhancement due to convection is shown to scale as the square root of the Péclet number in the steady convection regime, which is in agreement with previous theoretical and experimental results. In the oscillation convection regime, the diffusion is more strongly enhanced because the molecules can easily advect from one roll to its neighbor due to an oscillation mechanism. © 2010 American Institute of Physics. doi:10.1063/1.3528310

对LVDSMC方法的改进(英文)

最近,Homolle和Hadjiconstantinu提出了新的粒子模拟方法———LVDSMC方法[1],该方法采用了减少方差的思想从而提高了低速流动问题中的计算效率。本文针对LVDSMC方法提出两点改进:第一,除了方法中原来已采用的偏差粒子,在计算近自由分子流问题时建议额外地采用一些辅助粒子,从而可以约束计算过程中原始算法在生成偏差粒子时计算误差的累积效应;第二,提出一个可选的用于计算潜在Maxwell Boltzmann分布函数中的速度参数的增量,从而使得表面的应力及热流的计算变得简单。

Kinetic Studies of Gas Flows

Our recent studies on kinetic behaviors of gas flows are reviewed in this paper. These flows have a wide range of background, but share a common feature that the flow Knudsen number is larger than 0.01. Thus kinetic approaches such as the direct simulation Monte Carlo method are required for their description. In the past few years, we studied several micro/nano-scale flows by developing novel particle simulation approach, and investigated the flows in low-pressure chambers and at high altitude. In addition, the microscopic behaviors of a couple of classical flow problems were analyzed, which shows the potential for kinetic approaches to reveal the microscopic mechanism of gas flows.

气相色谱过程的蒙特卡罗模拟

Based on Monte Carlo method the microscopic gas-phase adsorption chromatographic behaviors of volatile chemical compounds were simulated,and the migration process of those compounds followed by the carrier gases along the chromatographic surface and the process of adsorption-desorption were also described.The programs have been compiled to simulate the processes of thermochromatography and isothermal chromatography with different experimental conditions and properties.The calculated results agree well with ...中文摘要：用蒙特卡罗方法模拟了易挥发化合物的气相色谱微观动力学行为,描述了化合物随气流在固体色谱柱表面的迁移以及吸附-解吸等过程。按气相色谱微观动力学模型编译的计算机程序模拟了超重元素化合物在等温色谱及热色谱的动力学过程,并根据不同实验条件进行了大量计算。计算结果与实验数据较为吻合。讨论了超重元素的半衰期、吸附态的周期、载气流量以及化合物的质量密度等对实验结果的影响及该理论模型的优点和待改进的地方。