An enhanced image binarization method incorporating with Monte-Carlo simulation

We proposed an enhanced image binarization method.The proposed solution incorporates Monte-Carlo simulation into the local thresholding method to address the essential issues with respect to complex background,spatially-changed illumination,and uncertainties of block size in traditional method.The proposed method first partitions the image into square blocks that reflect local characteristics of the image.After image partitioning,each block is binarized using Otsu’s thresholding method.To minimize the influence of the block size and the boundary effect,we incorporate Monte-Carlo simulation into the binarization algorithm.Iterative calculation with varying block sizes during Monte-Carlo simulation generates a probability map,which illustrates the probability of each pixel classified as foreground.By setting a probability threshold,and separating foreground and background of the source image,the final binary image can be obtained.The described method has been tested by benchmark tests.Results demonstrate that the proposed method performs well in dealing with the complex background and illumination condition.

Monte-Carlo Simulation of Surface Crack Growth Rate for Offshore Structural Steel E36-Z35

The Monte- Carlo method is used to simulate the surface fatigue crack growth rate for offshore structural steel E36-Z35, and to determine the distributions and relevance of the parameters in the Paris equation. By this method, the time and cost of fatigue crack propagation testing can be reduced. The application of the method is demonstrated by use of four sets of fatigue crack propagation data for offshore structural steel E36-Z35. A comparison of the test data with the theoretical prediction for surface crack growth rate shows the application of the simulation method to the fatigue crack propagation tests is successful.

MONTE-CARLO SIMULATION FOR ATOMIC DEPOSITION OF AMORPHOUS ELECTROLESS Ni_(80)P_(20) COATING

Atomic growth process and structure of Amorphous Electroless Coating have been studied, using Monte-Carlo simulation method. The simulation results of amorphous Ni80P20 coating show that PDFs are in accordance with practical values. The migrations of adatoms in coating's growth are different from that of solidification of amorphous materials. In some cases, the migrated adatoms in the process of growth of amorphous coating are not enough to occupy all vacancies and traps, so the amorphous coating is micro-porous. The immovable probability k and the largest migration distance of adatoms, which lie on the electroless bath components, affect the PDF, volume density and microporosity remarkably.

New Approach to Simulating the Absorption of Gamma Radiations Using the Monte-Carlo Method: A Computational Study

The following article has been retracted due to the investigation of complaints received against it. Mr. Mohammadali Ghorbani (corresponding author and also the last author) cheated the author’s name: Alireza Heidari. The scientific community takes a very strong view on this matter and we treat all unethical behavior such as plagiarism seriously. This paper published in Vol.3 No.3, 260-265, 2012, has been removed from this site.

Monte-Carlo simulation of a stochastic differential equation

For solving higher dimensional diffusion equations with an inhomogeneous diffusion coefficient,Monte Carlo（MC） techniques are considered to be more effective than other algorithms, such as finite element method or finite difference method. The inhomogeneity of diffusion coefficient strongly limits the use of different numerical techniques. For better convergence, methods with higher orders have been kept forward to allow MC codes with large step size. The main focus of this work is to look for operators that can produce converging results for large step sizes. As a first step, our comparative analysis has been applied to a general stochastic problem.Subsequently, our formulization is applied to the problem of pitch angle scattering resulting from Coulomb collisions of charge particles in the toroidal devices.

A new hybrid method—combined heat flux method with Monte-Carlo method to analyze thermal radiation

A new hybrid method, Monte-Carlo-Heat-Flux （MCHF） method, was presented to analyze the radiative heat transfer of participating medium in a three-dimensional rectangular enclosure using combined the Monte-Carlo method with the heat flux method. Its accuracy and reliability was proved by comparing the computational results with exact results from classical ＂Zone Method＂.

Dynamic simulation of beam-like structure with a crack subjected to a random moving mass oscillator

In this paper, dynamic simulation of a beam-like structure with a transverse open crack subjected to a random moving mass oscillator is investigated. The simultaneous effect of a crack and a random oscillator has not been addressed up to now. The crack in the beam at different locations and with different depths is considered as one group of damage, each as an individual imperfection. In addition, bearing immobility is considered as another type of problem in the beam. Mass, stiffness, damping and velocity of the oscillator are assumed to be random parameters. An improved perturbation technique is applied to reduce the simulation time. It was found that there is a maximum value of the variance of each uncertain parameter, in which the maximum reliability of the perturbation method can be achieved, and that this maximum value can be obtained by the Alpha-Hilber Monte-Carlo simulation method. The simulation results reveal that the mass and the velocity uncertainty cause high uncertainty in the deflection of the beam. Also, the pattern of the deflection is not affected by different random oscillator parameters, and as a result, the type of damage can be identified even with high uncertainty. Moreover, the deflection in the nodes around the mid-span of the beam provides the best information regarding the imperfections, and consequently leads to the best sensor locations in an actual experiment.

Simulation Study on High Energy Cosmic Electron Detection by Shower Image

Many projects have recently been carried out and proposed for observing high energy electrons since it is realized that cosmic ray electrons are very important when studying the dark matter particles and the acceleration mechanism of cosmic rays. An imaging calorimeter, BETS （Balloon-borne Electron Telescope with Scintillator fiber）, has been developed for this purpose. Using pattern analysis of the shower development, the electrons can be selected from those primary cosmic ray proton events with flux heights one-tenth that of the electrons. The Monte-Carlo simulation is indispensable for the instrument design, the signal trigger and the data analysis. We present different shower simulation codes and compare the simulation results with the beam test and the flight data of BETS. We conclude that the code FLUKA2002 gives the most consistent results with the experimental data.

FNM method for estimating reliability of existing bridges

Combined with current specifications and stress characteristics of concrete filled steel tubular （CFST） arch bridges, the determination principle of safe-middle-failure threestage mode is given. Accordingly, damage probability and failure probability and the corresponding reliability indices are calculated; a direct relationship between reliability indices and three-stage working status is made. Based on the three-stage working mode, a combined FNM （finite element-neural network- Monte-Carlo simulation） method is put forward to estimate the reliability of existing bridges. According to time-dependent reliability theory, subsequent service time is divided into several stages; minimum samples required by the Monte-Carlo method are generated by random sampling; training samples are calculated by the finite element method, and the training samples are extended by the neural network; failure probability and damage probability are calculated by the Monte-Carlo method. Thus, time dependent reliability indices are obtained, and the working status is judged. A case study is investigated to estimate the reliability of an actual bridge by the FNM method. The bridge is a CFST arch bridge with an 83.6 m span and it has been in operation for 10 years. According to analysis results, in the tenth year, the example bridge is still in safe status. This conclusion is consistent with the facts, which proves the feasibility of the FNM method for estimating the reliability of existing bridges.

Importance Sampling Method in V-Space

Based on the observation of importance sampling and second order information about the failure surface of a structure, an importance sampling region is defined in V-space which is obtained by rotating a U-space at the point of maximum likelihood. The sampling region is a hyper-ellipsoid that consists of the sampling ellipse on each plane of main curvature in V-space. Thus, the sampling probability density function can be constructed by the sampling region center and ellipsoid axes. Several examples have shown the efficiency and generality of this method.

Probabilistic analysis of embankment slope stability in frozen ground regions based on random finite element method

Prediction on the coupled thermal-hydraulic fields of embankment and cutting slopes is essential to the assessment on evolution of melting zone and natural permafrost table, which is usually a key factor for permafrost embankment design in frozen ground regions. The prediction may be further complicated due to the inherent uncertainties of material properties. Hence, stochastic analyses should be conducted. Firstly, Karhunen-Loeve expansion is applied to attain the random fields for hydraulic and thermal conductions. Next, the mixed-form modified Richards equation for mass transfer （i.e., mass equation） and the heat transport equation for heat transient flow in a variably saturated frozen soil are combined into one equation with temperature unknown. Furthermore, the finite element formulation for the coupled thermal-hydraulic fields is derived. Based on the random fields, the stochastic finite element analyses on stability of embankment are carried out. Numerical results show that stochastic analyses of embankment stability may provide a more rational picture for the distribution of factors of safety （FOS）, which is definitely useful for embankment design in frozen ground regions.

改进的响应面法及其在可靠度分析中的应用

分析了常用的基于响应面迭代的响应面法之不足,提出了改进的响应面法——一阶可靠性方法–响应面法二步法。该方法在第一步计算中用一阶可靠性方法求解可靠指标,用差分法或有理多项式法来求解求导数值,不需形成显式功能函数。然后,在一阶可靠性方法的验算点处进行常规的响应面拟合,并对此响应面用一阶可靠性方法、二阶可靠性方法或蒙特卡罗模拟法求解可靠指标。此方法在整个求解过程中只需拟合一个响应面,实例计算表明,该方法在计算精度及效率上均比常用的基于响应面迭代的响应面法有所提高。

RBFN及SVM在边坡稳定可靠度分析中的应用

基于径向基神经网络(Radial Basis Function Network,简称RBFN)及支持向量机(Support VectorMachine,简称SVM)的类似性,文章采用相同的符号体系,推导了RBFN及SVM在进行函数拟合时的表达式,指出这2种表达式形式上类似,主要区别是参数的计算方法有所不同;以RBFN及SVM的拟合结果为响应面,基于蒙特卡罗模拟法进行了边坡的可靠度分析。计算结果表明,基于RBFN的蒙特卡罗模拟法与基于SVM的蒙特卡罗模拟法具有较高的计算精度及效率,2种方法在计算精度上没有明显的区别。

边坡稳定可靠度分析方法的探讨

在边坡稳定的可靠度分析中 ,导数的求解及可靠度分析方法的选择是十分重要的。笔者分析指出 :可以用简单的差分法来求解导数 ;对于边坡稳定性分析中常用的瑞典条分法及Bishop法 ,当基本变量c、φ属于正态分布时 ,极限状态函数也属于正态分布 ,因此可用中心点法 (MFOSM)求解可靠指标及失效概率 。

COMPARISONS AMONG THE SOLUTIONS OF FIBER TEXTURE VECTOR

The texture vectors, as the fundatnental elements of the vector method (VM), are usually determined by the Durand's iterative method. In present paper, the texture vector is derived by two kinds of the maximum entropy method (MEM), which choose pole figure data (MEM(I)) and the series coefficients of pole figures (MEM(II)), respectively, as a constrained condition. The detailed comparisons, including the texture vector and residual vector in the pole figure and ODF, among the results obtained by different methods are given through the ideal fiber texture simulation with Gaussian distribution. It is demonstrated that, although both methods the good results in the ideal texture simulation, the solution on assumption of maximum entropy displays more attractive results. In order to compare the sensitivity of the different methods to the experimental errors, the stochastical errors in pole figures are introduced by the computer random processes (Monte-Carlo simulation). The Monte-Carlo simulation shows that the MEM with the series coefficients as a constrained condition is rather sensitive to the 'experimental' errors, however, inversely the conventional VM and MEM with pole figure data as a constrained condition.

Analytical reentry guidance framework based on swarm intelligence optimization and altitude-energy profile

Aimed at improving the real-time performance of guidance instruction generation,an analytical hypersonic reentry guidance framework is presented.The key steps of the novel guidance framework are the parameterization of reentry guidance problems and the optimization of parameters.First,a quintic polynomial function of energy was designed to describe the altitude profile.Then,according to the altitude-energy profile,the altitude,velocity,flight path angle,and bank angle were obtained analytically,which naturally met the terminal constraints.In addition,the angle of the attack profile was determined using the velocity parameter.The swarm intelligent optimization algorithms were used to optimize the parameters.The path constraints were enforced by the penalty function method.Finally,extensive simulations were carried out in both nominal and dispersed cases,and the simulation results showed that the proposed guidance framework was effective,high-precision,and robust in different scenarios.

Characterization on jointed rock masses based on PFC2D

Geometrical parameters of discontinuities,such as spacing,length,dip and fault throw between joints have a great influence on the mechanical behavior of jointed rock masses.Accurate characterization for discontinuities is important for investigate the stability of rock masses.In this paper,the PFC2D is combined with joint network generation method to examine the mechanical behaviors of jointed mass.Taking Miaogou Open-pit Mine as an example,the information and statistical distributions of discontinuities of the slope rock masses are measured by ShapeMetriX3D measuring tool.Then,the automatic generation algorithm of random joints network based on the Monte-Carlo method is proposed using the programming language(FISH)embedded within PFC2D.This algorithm could represent the discontinuities compared with the geological surveys.In simulating the compression test of a jointed rock sample,the mechanical behavior and crack propagation were investigated.The results reveal that the failure mode and crack propagation of the jointed rock are dominated by the distribution of joints in addition to the intact rock properties.The simulation result shows the feasibility of the joints generating method in application to jointed rock mass.